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25449 lines
963 KiB
Plaintext
25449 lines
963 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"tags": [
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"exclude"
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]
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},
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"source": [
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"#### Imports"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"tags": [
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"exclude"
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]
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},
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"outputs": [
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{
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"data": {
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"text/html": [
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" <script type=\"text/javascript\">\n",
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" window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
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" if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
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" if (typeof require !== 'undefined') {\n",
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" require.undef(\"plotly\");\n",
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" requirejs.config({\n",
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" paths: {\n",
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" 'plotly': ['https://cdn.plot.ly/plotly-2.30.0.min']\n",
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" }\n",
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" });\n",
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" require(['plotly'], function(Plotly) {\n",
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" window._Plotly = Plotly;\n",
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" });\n",
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" }\n",
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" </script>\n",
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" "
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"C:\\Users\\shahla.huseynova\\source\\repos\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\__init__.py\n"
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]
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}
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],
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"source": [
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"from datetime import timedelta, datetime\n",
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"import json\n",
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"import pprint\n",
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"from copy import deepcopy\n",
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"import pytz\n",
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"\n",
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"import cufflinks\n",
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"cufflinks.go_offline()\n",
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"import numpy as np\n",
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"from numpy.polynomial import Polynomial\n",
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"import pandas as pd\n",
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"from tqdm.notebook import tqdm\n",
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"\n",
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"import sys\n",
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"\n",
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"import os\n",
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" \n",
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"# Path to the folder containing the alternate version of PyRecoy\n",
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"\n",
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"alternate_pyrecoy_path = 'C:\\\\Users\\\\shahla.huseynova\\\\source\\\\repos\\\\Mooi-Kickstart\\\\pyrecoy\\\\pyrecoy'\n",
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" \n",
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"# Add the path to sys.path\n",
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"\n",
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"if alternate_pyrecoy_path not in sys.path:\n",
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"\n",
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" sys.path.insert(0, alternate_pyrecoy_path)\n",
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" \n",
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"# Now import PyRecoy\n",
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"\n",
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"import pyrecoy2\n",
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"\n",
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"# Check the version or path to confirm\n",
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"\n",
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"print(pyrecoy2.__file__)\n",
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"\n",
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"\n",
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"from pyrecoy2.assets import Heatpump, Eboiler, GasBoiler, HotWaterStorage\n",
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"from pyrecoy2.colors import *\n",
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"from pyrecoy2.converters import *\n",
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"from pyrecoy2.financial import calculate_eb_ode, get_tax_tables, get_tax_rate, get_grid_tariffs_electricity\n",
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"from pyrecoy2.framework import TimeFramework\n",
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"from pyrecoy2.casestudy import CaseStudy\n",
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"from pyrecoy2.plotting import ebitda_bar_chart, npv_bar_chart\n",
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"from pyrecoy2.reports import CaseReport, ComparisonReport, BusinessCaseReport, SingleFigureComparison\n",
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"from pyrecoy2.sensitivity import SensitivityAnalysis\n",
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"from pyrecoy2.prices import get_tennet_data, get_afrr_capacity_fees_nl\n",
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"from pyrecoy2.forecasts import Mipf, Forecast\n",
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"\n",
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"%load_ext autoreload\n",
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"%autoreload 2"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"tags": [
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"exclude"
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]
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},
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"source": [
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"#### Development backlog"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"tags": [
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"exclude"
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]
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},
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"source": [
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"* aFRR (can improve the optimisation case)\n",
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"* Report\n",
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"\n",
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"--\n",
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"* Create strategy on imbalance POS (buy 100% day-ahead, and respond to high prices)\n",
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"* Graphs\n",
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" * EBITDA vs. baseline (earnings vs baseline)\n",
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"* Show COP curves in different cases, just for illustration\n",
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"* Energy report --> Check + add gas\n",
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"* Fix comparison reports\n",
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"* Model verification"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"tags": [
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"exclude"
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]
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},
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"source": [
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"#### Meeting Notes"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"tags": [
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"exclude"
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]
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},
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"source": [
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"##### Meeting 25-11-2020"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"tags": [
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"exclude"
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]
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},
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"source": [
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"* aFRR can help optimisation case\n",
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"* SDE++ should be included\n",
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"* Tsource sensitivity really gives interesting insights\n",
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"* Sensitivities should be verified (especially CO2, Tsink, Tsource, time period)\n",
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"* AP TNO: Update/verify COP curve\n",
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"* AP TNO: Update CAPEX\n",
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"* AP Mark: \n",
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" * Create graphs on COP curve with different Tsource, Tsink\n",
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" * Generate table and output in .csv (send it to Andrew)\n",
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"* Investigate opportunity to lower the COP and negative electricity prices\n",
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" * Technically feasible, but not really needed/possible to do it in this project\n",
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"* Could be interesting to run this model on a usecase with higher delta T\n",
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"* Conclusion: Finalize this model, but not add too much extra complexity, next steps is to go towards industrial partners with the results"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"tags": [
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"exclude"
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]
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},
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"source": [
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"# ENCORE : Heatpump Optimisation Framework\n",
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"\n",
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"***\n",
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"© Mark Kremer \n",
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"July 2020\n",
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"##### Cases\n",
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"In this model, 3 cases are compared:\n",
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"* **Baseline** : All heat is supplied by steam turbine\n",
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"* **Heatpump case** : All heat is supplied by heatpump\n",
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"* **Hybrid case** : Steam turbine and heatpump run in hybrid mode, and are optimised on costs in real-time"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"tags": [
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"exclude"
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]
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},
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"source": [
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"#### Loading config"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"tags": [
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"exclude"
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]
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},
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"outputs": [],
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"source": [
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"class Config():\n",
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" start = '2023-01-01'\n",
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" end = '2023-12-31'\n",
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" # year = '2019'\n",
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" # startdate = year + '-01-01'\n",
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" # enddate = str(year) + '-12-31'\n",
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" # start = datetime.strptime(startdate, \"%Y-%m-%d\").astimezone(pytz.timezone('Europe/Amsterdam'))\n",
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" # end = datetime.strptime(enddate, \"%Y-%m-%d\").astimezone(pytz.timezone('Europe/Amsterdam'))\n",
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" # start = start.astimezone(pytz.UTC)\n",
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" # end = end.astimezone(pytz.UTC)\n",
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" \n",
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" hp_vdg_e_power = 23.3 # MW\n",
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" hp_ndg_e_power = 7.7 # MW\n",
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" hp_min_load = 0\n",
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" hp_lifetime = 25\n",
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" hp_capex = 200_000 # EUR/MWth\n",
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" hp_opex = 0.01 # in % of CAPEX\n",
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" hp_devex = 0.005 # in % of CAPEX\n",
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" \n",
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" gb_power = 35 # MW\n",
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" gb_efficiency = 0.9\n",
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" \n",
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" storage_power = 25\n",
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" storage_volume = 1000\n",
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" storage_cap_per_volume = 50 * 1e-3\n",
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" storage_lifetime = 25\n",
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" storage_temperature = 95\n",
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" storage_min_level = storage_volume * storage_cap_per_volume * 0.05\n",
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" storage_capex_per_MW = 7_000\n",
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" storage_capex_per_MWh = 5_000\n",
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" storage_opex_perc_of_capex = 0.02\n",
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" # storage_initial_level = 5\n",
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" threshold = 20\n",
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" \n",
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" tax_bracket_g = 4 \n",
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" tax_bracket_e = 4\n",
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" \n",
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" include_transport_costs = False\n",
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" grid_operator = 'Liander'\n",
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" connection_type = 'TS/MS'\n",
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" \n",
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" discount_rate = 0.1\n",
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" project_duration = 12\n",
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"\n",
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" forecast = 'ForeNeg'\n",
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" gas_price_multiplier = 1\n",
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" e_price_multiplier = 1\n",
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" e_price_volatility_multiplier = 1\n",
|
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" co2_price_multiplier = 1\n",
|
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" tsource_delta = 0\n",
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" tsink_delta = 0\n",
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" energy_tax_multiplier = 1\n",
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" \n",
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" # Review the SDE implementation\n",
|
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" sde_base_amount = 81\n",
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" longterm_gas_price = 24.00\n",
|
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" longterm_co2_price = 37.90\n",
|
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" sde_switch_price_correction = 40\n",
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" \n",
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" day_ahead_buying_perc = 0.3\n",
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" \n",
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" afrr_capacity_fee = 25_000\n",
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"\n",
|
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"c = Config()"
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]
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},
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{
|
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {
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"tags": [
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"exclude"
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]
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},
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"outputs": [],
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"source": [
|
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"class Store():\n",
|
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" pass"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"tags": [
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"exclude"
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]
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},
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"source": [
|
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"## Model set-up"
|
|
]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"source": [
|
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"# Define the file paths\n",
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"excel_file_path = r'C:\\Users\\shahla.huseynova\\source\\repos\\Mooi-Kickstart\\Kickstart\\V2\\Demand_Data_Smurfit_Preprocessed2.xlsx'\n",
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"output_directory = r'C:\\Users\\shahla.huseynova\\source\\repos\\Mooi-Kickstart\\Kickstart\\V2\\data'\n",
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"output_file_name = 'smurfit_demand_preprocessed2.csv'\n",
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"csv_file_path = os.path.join(output_directory, output_file_name)\n",
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"\n",
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"df = pd.read_excel(excel_file_path)\n",
|
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"# df = df.fillna(0) \n",
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"\n",
|
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"# # Save the DataFrame to CSV\n",
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"df.to_csv(csv_file_path, index=False)"
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]
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},
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{
|
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"cell_type": "code",
|
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"execution_count": 5,
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"metadata": {
|
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"tags": [
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"exclude"
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]
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},
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"outputs": [],
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"source": [
|
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"def load_demand_data(c, s):\n",
|
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" demand = pd.read_csv('data/smurfit_demand_preprocessed2.csv', delimiter=',', decimal=';')\n",
|
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" dt_index = pd.date_range(\n",
|
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" start=s.time_fw.start,\n",
|
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" end=s.time_fw.start + timedelta(days=365), \n",
|
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" freq='1T',\n",
|
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" tz='Europe/Amsterdam')\n",
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" dt_index = dt_index[:len(demand)]\n",
|
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" demand.index = dt_index\n",
|
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" demand['Total demand'] = demand['MW (VDG)'] + demand['MW (NDG)']\n",
|
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" demand = demand[c.start:c.end]\n",
|
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" return demand"
|
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]
|
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},
|
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{
|
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"cell_type": "code",
|
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"execution_count": 6,
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"metadata": {},
|
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"outputs": [],
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"source": [
|
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"s = Store()"
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]
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},
|
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{
|
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"cell_type": "code",
|
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"execution_count": 7,
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"metadata": {
|
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"tags": [
|
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"exclude"
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]
|
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},
|
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"outputs": [
|
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{
|
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"name": "stdout",
|
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"output_type": "stream",
|
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"text": [
|
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"testets\n"
|
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]
|
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"C:\\Users\\shahla.huseynova\\source\\repos\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\framework.py:41: UserWarning:\n",
|
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"\n",
|
|
"The chosen timeperiod spans 365.99930555555557 days, which is not a full year. Beware that certain functions that use yearly rates might return incorrect values.\n",
|
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"\n",
|
|
"C:\\Users\\shahla.huseynova\\source\\repos\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\forecasts.py:62: FutureWarning:\n",
|
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"\n",
|
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"'T' is deprecated and will be removed in a future version, please use 'min' instead.\n",
|
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"\n",
|
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"C:\\Users\\shahla.huseynova\\source\\repos\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\forecasts.py:115: FutureWarning:\n",
|
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"\n",
|
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"'T' is deprecated and will be removed in a future version, please use 'min' instead.\n",
|
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"\n",
|
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"C:\\Users\\shahla.huseynova\\source\\repos\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\framework.py:54: FutureWarning:\n",
|
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"\n",
|
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"'T' is deprecated and will be removed in a future version, please use 'min' instead.\n",
|
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"\n",
|
|
"C:\\Users\\shahla.huseynova\\source\\repos\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\framework.py:54: FutureWarning:\n",
|
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"\n",
|
|
"'T' is deprecated and will be removed in a future version, please use 'min' instead.\n",
|
|
"\n",
|
|
"C:\\Users\\shahla.huseynova\\source\\repos\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\framework.py:54: FutureWarning:\n",
|
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"\n",
|
|
"'T' is deprecated and will be removed in a future version, please use 'min' instead.\n",
|
|
"\n",
|
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"C:\\Users\\shahla.huseynova\\AppData\\Local\\Temp\\ipykernel_31900\\3886619535.py:3: FutureWarning:\n",
|
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"\n",
|
|
"'T' is deprecated and will be removed in a future version, please use 'min' instead.\n",
|
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"\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"def setup_model(c):\n",
|
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" s = Store()\n",
|
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" \n",
|
|
" s.time_fw = TimeFramework(start=c.start, end=c.end)\n",
|
|
" # s.minute_ix = s.time_fw.dt_index(freq='1T')\n",
|
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" mipf = Mipf(None, start=s.time_fw.start, end=s.time_fw.end, from_database=True, add_days_to_start_end=False).data\n",
|
|
" s.mipf = mipf\n",
|
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" s.baseline = CaseStudy(time_fw=s.time_fw, freq='1T', name='Baseline')\n",
|
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" s.hpcase = CaseStudy(time_fw=s.time_fw, freq='1T', name='Heatpump only', data=mipf)\n",
|
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" #s.hpcase_sde = CaseStudy(time_fw=s.time_fw, freq='1T', name='Heatpump + SDE', data=mipf)\n",
|
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" #s.optcase1 = CaseStudy(time_fw=s.time_fw, freq='1T', name='Optimisation', data=mipf)\n",
|
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" #s.afrr_case = CaseStudy(time_fw=s.time_fw, freq='1T', name='Optimisation + aFRR', data=mipf)\n",
|
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" s.storage_case_PCM = CaseStudy(time_fw=s.time_fw, freq='1T', name='Heatpump + Storage_PCM', data=mipf)\n",
|
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" # s.storage_case_TCM = CaseStudy(time_fw=s.time_fw, freq='1T', name='Heatpump + Storage_TCM', data=mipf)\n",
|
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" # s.storage_case_battery = CaseStudy(time_fw=s.time_fw, freq='1T', name='Heatpump + Storage_battery', data=mipf)\n",
|
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" s.cases = list(CaseStudy.instances.values())\n",
|
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" #s.optcases = [s.hpcase, s.hpcase_sde, s.optcase1, s.afrr_case]\n",
|
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" s.optcases = [s.hpcase, s.storage_case_PCM]\n",
|
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" #s.sde_cases = [s.hpcase_sde, s.optcase1, s.afrr_case]\n",
|
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" s.sde_cases = []\n",
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" \n",
|
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" s.demand = load_demand_data(c, s)\n",
|
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" return s\n",
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"\n",
|
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"s = setup_model(c)"
|
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]
|
|
},
|
|
{
|
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"cell_type": "code",
|
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"execution_count": 8,
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"metadata": {},
|
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"outputs": [
|
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"C:\\Users\\shahla.huseynova\\AppData\\Local\\Temp\\ipykernel_31900\\2657160476.py:1: FutureWarning:\n",
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|
"\n",
|
|
"'T' is deprecated and will be removed in a future version, please use 'min' instead.\n",
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|
"\n",
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"C:\\Users\\shahla.huseynova\\AppData\\Roaming\\Python\\Python310\\site-packages\\cufflinks\\plotlytools.py:117: FutureWarning:\n",
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"2023-01-04 04:15:00+01:00",
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"2023-01-04 04:30:00+01:00",
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"2023-01-04 04:45:00+01:00",
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"2023-01-04 05:15:00+01:00",
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"2023-01-04 05:30:00+01:00",
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"2023-01-04 05:45:00+01:00",
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"2023-01-04 06:15:00+01:00",
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"2023-01-04 07:15:00+01:00",
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"2023-01-04 07:30:00+01:00",
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"2023-01-04 08:15:00+01:00",
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"2023-01-04 08:45:00+01:00",
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"2023-01-04 09:15:00+01:00",
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"2023-01-04 09:30:00+01:00",
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"2023-01-04 09:45:00+01:00",
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"2023-01-04 10:15:00+01:00",
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"2023-01-04 10:30:00+01:00",
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"2023-01-04 10:45:00+01:00",
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"2023-01-04 11:00:00+01:00",
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"2023-01-04 11:15:00+01:00",
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"2023-01-04 11:30:00+01:00",
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"2023-01-04 11:45:00+01:00",
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"2023-01-04 12:00:00+01:00",
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"2023-01-04 12:15:00+01:00",
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"2023-01-04 12:30:00+01:00",
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"2023-01-04 12:45:00+01:00",
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"2023-01-04 13:00:00+01:00",
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"2023-01-04 13:15:00+01:00",
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"2023-01-04 13:30:00+01:00",
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"2023-01-04 13:45:00+01:00",
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"2023-01-04 14:15:00+01:00",
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"2023-01-04 14:30:00+01:00",
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"2023-01-04 17:15:00+01:00",
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"2023-01-04 17:30:00+01:00",
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"2023-01-04 17:45:00+01:00",
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"2023-01-04 18:15:00+01:00",
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"2023-01-04 18:30:00+01:00",
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"2023-01-04 18:45:00+01:00",
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"2023-01-04 19:15:00+01:00",
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"2023-01-04 20:15:00+01:00",
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"2023-01-04 21:15:00+01:00",
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"2023-01-04 21:30:00+01:00",
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"2023-01-04 21:45:00+01:00",
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"2023-01-04 22:15:00+01:00",
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"2023-01-04 23:15:00+01:00",
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"2023-01-04 23:45:00+01:00",
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"2023-01-05 00:15:00+01:00",
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"2023-01-05 01:15:00+01:00",
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"2023-01-05 02:15:00+01:00",
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"2023-01-05 03:00:00+01:00",
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"2023-01-05 03:15:00+01:00",
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"2023-01-05 04:15:00+01:00",
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"2023-01-05 04:45:00+01:00",
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"2023-01-05 05:15:00+01:00",
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"2023-01-05 05:30:00+01:00",
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"2023-01-05 05:45:00+01:00",
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"2023-01-05 06:15:00+01:00",
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"2023-01-05 06:30:00+01:00",
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"2023-01-05 07:15:00+01:00",
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"2023-01-05 07:30:00+01:00",
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"2023-01-05 07:45:00+01:00",
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"2023-01-05 08:15:00+01:00",
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"2023-01-05 08:30:00+01:00",
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"2023-01-05 08:45:00+01:00",
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"2023-01-05 09:00:00+01:00",
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"2023-01-05 09:15:00+01:00",
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"2023-01-05 09:30:00+01:00",
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"2023-01-05 09:45:00+01:00",
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"2023-01-05 10:15:00+01:00",
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"2023-01-05 10:30:00+01:00",
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"2023-01-05 10:45:00+01:00",
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"2023-01-05 11:00:00+01:00",
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"2023-01-05 11:15:00+01:00",
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"2023-01-05 11:30:00+01:00",
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"2023-01-05 11:45:00+01:00",
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"2023-01-05 12:00:00+01:00",
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"2023-01-05 12:15:00+01:00",
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"2023-01-05 12:30:00+01:00",
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"2023-01-05 12:45:00+01:00",
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"2023-01-05 13:00:00+01:00",
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"2023-01-05 13:15:00+01:00",
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"2023-01-05 13:30:00+01:00",
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"2023-01-05 13:45:00+01:00",
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"2023-01-05 14:00:00+01:00",
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"2023-01-05 14:15:00+01:00",
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"2023-01-05 14:30:00+01:00",
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"2023-01-05 14:45:00+01:00",
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"2023-01-05 15:00:00+01:00",
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"2023-01-05 15:15:00+01:00",
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"2023-01-05 15:30:00+01:00",
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"2023-01-05 15:45:00+01:00",
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"2023-01-05 16:00:00+01:00",
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"2023-01-05 16:15:00+01:00",
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"2023-01-05 16:30:00+01:00",
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"2023-01-05 16:45:00+01:00",
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"2023-01-05 17:00:00+01:00",
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"2023-01-05 17:15:00+01:00",
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"2023-01-05 17:30:00+01:00",
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"2023-01-05 17:45:00+01:00",
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"2023-01-05 18:00:00+01:00",
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"2023-01-05 18:15:00+01:00",
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"2023-01-05 18:30:00+01:00",
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"2023-01-05 18:45:00+01:00",
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"2023-01-05 19:00:00+01:00",
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"2023-01-05 19:15:00+01:00",
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"2023-01-05 19:30:00+01:00",
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"2023-01-05 19:45:00+01:00",
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"2023-01-05 20:00:00+01:00",
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"2023-01-05 20:15:00+01:00",
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"2023-01-05 20:30:00+01:00",
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"2023-01-05 20:45:00+01:00",
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"2023-01-05 21:00:00+01:00",
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"2023-01-05 21:15:00+01:00",
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"2023-01-05 21:30:00+01:00",
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"2023-01-05 21:45:00+01:00",
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"2023-01-05 22:00:00+01:00",
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"2023-01-05 22:15:00+01:00",
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"2023-01-05 22:30:00+01:00",
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"2023-01-05 22:45:00+01:00",
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"2023-01-05 23:00:00+01:00",
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"2023-01-05 23:15:00+01:00",
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"2023-01-05 23:30:00+01:00",
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"2023-01-05 23:45:00+01:00",
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"2023-01-06 00:00:00+01:00",
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"2023-01-06 00:15:00+01:00",
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"2023-01-06 00:30:00+01:00",
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"2023-01-06 00:45:00+01:00",
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"2023-01-06 01:00:00+01:00",
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"2023-01-06 01:15:00+01:00",
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"2023-01-06 01:30:00+01:00",
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"2023-01-06 01:45:00+01:00",
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"2023-01-06 02:00:00+01:00",
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"2023-01-06 02:15:00+01:00",
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"2023-01-06 02:30:00+01:00",
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"2023-01-06 02:45:00+01:00",
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"2023-01-06 03:00:00+01:00",
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"2023-01-06 03:15:00+01:00",
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"2023-01-06 03:30:00+01:00",
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"2023-01-06 03:45:00+01:00",
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"2023-01-06 04:00:00+01:00",
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"2023-01-06 04:15:00+01:00",
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"2023-01-06 04:30:00+01:00",
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"2023-01-06 04:45:00+01:00",
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"2023-01-06 05:00:00+01:00",
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"2023-01-06 05:15:00+01:00",
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"2023-01-06 05:30:00+01:00",
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"2023-01-06 05:45:00+01:00",
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"2023-01-06 06:00:00+01:00",
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"2023-01-06 06:15:00+01:00",
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"2023-01-06 06:30:00+01:00",
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"2023-01-06 06:45:00+01:00",
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"2023-01-06 07:00:00+01:00",
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"2023-01-06 07:15:00+01:00",
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"2023-01-06 07:30:00+01:00",
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"2023-01-06 07:45:00+01:00",
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"2023-01-06 08:00:00+01:00",
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"2023-01-06 08:15:00+01:00",
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"2023-01-06 08:30:00+01:00",
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"2023-01-06 08:45:00+01:00",
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"2023-01-06 09:00:00+01:00",
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"2023-01-06 09:15:00+01:00",
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"2023-01-06 09:30:00+01:00",
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"2023-01-06 09:45:00+01:00",
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"2023-01-06 10:00:00+01:00",
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"2023-01-06 10:15:00+01:00",
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"2023-01-06 10:30:00+01:00",
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"2023-01-06 10:45:00+01:00",
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"2023-01-06 11:00:00+01:00",
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"2023-01-06 11:15:00+01:00",
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"2023-01-06 11:30:00+01:00",
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"2023-01-06 11:45:00+01:00",
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"2023-01-06 12:00:00+01:00",
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"2023-01-06 12:15:00+01:00",
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"2023-01-06 12:30:00+01:00",
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"2023-01-06 12:45:00+01:00",
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"2023-01-06 13:00:00+01:00",
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"2023-01-06 13:15:00+01:00",
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"2023-01-06 13:30:00+01:00",
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"2023-01-06 13:45:00+01:00",
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"2023-01-06 14:00:00+01:00",
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"2023-01-06 14:15:00+01:00",
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"2023-01-06 14:30:00+01:00",
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"2023-01-06 14:45:00+01:00",
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"2023-01-06 15:00:00+01:00",
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"2023-01-06 15:15:00+01:00",
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"2023-01-06 15:30:00+01:00",
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"2023-01-06 15:45:00+01:00",
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"2023-01-06 16:00:00+01:00",
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"2023-01-06 16:15:00+01:00",
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"2023-01-06 16:30:00+01:00",
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"2023-01-06 16:45:00+01:00",
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"2023-01-06 17:00:00+01:00",
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"2023-01-06 17:15:00+01:00",
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"2023-01-06 17:30:00+01:00",
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"2023-01-06 17:45:00+01:00",
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"2023-01-06 18:00:00+01:00",
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"2023-01-06 18:15:00+01:00",
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"2023-01-06 18:30:00+01:00",
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"2023-01-06 18:45:00+01:00",
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"2023-01-06 19:00:00+01:00",
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"2023-01-06 19:15:00+01:00",
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"2023-01-06 19:30:00+01:00",
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"2023-01-06 19:45:00+01:00",
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"2023-01-06 20:00:00+01:00",
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"2023-01-06 20:15:00+01:00",
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"2023-01-06 20:30:00+01:00",
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"2023-01-06 20:45:00+01:00",
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"2023-01-06 21:00:00+01:00",
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"2023-01-06 21:15:00+01:00",
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"2023-01-06 21:30:00+01:00",
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"2023-01-06 21:45:00+01:00",
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"2023-01-06 22:00:00+01:00",
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"2023-01-06 22:15:00+01:00",
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"2023-01-06 22:30:00+01:00",
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"2023-01-06 22:45:00+01:00",
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"2023-01-06 23:00:00+01:00",
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"2023-01-06 23:15:00+01:00",
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"2023-01-06 23:30:00+01:00",
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"2023-01-06 23:45:00+01:00",
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"2023-01-07 00:00:00+01:00",
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"2023-01-07 00:15:00+01:00",
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"2023-01-07 00:30:00+01:00",
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"2023-01-07 00:45:00+01:00",
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"2023-01-07 01:00:00+01:00",
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"2023-01-07 01:15:00+01:00",
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"2023-01-07 01:30:00+01:00",
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"2023-01-07 01:45:00+01:00",
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"2023-01-07 02:00:00+01:00",
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"2023-01-07 02:15:00+01:00",
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"2023-01-07 02:30:00+01:00",
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"2023-01-07 02:45:00+01:00",
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"2023-01-07 03:00:00+01:00",
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"2023-01-07 03:15:00+01:00",
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"2023-01-07 03:30:00+01:00",
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"2023-01-07 03:45:00+01:00",
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"2023-01-07 04:00:00+01:00",
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"2023-01-07 04:15:00+01:00",
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"2023-01-07 04:30:00+01:00",
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"2023-01-07 04:45:00+01:00",
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"2023-01-07 05:00:00+01:00",
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"2023-01-07 05:15:00+01:00",
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"2023-01-07 05:30:00+01:00",
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"2023-01-07 05:45:00+01:00",
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"2023-01-07 06:00:00+01:00",
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"2023-01-07 06:15:00+01:00",
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"2023-01-07 06:30:00+01:00",
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"2023-01-07 06:45:00+01:00",
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"2023-01-07 07:00:00+01:00",
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"2023-01-07 07:15:00+01:00",
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"2023-01-07 07:30:00+01:00",
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"2023-01-07 07:45:00+01:00",
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"2023-01-07 08:00:00+01:00",
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"2023-01-07 08:15:00+01:00",
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"2023-01-07 08:30:00+01:00",
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"2023-01-07 08:45:00+01:00",
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"2023-01-07 09:00:00+01:00",
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"2023-01-07 09:15:00+01:00",
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"2023-01-07 09:30:00+01:00",
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"2023-01-07 09:45:00+01:00",
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"2023-01-07 10:00:00+01:00",
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"2023-01-07 10:15:00+01:00",
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"2023-01-07 10:30:00+01:00",
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"2023-01-07 10:45:00+01:00",
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"2023-01-07 11:00:00+01:00",
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"2023-01-07 11:15:00+01:00",
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"2023-01-07 11:30:00+01:00",
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"2023-01-07 11:45:00+01:00",
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"2023-01-07 12:00:00+01:00",
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"2023-01-07 12:15:00+01:00",
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"2023-01-07 12:30:00+01:00",
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"2023-01-07 12:45:00+01:00",
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"2023-01-07 13:00:00+01:00",
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"2023-01-07 13:15:00+01:00",
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"2023-01-07 13:30:00+01:00",
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"2023-01-07 13:45:00+01:00",
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"2023-01-07 14:00:00+01:00",
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"2023-01-07 14:15:00+01:00",
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"2023-01-07 14:30:00+01:00",
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"2023-01-07 14:45:00+01:00",
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"2023-01-07 15:00:00+01:00",
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"2023-01-07 15:15:00+01:00",
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"2023-01-07 15:30:00+01:00",
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"2023-01-07 15:45:00+01:00",
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"2023-01-07 16:00:00+01:00",
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"2023-01-07 16:15:00+01:00",
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"2023-01-07 16:30:00+01:00",
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"2023-01-07 16:45:00+01:00",
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"2023-01-07 17:00:00+01:00",
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"2023-01-07 17:15:00+01:00",
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"2023-01-07 17:30:00+01:00",
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"2023-01-07 17:45:00+01:00",
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"2023-01-07 18:00:00+01:00",
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"2023-01-07 18:15:00+01:00",
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"2023-01-07 18:30:00+01:00",
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"2023-01-07 18:45:00+01:00",
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"2023-01-07 19:00:00+01:00",
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"2023-01-07 19:15:00+01:00",
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"2023-01-07 19:30:00+01:00",
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"2023-01-07 19:45:00+01:00",
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"2023-01-07 20:00:00+01:00",
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"2023-01-07 20:15:00+01:00",
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"2023-01-07 20:30:00+01:00",
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"2023-01-07 20:45:00+01:00",
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"2023-01-07 21:00:00+01:00",
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"2023-01-07 21:15:00+01:00",
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"2023-01-07 21:30:00+01:00",
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"2023-01-07 21:45:00+01:00",
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"2023-01-07 22:00:00+01:00",
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"2023-01-07 22:15:00+01:00",
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"2023-01-07 22:30:00+01:00",
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"2023-01-07 22:45:00+01:00",
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"2023-01-07 23:00:00+01:00",
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"2023-01-07 23:15:00+01:00",
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"2023-01-07 23:30:00+01:00",
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"2023-01-07 23:45:00+01:00",
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"2023-01-08 00:00:00+01:00",
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"2023-01-08 00:15:00+01:00",
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"2023-01-08 00:30:00+01:00",
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"2023-01-08 00:45:00+01:00",
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"2023-01-08 01:00:00+01:00",
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"2023-01-08 01:15:00+01:00",
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"2023-01-08 01:30:00+01:00",
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"2023-01-08 01:45:00+01:00",
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"2023-01-08 02:00:00+01:00",
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"2023-01-08 02:15:00+01:00",
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"2023-01-08 02:30:00+01:00",
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"2023-01-08 02:45:00+01:00",
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"2023-01-08 03:00:00+01:00",
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"2023-01-08 03:15:00+01:00",
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"2023-01-08 03:30:00+01:00",
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"2023-01-08 03:45:00+01:00",
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"2023-01-08 04:00:00+01:00",
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"2023-01-08 04:15:00+01:00",
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"2023-01-08 04:30:00+01:00",
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"2023-01-08 04:45:00+01:00",
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"2023-01-08 05:00:00+01:00",
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"2023-01-08 05:15:00+01:00",
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"2023-01-08 05:30:00+01:00",
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"2023-01-08 05:45:00+01:00",
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"2023-01-08 06:00:00+01:00",
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"2023-01-08 06:15:00+01:00",
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"2023-01-08 06:30:00+01:00",
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"2023-01-08 06:45:00+01:00",
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"2023-01-08 07:00:00+01:00",
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"2023-01-08 07:15:00+01:00",
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"2023-01-08 07:30:00+01:00",
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"2023-01-08 07:45:00+01:00",
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"2023-01-08 08:00:00+01:00",
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"2023-01-08 08:15:00+01:00",
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"2023-01-08 08:30:00+01:00",
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"2023-01-08 08:45:00+01:00",
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"2023-01-08 09:00:00+01:00",
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"2023-01-08 09:15:00+01:00",
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"2023-01-08 09:30:00+01:00",
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"2023-01-08 09:45:00+01:00",
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"2023-01-08 10:00:00+01:00",
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"2023-01-08 10:15:00+01:00",
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"2023-01-08 10:30:00+01:00",
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"2023-01-08 10:45:00+01:00",
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"2023-01-08 11:00:00+01:00",
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"2023-01-08 11:15:00+01:00",
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"2023-01-08 11:30:00+01:00",
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"2023-01-08 11:45:00+01:00",
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"2023-01-08 12:00:00+01:00",
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"2023-01-08 12:15:00+01:00",
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"2023-01-08 12:30:00+01:00",
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"2023-01-08 12:45:00+01:00",
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"2023-01-08 13:00:00+01:00",
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"2023-01-08 13:15:00+01:00",
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"2023-01-08 13:30:00+01:00",
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"2023-01-08 13:45:00+01:00",
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"2023-01-08 14:00:00+01:00",
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"2023-01-08 14:15:00+01:00",
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"2023-01-08 14:30:00+01:00",
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"2023-01-08 14:45:00+01:00",
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"2023-01-08 15:00:00+01:00",
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"2023-01-08 15:15:00+01:00",
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"2023-01-08 15:30:00+01:00",
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"2023-01-08 15:45:00+01:00",
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"2023-01-08 16:00:00+01:00",
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"2023-01-08 16:15:00+01:00",
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"2023-01-08 16:30:00+01:00",
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"2023-01-08 16:45:00+01:00",
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"2023-01-08 17:00:00+01:00",
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"2023-01-08 17:15:00+01:00",
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"2023-01-08 17:30:00+01:00",
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"2023-01-08 17:45:00+01:00",
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"2023-01-08 18:00:00+01:00",
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"2023-01-08 18:15:00+01:00",
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"2023-01-08 18:30:00+01:00",
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"2023-01-08 18:45:00+01:00",
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"2023-01-08 19:00:00+01:00",
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"2023-01-08 19:15:00+01:00",
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"2023-01-08 19:30:00+01:00",
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"2023-01-08 19:45:00+01:00",
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"2023-01-08 20:00:00+01:00",
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"2023-01-08 20:15:00+01:00",
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"2023-01-08 20:30:00+01:00",
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"2023-01-08 20:45:00+01:00",
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"2023-01-08 21:00:00+01:00",
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"2023-01-08 21:15:00+01:00",
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"2023-01-08 21:30:00+01:00",
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"2023-01-08 21:45:00+01:00",
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"2023-01-08 22:00:00+01:00",
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"2023-01-08 22:15:00+01:00",
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"2023-01-08 22:30:00+01:00",
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"2023-01-08 22:45:00+01:00",
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"2023-01-08 23:00:00+01:00",
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"2023-01-08 23:15:00+01:00",
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"2023-01-08 23:30:00+01:00",
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"2023-01-08 23:45:00+01:00",
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"2023-01-09 00:00:00+01:00",
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"2023-01-09 00:15:00+01:00",
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"2023-01-09 00:30:00+01:00",
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"2023-01-09 00:45:00+01:00",
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"2023-01-09 01:00:00+01:00",
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"2023-01-09 01:15:00+01:00",
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"2023-01-09 01:30:00+01:00",
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"2023-01-09 01:45:00+01:00",
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"2023-01-09 02:00:00+01:00",
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"2023-01-09 02:15:00+01:00",
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"2023-01-09 02:30:00+01:00",
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"2023-01-09 02:45:00+01:00",
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"2023-01-09 03:00:00+01:00",
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"2023-01-09 03:15:00+01:00",
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"2023-01-09 03:30:00+01:00",
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"2023-01-09 03:45:00+01:00",
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"2023-01-09 04:00:00+01:00",
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"2023-01-09 04:15:00+01:00",
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"2023-01-09 04:30:00+01:00",
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"2023-01-09 04:45:00+01:00",
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"2023-01-09 05:00:00+01:00",
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"2023-01-09 05:15:00+01:00",
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"2023-01-09 05:30:00+01:00",
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"2023-01-09 05:45:00+01:00",
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"2023-01-09 06:00:00+01:00",
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"2023-01-09 06:15:00+01:00",
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"2023-01-09 06:30:00+01:00",
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"2023-01-09 06:45:00+01:00",
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"2023-01-09 07:00:00+01:00",
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"2023-01-09 07:15:00+01:00",
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"2023-01-09 07:30:00+01:00",
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"2023-01-09 07:45:00+01:00",
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"2023-01-09 08:00:00+01:00",
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"2023-01-09 08:15:00+01:00",
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"2023-01-09 08:30:00+01:00",
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"2023-01-09 08:45:00+01:00",
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"2023-01-09 09:00:00+01:00",
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"2023-01-09 09:15:00+01:00",
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"2023-01-09 09:30:00+01:00",
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"2023-01-09 09:45:00+01:00",
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"2023-01-09 10:00:00+01:00",
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"2023-01-09 10:15:00+01:00",
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"2023-01-09 10:30:00+01:00",
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"2023-01-09 10:45:00+01:00",
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"2023-01-09 11:00:00+01:00",
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"2023-01-09 11:15:00+01:00",
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"2023-01-09 11:30:00+01:00",
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"2023-01-09 11:45:00+01:00",
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"2023-01-09 12:00:00+01:00",
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"2023-01-09 12:15:00+01:00",
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"2023-01-09 12:30:00+01:00",
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"2023-01-09 12:45:00+01:00",
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"2023-01-09 13:00:00+01:00",
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"2023-01-09 13:15:00+01:00",
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"2023-01-09 13:30:00+01:00",
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"2023-01-09 13:45:00+01:00",
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"2023-01-09 14:00:00+01:00",
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"2023-01-09 14:15:00+01:00",
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"2023-01-09 14:30:00+01:00",
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"2023-01-09 14:45:00+01:00",
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"2023-01-09 15:00:00+01:00",
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"2023-01-09 15:15:00+01:00",
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"2023-01-09 15:30:00+01:00",
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"2023-01-09 15:45:00+01:00",
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"2023-01-09 16:00:00+01:00",
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"2023-01-09 16:15:00+01:00",
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"2023-01-09 16:30:00+01:00",
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"2023-01-09 16:45:00+01:00",
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"2023-01-09 17:00:00+01:00",
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"2023-01-09 17:15:00+01:00",
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"2023-01-09 17:30:00+01:00",
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"2023-01-09 17:45:00+01:00",
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"2023-01-09 18:00:00+01:00",
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"2023-01-09 18:15:00+01:00",
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"2023-01-09 18:30:00+01:00",
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"2023-01-09 18:45:00+01:00",
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"2023-01-09 19:00:00+01:00",
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"2023-01-09 19:15:00+01:00",
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"2023-01-09 19:30:00+01:00",
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"2023-01-09 19:45:00+01:00",
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"2023-01-09 20:00:00+01:00",
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"2023-01-09 20:15:00+01:00",
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"2023-01-09 20:30:00+01:00",
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"2023-01-09 20:45:00+01:00",
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"2023-01-09 21:00:00+01:00",
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"2023-01-09 21:15:00+01:00",
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"2023-01-09 21:30:00+01:00",
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"2023-01-09 21:45:00+01:00",
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"2023-01-09 22:00:00+01:00",
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"2023-01-09 22:15:00+01:00",
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"2023-01-09 22:30:00+01:00",
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"2023-01-09 22:45:00+01:00",
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"2023-01-09 23:00:00+01:00",
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"2023-01-09 23:15:00+01:00",
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"2023-01-09 23:30:00+01:00",
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"2023-01-09 23:45:00+01:00",
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"2023-01-10 00:00:00+01:00",
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"2023-01-10 00:15:00+01:00",
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"2023-01-10 00:30:00+01:00",
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"2023-01-10 00:45:00+01:00",
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"2023-01-10 01:00:00+01:00",
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"2023-01-10 01:15:00+01:00",
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"2023-01-10 01:30:00+01:00",
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"2023-01-10 01:45:00+01:00",
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"2023-01-10 02:00:00+01:00",
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"2023-01-10 02:15:00+01:00",
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"2023-01-10 02:30:00+01:00",
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"2023-01-10 02:45:00+01:00",
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"2023-01-10 03:00:00+01:00",
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"2023-01-10 03:15:00+01:00",
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"2023-01-10 03:30:00+01:00",
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"2023-01-10 03:45:00+01:00",
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"2023-01-10 04:00:00+01:00",
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"2023-01-10 04:15:00+01:00",
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"2023-01-10 04:30:00+01:00",
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"2023-01-10 04:45:00+01:00",
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"2023-01-10 05:00:00+01:00",
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"2023-01-10 05:15:00+01:00",
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"2023-01-10 05:30:00+01:00",
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"2023-01-10 05:45:00+01:00",
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"2023-01-10 06:00:00+01:00",
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"2023-01-10 06:15:00+01:00",
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"2023-01-10 06:30:00+01:00",
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"2023-01-10 06:45:00+01:00",
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"2023-01-10 07:00:00+01:00",
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"2023-01-10 07:15:00+01:00",
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"2023-01-10 07:30:00+01:00",
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"2023-01-10 07:45:00+01:00",
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"2023-01-10 08:00:00+01:00",
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"2023-01-10 08:15:00+01:00",
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"2023-01-10 08:30:00+01:00",
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"2023-01-10 08:45:00+01:00",
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"2023-01-10 09:00:00+01:00",
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"2023-01-10 09:15:00+01:00",
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"2023-01-10 09:30:00+01:00",
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"2023-01-10 09:45:00+01:00",
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"2023-01-10 10:00:00+01:00",
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"2023-01-10 10:15:00+01:00",
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"2023-01-10 10:30:00+01:00",
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"2023-01-10 10:45:00+01:00",
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"2023-01-10 11:00:00+01:00",
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"2023-01-10 11:15:00+01:00",
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"2023-01-10 11:30:00+01:00",
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"2023-01-10 11:45:00+01:00",
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"2023-01-10 12:00:00+01:00",
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"2023-01-10 12:15:00+01:00",
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"2023-01-10 12:30:00+01:00",
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"2023-01-10 12:45:00+01:00",
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"2023-01-10 13:00:00+01:00",
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"2023-01-10 13:15:00+01:00",
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"2023-01-10 13:30:00+01:00",
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"2023-01-10 13:45:00+01:00",
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"2023-01-10 14:00:00+01:00",
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"2023-01-10 14:15:00+01:00",
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"2023-01-10 14:30:00+01:00",
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"2023-01-10 14:45:00+01:00",
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"2023-01-10 15:00:00+01:00",
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"2023-01-10 15:15:00+01:00",
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"2023-01-10 15:30:00+01:00",
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"2023-01-10 15:45:00+01:00",
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"2023-01-10 16:00:00+01:00",
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"2023-01-10 16:15:00+01:00",
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"2023-01-10 16:30:00+01:00",
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"2023-01-10 16:45:00+01:00",
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"2023-01-10 17:00:00+01:00",
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"2023-01-10 17:15:00+01:00",
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"2023-01-10 17:30:00+01:00",
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"2023-01-10 17:45:00+01:00",
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"2023-01-10 18:00:00+01:00",
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"2023-01-10 18:15:00+01:00",
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"2023-01-10 18:30:00+01:00",
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"2023-01-10 18:45:00+01:00",
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"2023-01-10 19:00:00+01:00",
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"2023-01-10 19:15:00+01:00",
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"2023-01-10 19:30:00+01:00",
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"2023-01-10 19:45:00+01:00",
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"2023-01-10 20:00:00+01:00",
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"2023-01-10 20:15:00+01:00",
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"2023-01-10 20:30:00+01:00",
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"2023-01-10 20:45:00+01:00",
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"2023-01-10 21:00:00+01:00",
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"2023-01-10 21:15:00+01:00",
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"2023-01-10 21:30:00+01:00",
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"2023-01-10 21:45:00+01:00",
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"2023-01-10 22:00:00+01:00",
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"2023-01-10 22:15:00+01:00",
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"2023-01-10 22:30:00+01:00",
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"2023-01-10 22:45:00+01:00",
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"2023-01-10 23:00:00+01:00",
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"2023-01-10 23:15:00+01:00",
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"2023-01-10 23:30:00+01:00",
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"2023-01-10 23:45:00+01:00",
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"2023-01-11 00:00:00+01:00",
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"2023-01-11 00:15:00+01:00",
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"2023-01-11 00:30:00+01:00",
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"2023-01-11 00:45:00+01:00",
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"2023-01-11 01:00:00+01:00",
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"2023-01-11 01:15:00+01:00",
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"2023-01-11 01:30:00+01:00",
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"2023-01-11 01:45:00+01:00",
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"2023-01-11 02:00:00+01:00",
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"2023-01-11 02:15:00+01:00",
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"2023-01-11 02:30:00+01:00",
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"2023-01-11 02:45:00+01:00",
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"2023-01-11 03:00:00+01:00",
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"2023-01-11 03:15:00+01:00",
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"2023-01-11 03:30:00+01:00",
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"2023-01-11 03:45:00+01:00",
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"2023-01-11 04:00:00+01:00",
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"2023-01-11 04:15:00+01:00",
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"2023-01-11 04:30:00+01:00",
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"2023-01-11 04:45:00+01:00",
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"2023-01-11 05:00:00+01:00",
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"2023-01-11 05:15:00+01:00",
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"2023-01-11 05:30:00+01:00",
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"2023-01-11 05:45:00+01:00",
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"2023-01-11 06:00:00+01:00",
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"2023-01-11 06:15:00+01:00",
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"2023-01-11 06:30:00+01:00",
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"2023-01-11 06:45:00+01:00",
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"2023-01-11 07:00:00+01:00",
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"2023-01-11 07:15:00+01:00",
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"2023-01-11 07:30:00+01:00",
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"2023-01-11 07:45:00+01:00",
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"2023-01-11 08:00:00+01:00",
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"2023-01-11 08:15:00+01:00",
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"2023-01-11 08:30:00+01:00",
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"2023-01-11 08:45:00+01:00",
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"2023-01-11 09:00:00+01:00",
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"2023-01-11 09:15:00+01:00",
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"2023-01-11 09:30:00+01:00",
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"2023-01-11 09:45:00+01:00",
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"2023-01-11 10:00:00+01:00",
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"2023-01-11 10:15:00+01:00",
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"2023-01-11 10:30:00+01:00",
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"2023-01-11 10:45:00+01:00",
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"2023-01-11 11:00:00+01:00",
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"2023-01-11 11:15:00+01:00",
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"2023-01-11 11:30:00+01:00",
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"2023-01-11 11:45:00+01:00",
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"2023-01-11 12:00:00+01:00",
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"2023-01-11 12:15:00+01:00",
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"2023-01-11 12:30:00+01:00",
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"2023-01-11 12:45:00+01:00",
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"2023-01-11 13:00:00+01:00",
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"2023-01-11 13:15:00+01:00",
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"2023-01-11 13:30:00+01:00",
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"2023-01-11 13:45:00+01:00",
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"2023-01-11 14:00:00+01:00",
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"2023-01-11 14:15:00+01:00",
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"2023-01-11 14:30:00+01:00",
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"2023-01-11 14:45:00+01:00",
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"2023-01-11 15:00:00+01:00",
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"2023-01-11 15:15:00+01:00",
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"2023-01-11 15:30:00+01:00",
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"2023-01-11 15:45:00+01:00",
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"2023-01-11 16:00:00+01:00",
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"2023-01-11 16:15:00+01:00",
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"2023-01-11 16:30:00+01:00",
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"2023-01-11 16:45:00+01:00",
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"2023-01-11 17:00:00+01:00",
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"2023-01-11 17:15:00+01:00",
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"2023-01-11 17:30:00+01:00",
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"2023-01-11 17:45:00+01:00",
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"2023-01-11 18:00:00+01:00",
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"2023-01-11 18:15:00+01:00",
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"2023-01-11 18:30:00+01:00",
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"2023-01-11 18:45:00+01:00",
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"2023-01-11 19:00:00+01:00",
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"2023-01-11 19:15:00+01:00",
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"2023-01-11 19:30:00+01:00",
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"2023-01-11 19:45:00+01:00",
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"2023-01-11 20:00:00+01:00",
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"2023-01-11 20:15:00+01:00",
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"2023-01-11 20:30:00+01:00",
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"2023-01-11 20:45:00+01:00",
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"2023-01-11 21:00:00+01:00",
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"2023-01-11 21:15:00+01:00",
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"2023-01-11 21:30:00+01:00",
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"2023-01-11 21:45:00+01:00",
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"2023-01-11 22:00:00+01:00",
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"2023-01-11 22:15:00+01:00",
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"2023-01-11 22:30:00+01:00",
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"2023-01-11 22:45:00+01:00",
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"2023-01-11 23:00:00+01:00",
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"2023-01-11 23:15:00+01:00",
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"2023-01-11 23:30:00+01:00",
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"2023-01-11 23:45:00+01:00",
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"2023-01-12 00:00:00+01:00",
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"2023-01-12 00:15:00+01:00",
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"2023-01-12 00:30:00+01:00",
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"2023-01-12 00:45:00+01:00",
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"2023-01-12 01:00:00+01:00",
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"2023-01-12 01:15:00+01:00",
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"2023-01-12 01:30:00+01:00",
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"2023-01-12 01:45:00+01:00",
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"2023-01-12 02:00:00+01:00",
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"2023-01-12 02:15:00+01:00",
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"2023-01-12 02:30:00+01:00",
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"2023-01-12 02:45:00+01:00",
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"2023-01-12 03:00:00+01:00",
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"2023-01-12 03:15:00+01:00",
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"2023-01-12 03:30:00+01:00",
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"2023-01-12 03:45:00+01:00",
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"2023-01-12 04:00:00+01:00",
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"2023-01-12 04:15:00+01:00",
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"2023-01-12 04:30:00+01:00",
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"2023-01-12 04:45:00+01:00",
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"2023-01-12 05:00:00+01:00",
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"2023-01-12 05:15:00+01:00",
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"2023-01-12 05:30:00+01:00",
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"2023-01-12 05:45:00+01:00",
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"2023-01-12 06:00:00+01:00",
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"2023-01-12 06:15:00+01:00",
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"2023-01-12 06:30:00+01:00",
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"2023-01-12 06:45:00+01:00",
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"2023-01-12 07:00:00+01:00",
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"2023-01-12 07:15:00+01:00",
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"2023-01-12 07:30:00+01:00",
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"2023-01-12 07:45:00+01:00",
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"2023-01-12 08:00:00+01:00",
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"2023-01-12 08:15:00+01:00",
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"2023-01-12 08:30:00+01:00",
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"2023-01-12 08:45:00+01:00",
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"2023-01-12 09:00:00+01:00",
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"2023-01-12 09:15:00+01:00",
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"2023-01-12 09:30:00+01:00",
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"2023-01-12 09:45:00+01:00",
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"2023-01-12 10:00:00+01:00",
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"2023-01-12 10:15:00+01:00",
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"2023-01-12 10:30:00+01:00",
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"2023-01-12 10:45:00+01:00",
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"2023-01-12 11:00:00+01:00",
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"2023-01-12 11:15:00+01:00",
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"2023-01-12 11:30:00+01:00",
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"2023-01-12 11:45:00+01:00",
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"2023-01-12 12:00:00+01:00",
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"2023-01-12 12:15:00+01:00",
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"2023-01-12 12:30:00+01:00",
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"2023-01-12 12:45:00+01:00",
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"2023-01-12 13:00:00+01:00",
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"2023-01-12 13:15:00+01:00",
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"2023-01-12 13:30:00+01:00",
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"2023-01-12 13:45:00+01:00",
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"2023-01-12 14:00:00+01:00",
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"2023-01-12 14:15:00+01:00",
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"2023-01-12 14:30:00+01:00",
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"2023-01-12 14:45:00+01:00",
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"2023-01-12 15:00:00+01:00",
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"2023-01-12 15:15:00+01:00",
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"2023-01-12 15:30:00+01:00",
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"2023-01-12 15:45:00+01:00",
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"2023-01-12 16:00:00+01:00",
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"2023-01-12 16:15:00+01:00",
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"2023-01-12 16:30:00+01:00",
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"2023-01-12 16:45:00+01:00",
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"2023-01-12 17:00:00+01:00",
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"2023-01-12 17:15:00+01:00",
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"2023-01-12 17:30:00+01:00",
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"2023-01-12 17:45:00+01:00",
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"2023-01-12 18:00:00+01:00",
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"2023-01-12 18:15:00+01:00",
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"2023-01-12 18:30:00+01:00",
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"2023-01-12 18:45:00+01:00",
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"2023-01-12 19:00:00+01:00",
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"2023-01-12 19:15:00+01:00",
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"2023-01-12 19:30:00+01:00",
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"2023-01-12 19:45:00+01:00",
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"2023-01-12 20:00:00+01:00",
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"2023-01-12 20:15:00+01:00",
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"2023-01-12 20:30:00+01:00",
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"2023-01-12 20:45:00+01:00",
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"2023-01-12 21:00:00+01:00",
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"2023-01-12 21:15:00+01:00",
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"2023-01-12 21:30:00+01:00",
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"2023-01-12 21:45:00+01:00",
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"2023-01-12 22:00:00+01:00",
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"2023-01-12 22:15:00+01:00",
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"2023-01-12 22:30:00+01:00",
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"2023-01-12 22:45:00+01:00",
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"2023-01-12 23:00:00+01:00",
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"2023-01-12 23:15:00+01:00",
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"2023-01-12 23:30:00+01:00",
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"2023-01-12 23:45:00+01:00",
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"2023-01-13 00:00:00+01:00",
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"2023-01-13 00:15:00+01:00",
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"2023-01-13 00:30:00+01:00",
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"2023-01-13 00:45:00+01:00",
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"2023-01-13 01:00:00+01:00",
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"2023-01-13 01:15:00+01:00",
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"2023-01-13 01:30:00+01:00",
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"2023-01-13 01:45:00+01:00",
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"2023-01-13 02:00:00+01:00",
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"2023-01-13 02:15:00+01:00",
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"2023-01-13 02:30:00+01:00",
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"2023-01-13 02:45:00+01:00",
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"2023-01-13 03:00:00+01:00",
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"2023-01-13 03:15:00+01:00",
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"2023-01-13 03:30:00+01:00",
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"2023-01-13 03:45:00+01:00",
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"2023-01-13 04:00:00+01:00",
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"2023-01-13 04:15:00+01:00",
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"2023-01-13 04:30:00+01:00",
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"2023-01-13 04:45:00+01:00",
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"2023-01-13 05:00:00+01:00",
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"2023-01-13 05:15:00+01:00",
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"2023-01-13 05:30:00+01:00",
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"2023-01-13 05:45:00+01:00",
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"2023-01-13 06:00:00+01:00",
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"2023-01-13 06:15:00+01:00",
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"2023-01-13 06:30:00+01:00",
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"2023-01-13 06:45:00+01:00",
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"2023-01-13 07:00:00+01:00",
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"2023-01-13 07:15:00+01:00",
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"2023-01-13 07:30:00+01:00",
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"2023-01-13 07:45:00+01:00",
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"2023-01-13 08:00:00+01:00",
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"2023-01-13 08:15:00+01:00",
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"2023-01-13 08:30:00+01:00",
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"2023-01-13 08:45:00+01:00",
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"2023-01-13 09:00:00+01:00",
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"2023-01-13 09:15:00+01:00",
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"2023-01-13 09:30:00+01:00",
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"2023-01-13 09:45:00+01:00",
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"2023-01-13 10:00:00+01:00",
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"2023-01-13 10:15:00+01:00",
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"2023-01-13 10:30:00+01:00",
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"2023-01-13 10:45:00+01:00",
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"2023-01-13 11:00:00+01:00",
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"2023-01-13 11:15:00+01:00",
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"2023-01-13 11:30:00+01:00",
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"2023-01-13 11:45:00+01:00",
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"2023-01-13 12:00:00+01:00",
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"2023-01-13 12:15:00+01:00",
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"2023-01-13 12:30:00+01:00",
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"2023-01-13 12:45:00+01:00",
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"2023-01-13 13:00:00+01:00",
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"2023-01-13 13:15:00+01:00",
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"2023-01-13 13:30:00+01:00",
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"2023-01-13 13:45:00+01:00",
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"2023-01-13 14:00:00+01:00",
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"2023-01-13 14:15:00+01:00",
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"2023-01-13 14:30:00+01:00",
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"2023-01-13 14:45:00+01:00",
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"2023-01-13 15:00:00+01:00",
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"2023-01-13 15:15:00+01:00",
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"2023-01-13 15:30:00+01:00",
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"2023-01-13 15:45:00+01:00",
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"2023-01-13 16:00:00+01:00",
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"2023-01-13 16:15:00+01:00",
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"2023-01-13 16:30:00+01:00",
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"2023-01-13 16:45:00+01:00",
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"2023-01-13 17:00:00+01:00",
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"2023-01-13 17:15:00+01:00",
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"2023-01-13 17:30:00+01:00",
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"2023-01-13 17:45:00+01:00",
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"2023-01-13 18:00:00+01:00",
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"2023-01-13 18:15:00+01:00",
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"2023-01-13 18:30:00+01:00",
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"2023-01-13 18:45:00+01:00",
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"2023-01-13 19:00:00+01:00",
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"2023-01-13 19:15:00+01:00",
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"2023-01-13 19:30:00+01:00",
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"2023-01-13 19:45:00+01:00",
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"2023-01-13 20:00:00+01:00",
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"2023-01-13 20:15:00+01:00",
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"2023-01-13 20:30:00+01:00",
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"2023-01-13 20:45:00+01:00",
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"2023-01-13 21:00:00+01:00",
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"2023-01-13 21:15:00+01:00",
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"2023-01-13 21:30:00+01:00",
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"2023-01-13 21:45:00+01:00",
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"2023-01-13 22:00:00+01:00",
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"2023-01-13 22:15:00+01:00",
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"2023-01-13 22:30:00+01:00",
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"2023-01-13 22:45:00+01:00",
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"2023-01-13 23:00:00+01:00",
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"2023-01-13 23:15:00+01:00",
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"2023-01-13 23:30:00+01:00",
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"2023-01-13 23:45:00+01:00",
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"2023-01-14 00:00:00+01:00",
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"2023-01-14 00:15:00+01:00",
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"2023-01-14 00:30:00+01:00",
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"2023-01-14 00:45:00+01:00",
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"2023-01-14 01:00:00+01:00",
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"2023-01-14 01:15:00+01:00",
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"2023-01-14 01:30:00+01:00",
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"2023-01-14 01:45:00+01:00",
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"2023-01-14 02:00:00+01:00",
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"2023-01-14 02:15:00+01:00",
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"2023-01-14 02:30:00+01:00",
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"2023-01-14 02:45:00+01:00",
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"2023-01-14 03:00:00+01:00",
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"2023-01-14 03:15:00+01:00",
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"2023-01-14 03:30:00+01:00",
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"2023-01-14 03:45:00+01:00",
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"2023-01-14 04:00:00+01:00",
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"2023-01-14 04:15:00+01:00",
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"2023-01-14 04:30:00+01:00",
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"2023-01-14 04:45:00+01:00",
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"2023-01-14 05:00:00+01:00",
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"2023-01-14 05:15:00+01:00",
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"2023-01-14 05:30:00+01:00",
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"2023-01-14 05:45:00+01:00",
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"2023-01-14 06:00:00+01:00",
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"2023-01-14 06:15:00+01:00",
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"2023-01-14 06:30:00+01:00",
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"2023-01-14 06:45:00+01:00",
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"2023-01-14 07:00:00+01:00",
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"2023-01-14 07:15:00+01:00",
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"2023-01-14 07:30:00+01:00",
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"2023-01-14 07:45:00+01:00",
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"2023-01-14 08:00:00+01:00",
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"2023-01-14 08:15:00+01:00",
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"2023-01-14 08:30:00+01:00",
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"2023-01-14 08:45:00+01:00",
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"2023-01-14 09:00:00+01:00",
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"2023-01-14 09:15:00+01:00",
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"2023-01-14 09:30:00+01:00",
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"2023-01-14 09:45:00+01:00",
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"2023-01-14 10:00:00+01:00",
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"2023-01-14 10:15:00+01:00",
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"2023-01-14 10:30:00+01:00",
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"2023-01-14 10:45:00+01:00",
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"2023-01-14 11:00:00+01:00",
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"2023-01-14 11:15:00+01:00",
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"2023-01-14 11:30:00+01:00",
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"2023-01-14 11:45:00+01:00",
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"2023-01-14 12:00:00+01:00",
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"2023-01-14 12:15:00+01:00",
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"2023-01-14 12:30:00+01:00",
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"2023-01-14 12:45:00+01:00",
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"2023-01-14 13:00:00+01:00",
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"2023-01-14 13:15:00+01:00",
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"2023-01-14 13:30:00+01:00",
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"2023-01-14 13:45:00+01:00",
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"2023-01-14 14:00:00+01:00",
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"2023-01-14 14:15:00+01:00",
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"2023-01-14 14:30:00+01:00",
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"2023-01-14 14:45:00+01:00",
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"2023-01-14 15:00:00+01:00",
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"2023-01-14 15:15:00+01:00",
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"2023-01-14 15:30:00+01:00",
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"2023-01-14 15:45:00+01:00",
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"2023-01-14 16:00:00+01:00",
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"2023-01-14 16:15:00+01:00",
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"2023-01-14 16:30:00+01:00",
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"2023-01-14 16:45:00+01:00",
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"2023-01-14 17:00:00+01:00",
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"2023-01-14 17:15:00+01:00",
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"2023-01-14 17:30:00+01:00",
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"2023-01-14 17:45:00+01:00",
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"2023-01-14 18:00:00+01:00",
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"2023-01-14 18:15:00+01:00",
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"2023-01-14 18:30:00+01:00",
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"2023-01-14 18:45:00+01:00",
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"2023-01-14 19:00:00+01:00",
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"2023-01-14 19:15:00+01:00",
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"2023-01-14 19:30:00+01:00",
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"2023-01-14 19:45:00+01:00",
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"2023-01-14 20:00:00+01:00",
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"2023-01-14 20:15:00+01:00",
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"2023-01-14 20:30:00+01:00",
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"2023-01-14 20:45:00+01:00",
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"2023-01-14 21:00:00+01:00",
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"2023-01-14 21:15:00+01:00",
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"2023-01-14 21:30:00+01:00",
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"2023-01-14 21:45:00+01:00",
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"2023-01-14 22:00:00+01:00",
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"2023-01-14 22:15:00+01:00",
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"2023-01-14 22:30:00+01:00",
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"2023-01-14 22:45:00+01:00",
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"2023-01-14 23:00:00+01:00",
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"2023-01-14 23:15:00+01:00",
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"2023-01-14 23:30:00+01:00",
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"2023-01-14 23:45:00+01:00",
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"2023-01-15 00:00:00+01:00",
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"2023-01-15 00:15:00+01:00",
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"2023-01-15 00:30:00+01:00",
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"2023-01-15 00:45:00+01:00",
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"2023-01-15 01:00:00+01:00",
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"2023-01-15 01:15:00+01:00",
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"2023-01-15 01:30:00+01:00",
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"2023-01-15 01:45:00+01:00",
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"2023-01-15 02:00:00+01:00",
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"2023-01-15 02:15:00+01:00",
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"2023-01-15 02:30:00+01:00",
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"2023-01-15 02:45:00+01:00",
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"2023-01-15 03:00:00+01:00",
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"2023-01-15 03:15:00+01:00",
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"2023-01-15 03:30:00+01:00",
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"2023-01-15 03:45:00+01:00",
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"2023-01-15 04:00:00+01:00",
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"2023-01-15 04:15:00+01:00",
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"2023-01-15 04:30:00+01:00",
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"2023-01-15 04:45:00+01:00",
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"2023-01-15 05:00:00+01:00",
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"2023-01-15 05:15:00+01:00",
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"2023-01-15 05:30:00+01:00",
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"2023-01-15 05:45:00+01:00",
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"2023-01-15 06:00:00+01:00",
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"2023-01-15 06:15:00+01:00",
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"2023-01-15 06:30:00+01:00",
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"2023-01-15 06:45:00+01:00",
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"2023-01-15 07:00:00+01:00",
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"2023-01-15 07:15:00+01:00",
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"2023-01-15 07:30:00+01:00",
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"2023-01-15 07:45:00+01:00",
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"2023-01-15 08:00:00+01:00",
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"2023-01-15 08:15:00+01:00",
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"2023-01-15 08:30:00+01:00",
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"2023-01-15 08:45:00+01:00",
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"2023-01-15 09:00:00+01:00",
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"2023-01-15 09:15:00+01:00",
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"2023-01-15 09:30:00+01:00",
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"2023-01-15 09:45:00+01:00",
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"2023-01-15 10:00:00+01:00",
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"2023-01-15 10:15:00+01:00",
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"2023-01-15 10:30:00+01:00",
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"2023-01-15 10:45:00+01:00",
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"2023-01-15 11:00:00+01:00",
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"2023-01-15 11:15:00+01:00",
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"2023-01-15 11:30:00+01:00",
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"2023-01-15 11:45:00+01:00",
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"2023-01-15 12:00:00+01:00",
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"2023-01-15 12:15:00+01:00",
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"2023-01-15 12:30:00+01:00",
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"2023-01-15 12:45:00+01:00",
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"2023-01-15 13:00:00+01:00",
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"2023-01-15 13:15:00+01:00",
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"2023-01-15 13:30:00+01:00",
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"2023-01-15 13:45:00+01:00",
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"2023-01-15 14:00:00+01:00",
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"2023-01-15 14:15:00+01:00",
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"2023-01-15 14:30:00+01:00",
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"2023-01-15 14:45:00+01:00",
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"2023-01-15 15:00:00+01:00",
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"2023-01-15 15:15:00+01:00",
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"2023-01-15 15:30:00+01:00",
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"2023-01-15 15:45:00+01:00",
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"2023-01-15 16:00:00+01:00",
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"2023-01-15 16:15:00+01:00",
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"2023-01-15 16:30:00+01:00",
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"2023-01-15 16:45:00+01:00",
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"2023-01-15 17:00:00+01:00",
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"2023-01-15 17:15:00+01:00",
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"2023-01-15 17:30:00+01:00",
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"2023-01-15 17:45:00+01:00",
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"2023-01-15 18:00:00+01:00",
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"2023-01-15 18:15:00+01:00",
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"2023-01-15 18:30:00+01:00",
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"2023-01-15 18:45:00+01:00",
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"2023-01-15 19:00:00+01:00",
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"2023-01-15 19:15:00+01:00",
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"2023-01-15 19:30:00+01:00",
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"2023-01-15 19:45:00+01:00",
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"2023-01-15 20:00:00+01:00",
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"2023-01-15 20:15:00+01:00",
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"2023-01-15 20:30:00+01:00",
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"2023-01-15 20:45:00+01:00",
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"2023-01-15 21:00:00+01:00",
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"2023-01-15 21:15:00+01:00",
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"2023-01-15 21:30:00+01:00",
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"2023-01-15 21:45:00+01:00",
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"2023-01-15 22:00:00+01:00",
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"2023-01-15 22:15:00+01:00",
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"2023-01-15 22:30:00+01:00",
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"2023-01-15 22:45:00+01:00",
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"2023-01-15 23:00:00+01:00",
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"2023-01-15 23:15:00+01:00",
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"2023-01-15 23:30:00+01:00",
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"2023-01-15 23:45:00+01:00",
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"2023-01-16 00:00:00+01:00",
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"2023-01-16 00:15:00+01:00",
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"2023-01-16 00:30:00+01:00",
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"2023-01-16 00:45:00+01:00",
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"2023-01-16 01:00:00+01:00",
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"2023-01-16 01:15:00+01:00",
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"2023-01-16 01:30:00+01:00",
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"2023-01-16 01:45:00+01:00",
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"2023-01-16 02:00:00+01:00",
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"2023-01-16 02:15:00+01:00",
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"2023-01-16 02:30:00+01:00",
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"2023-01-16 02:45:00+01:00",
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"2023-01-16 03:00:00+01:00",
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"2023-01-16 03:15:00+01:00",
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"2023-01-16 03:30:00+01:00",
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"2023-01-16 03:45:00+01:00",
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"2023-01-16 04:00:00+01:00",
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"2023-01-16 04:15:00+01:00",
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"2023-01-16 04:30:00+01:00",
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"2023-01-16 04:45:00+01:00",
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"2023-01-16 05:00:00+01:00",
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"2023-01-16 05:15:00+01:00",
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"2023-01-16 05:30:00+01:00",
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"2023-01-16 05:45:00+01:00",
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"2023-01-16 06:00:00+01:00",
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"2023-01-16 06:15:00+01:00",
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"2023-01-16 06:30:00+01:00",
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"2023-01-16 06:45:00+01:00",
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"2023-01-16 07:00:00+01:00",
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"2023-01-16 07:15:00+01:00",
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"2023-01-16 07:30:00+01:00",
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"2023-01-16 07:45:00+01:00",
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"2023-01-16 08:00:00+01:00",
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"2023-01-16 08:15:00+01:00",
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"2023-01-16 08:30:00+01:00",
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"2023-01-16 08:45:00+01:00",
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"2023-01-16 09:00:00+01:00",
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"2023-01-16 09:15:00+01:00",
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"2023-01-16 09:30:00+01:00",
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"2023-01-16 09:45:00+01:00",
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"2023-01-16 10:00:00+01:00",
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"2023-01-16 10:15:00+01:00",
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"2023-01-16 10:30:00+01:00",
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"2023-01-16 10:45:00+01:00",
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"2023-01-16 11:00:00+01:00",
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"2023-01-16 11:15:00+01:00",
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"2023-01-16 11:30:00+01:00",
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"2023-01-16 11:45:00+01:00",
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"2023-01-16 12:00:00+01:00",
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"2023-01-16 12:15:00+01:00",
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"2023-01-16 12:30:00+01:00",
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"2023-01-16 12:45:00+01:00",
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"2023-01-16 13:00:00+01:00",
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"2023-01-16 13:15:00+01:00",
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"2023-01-16 13:30:00+01:00",
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"2023-01-16 13:45:00+01:00",
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"2023-01-16 14:00:00+01:00",
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"2023-01-16 14:15:00+01:00",
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"2023-01-16 14:30:00+01:00",
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"2023-01-16 14:45:00+01:00",
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"2023-01-16 15:00:00+01:00",
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"2023-01-16 15:15:00+01:00",
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"2023-01-16 15:30:00+01:00",
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"2023-01-16 15:45:00+01:00",
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"2023-01-16 16:00:00+01:00",
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"2023-01-16 16:15:00+01:00",
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"2023-01-16 16:30:00+01:00",
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"2023-01-16 16:45:00+01:00",
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"2023-01-16 17:00:00+01:00",
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"2023-01-16 17:15:00+01:00",
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"2023-01-16 17:30:00+01:00",
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"2023-01-16 17:45:00+01:00",
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"2023-01-16 18:00:00+01:00",
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"2023-01-16 18:15:00+01:00",
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"2023-01-16 18:30:00+01:00",
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"2023-01-16 18:45:00+01:00",
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"2023-01-16 19:00:00+01:00",
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"2023-01-16 19:15:00+01:00",
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"2023-01-16 19:30:00+01:00",
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"2023-01-16 19:45:00+01:00",
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"2023-01-16 20:00:00+01:00",
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"2023-01-16 20:15:00+01:00",
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"2023-01-16 20:30:00+01:00",
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"2023-01-16 20:45:00+01:00",
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"2023-01-16 21:00:00+01:00",
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"2023-01-16 21:15:00+01:00",
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"2023-01-16 21:30:00+01:00",
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"2023-01-16 21:45:00+01:00",
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"2023-01-16 22:00:00+01:00",
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"2023-01-16 22:15:00+01:00",
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"2023-01-16 22:30:00+01:00",
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"2023-01-16 22:45:00+01:00",
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"2023-01-16 23:00:00+01:00",
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"2023-01-16 23:15:00+01:00",
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"2023-01-16 23:30:00+01:00",
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"2023-01-16 23:45:00+01:00",
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"2023-01-17 00:00:00+01:00",
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"2023-01-17 00:15:00+01:00",
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"2023-01-17 00:30:00+01:00",
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"2023-01-17 00:45:00+01:00",
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"2023-01-17 01:00:00+01:00",
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"2023-01-17 01:15:00+01:00",
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"2023-01-17 01:30:00+01:00",
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"2023-01-17 01:45:00+01:00",
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"2023-01-17 02:00:00+01:00",
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"2023-01-17 02:15:00+01:00",
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"2023-01-17 02:30:00+01:00",
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"2023-01-17 02:45:00+01:00",
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"2023-01-17 03:00:00+01:00",
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"2023-01-17 03:15:00+01:00",
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"2023-01-17 03:30:00+01:00",
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"2023-01-17 03:45:00+01:00",
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"2023-01-17 04:00:00+01:00",
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"2023-01-17 04:15:00+01:00",
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"2023-01-17 04:30:00+01:00",
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"2023-01-17 04:45:00+01:00",
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"2023-01-17 05:00:00+01:00",
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"2023-01-17 05:15:00+01:00",
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"2023-01-17 05:30:00+01:00",
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"2023-01-17 05:45:00+01:00",
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"2023-01-17 06:00:00+01:00",
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"2023-01-17 06:15:00+01:00",
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"2023-01-17 06:30:00+01:00",
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"2023-01-17 06:45:00+01:00",
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"2023-01-17 07:00:00+01:00",
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"2023-01-17 07:15:00+01:00",
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"2023-01-17 07:30:00+01:00",
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"2023-01-17 07:45:00+01:00",
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"2023-01-17 08:00:00+01:00",
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"2023-01-17 08:15:00+01:00",
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"2023-01-17 08:30:00+01:00",
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"2023-01-17 08:45:00+01:00",
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"2023-01-17 09:00:00+01:00",
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"2023-01-17 09:15:00+01:00",
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"2023-01-17 09:30:00+01:00",
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"2023-01-17 09:45:00+01:00",
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"2023-01-17 10:00:00+01:00",
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"2023-01-17 10:15:00+01:00",
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"2023-01-17 10:30:00+01:00",
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"2023-01-17 10:45:00+01:00",
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"2023-01-17 11:00:00+01:00",
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"2023-01-17 11:15:00+01:00",
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"2023-01-17 11:30:00+01:00",
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"2023-01-17 11:45:00+01:00",
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"2023-01-17 12:00:00+01:00",
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"2023-01-17 12:15:00+01:00",
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"2023-01-17 12:30:00+01:00",
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"2023-01-17 12:45:00+01:00",
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"2023-01-17 13:00:00+01:00",
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"2023-01-17 13:15:00+01:00",
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"2023-01-17 13:30:00+01:00",
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"2023-01-17 13:45:00+01:00",
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"2023-01-17 14:00:00+01:00",
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"2023-01-17 14:15:00+01:00",
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"2023-01-17 14:30:00+01:00",
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"2023-01-17 14:45:00+01:00",
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"2023-01-17 15:00:00+01:00",
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"2023-01-17 15:15:00+01:00",
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"2023-01-17 15:30:00+01:00",
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"2023-01-17 15:45:00+01:00",
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"2023-01-17 16:00:00+01:00",
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"2023-01-17 16:15:00+01:00",
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"2023-01-17 16:30:00+01:00",
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"2023-01-17 16:45:00+01:00",
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"2023-01-17 17:00:00+01:00",
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"2023-01-17 17:15:00+01:00",
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"2023-01-17 17:30:00+01:00",
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"2023-01-17 17:45:00+01:00",
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"2023-01-17 18:00:00+01:00",
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"2023-01-17 18:15:00+01:00",
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"2023-01-17 18:30:00+01:00",
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"2023-01-17 18:45:00+01:00",
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"2023-01-17 19:00:00+01:00",
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"2023-01-17 19:15:00+01:00",
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"2023-01-17 19:30:00+01:00",
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"2023-01-17 19:45:00+01:00",
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"2023-01-17 20:00:00+01:00",
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"2023-01-17 20:15:00+01:00",
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"2023-01-17 20:30:00+01:00",
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"2023-01-17 20:45:00+01:00",
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"2023-01-17 21:00:00+01:00",
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"2023-01-17 21:15:00+01:00",
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"2023-01-17 21:30:00+01:00",
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"2023-01-17 21:45:00+01:00",
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"2023-01-17 22:00:00+01:00",
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"2023-01-17 22:15:00+01:00",
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"2023-01-17 22:30:00+01:00",
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"2023-01-17 22:45:00+01:00",
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"2023-01-17 23:00:00+01:00",
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"2023-01-17 23:15:00+01:00",
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"2023-01-17 23:30:00+01:00",
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"2023-01-17 23:45:00+01:00",
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"2023-01-18 00:00:00+01:00",
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"2023-01-18 00:15:00+01:00",
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"2023-01-18 00:30:00+01:00",
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"2023-01-18 00:45:00+01:00",
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"2023-01-18 01:00:00+01:00",
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"2023-01-18 01:15:00+01:00",
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"2023-01-18 01:30:00+01:00",
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"2023-01-18 01:45:00+01:00",
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"2023-01-18 02:00:00+01:00",
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"2023-01-18 02:15:00+01:00",
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"2023-01-18 02:30:00+01:00",
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"2023-01-18 02:45:00+01:00",
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"2023-01-18 03:00:00+01:00",
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"2023-01-18 03:15:00+01:00",
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"2023-01-18 03:30:00+01:00",
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"2023-01-18 03:45:00+01:00",
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"2023-01-18 04:00:00+01:00",
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"2023-01-18 04:15:00+01:00",
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"2023-01-18 04:30:00+01:00",
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"2023-01-18 04:45:00+01:00",
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"2023-01-18 05:00:00+01:00",
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"2023-01-18 05:15:00+01:00",
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"2023-01-18 05:30:00+01:00",
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"2023-01-18 05:45:00+01:00",
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"2023-01-18 06:00:00+01:00",
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"2023-01-18 06:15:00+01:00",
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"2023-01-18 06:30:00+01:00",
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"2023-01-18 06:45:00+01:00",
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"2023-01-18 07:15:00+01:00",
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"2023-01-18 07:30:00+01:00",
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"2023-01-18 07:45:00+01:00",
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"2023-01-18 08:00:00+01:00",
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"2023-01-18 08:15:00+01:00",
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"2023-01-18 08:30:00+01:00",
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"2023-01-18 08:45:00+01:00",
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"2023-01-18 09:00:00+01:00",
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"2023-01-18 09:15:00+01:00",
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"2023-01-18 09:30:00+01:00",
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"2023-01-18 09:45:00+01:00",
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"2023-01-18 10:15:00+01:00",
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"2023-01-18 10:30:00+01:00",
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"2023-01-18 10:45:00+01:00",
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"2023-01-18 11:00:00+01:00",
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"2023-01-18 11:15:00+01:00",
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"2023-01-18 11:30:00+01:00",
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"2023-01-18 11:45:00+01:00",
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"2023-01-18 12:00:00+01:00",
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"2023-01-18 12:15:00+01:00",
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"2023-01-18 12:30:00+01:00",
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"2023-01-18 12:45:00+01:00",
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"2023-01-18 13:00:00+01:00",
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"2023-01-18 13:15:00+01:00",
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"2023-01-18 13:30:00+01:00",
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"2023-01-18 13:45:00+01:00",
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"2023-01-18 14:00:00+01:00",
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"2023-01-18 14:15:00+01:00",
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"2023-01-18 14:30:00+01:00",
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"2023-01-18 14:45:00+01:00",
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"2023-01-18 15:00:00+01:00",
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"2023-01-18 15:15:00+01:00",
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"2023-01-18 15:30:00+01:00",
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"2023-01-18 15:45:00+01:00",
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"2023-01-18 16:00:00+01:00",
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"2023-01-18 16:15:00+01:00",
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"2023-01-18 16:30:00+01:00",
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"2023-01-18 16:45:00+01:00",
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"2023-01-18 17:00:00+01:00",
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"2023-01-18 17:15:00+01:00",
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"2023-01-18 17:30:00+01:00",
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"2023-01-18 17:45:00+01:00",
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"2023-01-18 18:00:00+01:00",
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"2023-01-18 18:15:00+01:00",
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"2023-01-18 18:30:00+01:00",
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"2023-01-18 18:45:00+01:00",
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"2023-01-18 19:00:00+01:00",
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"2023-01-18 19:15:00+01:00",
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"2023-01-18 19:30:00+01:00",
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"2023-01-18 19:45:00+01:00",
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"2023-01-18 20:00:00+01:00",
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"2023-01-18 20:15:00+01:00",
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"2023-01-18 20:30:00+01:00",
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"2023-01-18 20:45:00+01:00",
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"2023-01-18 21:00:00+01:00",
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"2023-01-18 21:15:00+01:00",
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"2023-01-18 21:30:00+01:00",
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"2023-01-18 21:45:00+01:00",
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"2023-01-18 22:00:00+01:00",
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"2023-01-18 22:15:00+01:00",
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"2023-01-18 22:30:00+01:00",
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"2023-01-18 22:45:00+01:00",
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"2023-01-18 23:00:00+01:00",
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"2023-01-18 23:15:00+01:00",
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"2023-01-18 23:30:00+01:00",
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"2023-01-18 23:45:00+01:00",
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"2023-01-19 00:00:00+01:00",
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"2023-01-19 00:15:00+01:00",
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"2023-01-19 00:30:00+01:00",
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"2023-01-19 00:45:00+01:00",
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"2023-01-19 01:00:00+01:00",
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"2023-01-19 01:15:00+01:00",
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"2023-01-19 01:30:00+01:00",
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"2023-01-19 01:45:00+01:00",
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"2023-01-19 02:00:00+01:00",
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"2023-01-19 02:15:00+01:00",
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"2023-01-19 02:30:00+01:00",
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"2023-01-19 02:45:00+01:00",
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"2023-01-19 03:00:00+01:00",
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"2023-01-19 03:15:00+01:00",
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"2023-01-19 03:30:00+01:00",
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"2023-01-19 03:45:00+01:00",
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"2023-01-19 04:00:00+01:00",
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"2023-01-19 04:15:00+01:00",
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"2023-01-19 04:30:00+01:00",
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"2023-01-19 04:45:00+01:00",
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"2023-01-19 05:00:00+01:00",
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"2023-01-19 05:15:00+01:00",
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"2023-01-19 05:30:00+01:00",
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"2023-01-19 05:45:00+01:00",
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"2023-01-19 06:00:00+01:00",
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"2023-01-19 06:15:00+01:00",
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"2023-01-19 06:30:00+01:00",
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"2023-01-19 06:45:00+01:00",
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"2023-01-19 07:00:00+01:00",
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"2023-01-19 07:15:00+01:00",
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"2023-01-19 07:30:00+01:00",
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"2023-01-19 07:45:00+01:00",
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"2023-01-19 08:00:00+01:00",
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"2023-01-19 08:15:00+01:00",
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"2023-01-19 08:30:00+01:00",
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"2023-01-19 08:45:00+01:00",
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"2023-01-19 09:00:00+01:00",
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"2023-01-19 09:15:00+01:00",
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"2023-01-19 09:30:00+01:00",
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"2023-01-19 09:45:00+01:00",
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"2023-01-19 10:00:00+01:00",
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"2023-01-19 10:15:00+01:00",
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"2023-01-19 10:30:00+01:00",
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"2023-01-19 10:45:00+01:00",
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"2023-01-19 11:00:00+01:00",
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"2023-01-19 11:15:00+01:00",
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"2023-01-19 11:30:00+01:00",
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"2023-01-19 11:45:00+01:00",
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"2023-01-19 12:00:00+01:00",
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"2023-01-19 12:15:00+01:00",
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"2023-01-19 12:30:00+01:00",
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"2023-01-19 12:45:00+01:00",
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"2023-01-19 13:00:00+01:00",
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"2023-01-19 13:15:00+01:00",
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"2023-01-19 13:30:00+01:00",
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"2023-01-19 13:45:00+01:00",
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"2023-01-19 14:00:00+01:00",
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"2023-01-19 14:15:00+01:00",
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"2023-01-19 14:30:00+01:00",
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"2023-01-19 14:45:00+01:00",
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"2023-01-19 15:00:00+01:00",
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"2023-01-19 15:15:00+01:00",
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"2023-01-19 15:30:00+01:00",
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"2023-01-19 15:45:00+01:00",
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"2023-01-19 16:00:00+01:00",
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"2023-01-19 16:15:00+01:00",
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"2023-01-19 16:30:00+01:00",
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"2023-01-19 16:45:00+01:00",
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"2023-01-19 17:00:00+01:00",
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"2023-01-19 17:15:00+01:00",
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"2023-01-19 17:30:00+01:00",
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"2023-01-19 17:45:00+01:00",
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"2023-01-19 18:00:00+01:00",
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"2023-01-19 18:15:00+01:00",
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"2023-01-19 18:30:00+01:00",
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"2023-01-19 18:45:00+01:00",
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"2023-01-19 19:00:00+01:00",
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"2023-01-19 19:15:00+01:00",
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"2023-01-19 19:30:00+01:00",
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"2023-01-19 19:45:00+01:00",
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"2023-01-19 20:00:00+01:00",
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"2023-01-19 20:15:00+01:00",
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"2023-01-19 20:30:00+01:00",
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"2023-01-19 20:45:00+01:00",
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"2023-01-19 21:00:00+01:00",
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"2023-01-19 21:15:00+01:00",
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"2023-01-19 21:30:00+01:00",
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"2023-01-19 21:45:00+01:00",
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"2023-01-19 22:00:00+01:00",
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"2023-01-19 22:15:00+01:00",
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"2023-01-19 22:30:00+01:00",
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"2023-01-19 22:45:00+01:00",
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"2023-01-19 23:00:00+01:00",
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"2023-01-19 23:15:00+01:00",
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"2023-01-19 23:30:00+01:00",
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"2023-01-19 23:45:00+01:00",
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"2023-01-20 00:00:00+01:00",
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"2023-01-20 00:15:00+01:00",
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"2023-01-20 00:30:00+01:00",
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"2023-01-20 00:45:00+01:00",
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"2023-01-20 01:00:00+01:00",
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"2023-01-20 01:15:00+01:00",
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"2023-01-20 01:30:00+01:00",
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"2023-01-20 01:45:00+01:00",
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"2023-01-20 02:00:00+01:00",
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"2023-01-20 02:15:00+01:00",
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"2023-01-20 02:30:00+01:00",
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"2023-01-20 02:45:00+01:00",
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"2023-01-20 03:00:00+01:00",
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"2023-01-20 03:15:00+01:00",
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"2023-01-20 03:30:00+01:00",
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"2023-01-20 03:45:00+01:00",
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"2023-01-20 04:00:00+01:00",
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"2023-01-20 04:15:00+01:00",
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"2023-01-20 04:30:00+01:00",
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"2023-01-20 04:45:00+01:00",
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"2023-01-20 05:00:00+01:00",
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"2023-01-20 05:15:00+01:00",
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"2023-01-20 05:30:00+01:00",
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"2023-01-20 05:45:00+01:00",
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"2023-01-20 06:00:00+01:00",
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"2023-01-20 06:15:00+01:00",
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"2023-01-20 06:30:00+01:00",
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"2023-01-20 06:45:00+01:00",
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"2023-01-20 07:00:00+01:00",
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"2023-01-20 07:15:00+01:00",
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"2023-01-20 07:30:00+01:00",
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"2023-01-20 07:45:00+01:00",
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"2023-01-20 08:00:00+01:00",
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"2023-01-20 08:15:00+01:00",
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"2023-01-20 08:30:00+01:00",
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"2023-01-20 08:45:00+01:00",
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"2023-01-20 09:00:00+01:00",
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"2023-01-20 09:15:00+01:00",
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"2023-01-20 09:30:00+01:00",
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"2023-01-20 09:45:00+01:00",
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"2023-01-20 10:00:00+01:00",
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"2023-01-20 10:15:00+01:00",
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"2023-01-20 10:30:00+01:00",
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"2023-01-20 10:45:00+01:00",
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"2023-01-20 11:00:00+01:00",
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"2023-01-20 11:15:00+01:00",
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"2023-01-20 11:30:00+01:00",
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"2023-01-20 11:45:00+01:00",
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"2023-01-20 12:00:00+01:00",
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"2023-01-20 12:15:00+01:00",
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"2023-01-20 12:30:00+01:00",
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"2023-01-20 12:45:00+01:00",
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"2023-01-20 13:00:00+01:00",
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"2023-01-20 13:15:00+01:00",
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"2023-01-20 13:30:00+01:00",
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"2023-01-20 13:45:00+01:00",
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"2023-01-20 14:00:00+01:00",
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"2023-01-20 14:15:00+01:00",
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"2023-01-20 14:30:00+01:00",
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"2023-01-20 14:45:00+01:00",
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"2023-01-20 15:00:00+01:00",
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"2023-01-20 15:15:00+01:00",
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"2023-01-20 15:30:00+01:00",
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"2023-01-20 15:45:00+01:00",
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"2023-01-20 16:00:00+01:00",
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"2023-01-20 16:15:00+01:00",
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"2023-01-20 16:30:00+01:00",
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"2023-01-20 16:45:00+01:00",
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"2023-01-20 17:00:00+01:00",
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"2023-01-20 17:15:00+01:00",
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"2023-01-20 17:30:00+01:00",
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"2023-01-20 17:45:00+01:00",
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"2023-01-20 18:00:00+01:00",
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"2023-01-20 18:15:00+01:00",
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"2023-01-20 18:30:00+01:00",
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"2023-01-20 18:45:00+01:00",
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"2023-01-20 19:00:00+01:00",
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"2023-01-20 19:15:00+01:00",
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"2023-01-20 19:30:00+01:00",
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"2023-01-20 19:45:00+01:00",
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"2023-01-20 20:00:00+01:00",
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"2023-01-20 20:15:00+01:00",
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"2023-01-20 20:30:00+01:00",
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"2023-01-20 20:45:00+01:00",
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"2023-01-20 21:00:00+01:00",
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"2023-01-20 21:15:00+01:00",
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"2023-01-20 21:30:00+01:00",
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"2023-01-20 21:45:00+01:00",
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"2023-01-20 22:00:00+01:00",
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"2023-01-20 22:15:00+01:00",
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"2023-01-20 22:30:00+01:00",
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"2023-01-20 22:45:00+01:00",
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"2023-01-20 23:00:00+01:00",
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"2023-01-20 23:15:00+01:00",
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"2023-01-20 23:30:00+01:00",
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"2023-01-20 23:45:00+01:00",
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"2023-01-21 00:00:00+01:00",
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"2023-01-21 00:15:00+01:00",
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"2023-01-21 00:30:00+01:00",
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"2023-01-21 00:45:00+01:00",
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"2023-01-21 01:00:00+01:00",
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"2023-01-21 01:15:00+01:00",
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"2023-01-21 01:30:00+01:00",
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"2023-01-21 01:45:00+01:00",
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"2023-01-21 02:00:00+01:00",
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"2023-01-21 02:15:00+01:00",
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"2023-01-21 02:30:00+01:00",
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"2023-01-21 02:45:00+01:00",
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"2023-01-21 03:00:00+01:00",
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"2023-01-21 03:15:00+01:00",
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"2023-01-21 03:30:00+01:00",
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"2023-01-21 03:45:00+01:00",
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"2023-01-21 04:00:00+01:00",
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"2023-01-21 04:15:00+01:00",
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"2023-01-21 04:30:00+01:00",
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"2023-01-21 04:45:00+01:00",
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"2023-01-21 05:00:00+01:00",
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"2023-01-21 05:15:00+01:00",
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"2023-01-21 05:30:00+01:00",
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"2023-01-21 05:45:00+01:00",
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"2023-01-21 06:00:00+01:00",
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"2023-01-21 06:15:00+01:00",
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"2023-01-21 06:30:00+01:00",
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"2023-01-21 06:45:00+01:00",
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"2023-01-21 07:15:00+01:00",
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"2023-01-21 07:30:00+01:00",
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"2023-01-21 07:45:00+01:00",
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"2023-01-21 08:15:00+01:00",
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"2023-01-21 09:15:00+01:00",
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"2023-01-21 09:30:00+01:00",
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"2023-01-21 09:45:00+01:00",
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"2023-01-21 10:15:00+01:00",
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"2023-01-21 10:30:00+01:00",
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"2023-01-21 10:45:00+01:00",
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"2023-01-21 11:00:00+01:00",
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"2023-01-21 11:15:00+01:00",
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"2023-01-21 11:30:00+01:00",
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"2023-01-21 11:45:00+01:00",
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"2023-01-21 12:15:00+01:00",
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"2023-01-21 13:15:00+01:00",
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"2023-01-21 14:15:00+01:00",
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"2023-01-21 14:30:00+01:00",
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"2023-01-21 17:15:00+01:00",
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"2023-01-21 17:45:00+01:00",
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"2023-01-21 18:15:00+01:00",
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"2023-01-21 19:15:00+01:00",
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"2023-01-21 19:30:00+01:00",
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"2023-01-21 20:15:00+01:00",
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"2023-01-21 20:45:00+01:00",
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"2023-01-21 21:15:00+01:00",
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"2023-01-21 22:15:00+01:00",
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"2023-01-21 23:15:00+01:00",
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"2023-01-22 00:15:00+01:00",
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"2023-01-22 01:00:00+01:00",
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"2023-01-22 01:15:00+01:00",
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"2023-01-22 01:30:00+01:00",
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"2023-01-22 01:45:00+01:00",
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"2023-01-22 02:00:00+01:00",
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"2023-01-22 02:15:00+01:00",
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"2023-01-22 02:30:00+01:00",
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"2023-01-22 02:45:00+01:00",
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"2023-01-22 03:00:00+01:00",
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"2023-01-22 03:15:00+01:00",
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"2023-01-22 03:30:00+01:00",
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"2023-01-22 03:45:00+01:00",
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"2023-01-22 04:15:00+01:00",
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"2023-01-22 05:15:00+01:00",
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"2023-01-22 05:30:00+01:00",
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"2023-01-22 05:45:00+01:00",
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"2023-01-22 06:15:00+01:00",
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"2023-01-22 06:30:00+01:00",
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"2023-01-22 06:45:00+01:00",
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"2023-01-22 07:15:00+01:00",
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"2023-01-22 07:30:00+01:00",
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"2023-01-22 07:45:00+01:00",
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"2023-01-22 08:15:00+01:00",
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"2023-01-22 09:00:00+01:00",
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"2023-01-22 09:15:00+01:00",
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"2023-01-22 09:30:00+01:00",
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"2023-01-22 09:45:00+01:00",
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"2023-01-22 10:15:00+01:00",
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"2023-01-22 10:30:00+01:00",
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"2023-01-22 10:45:00+01:00",
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"2023-01-22 11:00:00+01:00",
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"2023-01-22 11:15:00+01:00",
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"2023-01-22 11:30:00+01:00",
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"2023-01-22 11:45:00+01:00",
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"2023-01-22 12:00:00+01:00",
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"2023-01-22 12:15:00+01:00",
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"2023-01-22 12:30:00+01:00",
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"2023-01-22 12:45:00+01:00",
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"2023-01-22 13:00:00+01:00",
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"2023-01-22 13:15:00+01:00",
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"2023-01-22 13:30:00+01:00",
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"2023-01-22 14:15:00+01:00",
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"2023-01-22 14:30:00+01:00",
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"2023-01-22 14:45:00+01:00",
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"2023-01-22 15:15:00+01:00",
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"2023-01-22 15:30:00+01:00",
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"2023-01-22 15:45:00+01:00",
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"2023-01-22 16:15:00+01:00",
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"2023-01-22 16:30:00+01:00",
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"2023-01-22 16:45:00+01:00",
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"2023-01-22 17:00:00+01:00",
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"2023-01-22 17:15:00+01:00",
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"2023-01-22 17:30:00+01:00",
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"2023-01-22 17:45:00+01:00",
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"2023-01-22 18:00:00+01:00",
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"2023-01-22 18:15:00+01:00",
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"2023-01-22 18:30:00+01:00",
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"2023-01-22 18:45:00+01:00",
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"2023-01-22 19:00:00+01:00",
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"2023-01-22 19:15:00+01:00",
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"2023-01-22 19:30:00+01:00",
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"2023-01-22 19:45:00+01:00",
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"2023-01-22 20:00:00+01:00",
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"2023-01-22 20:15:00+01:00",
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"2023-01-22 20:30:00+01:00",
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"2023-01-22 20:45:00+01:00",
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"2023-01-22 21:00:00+01:00",
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"2023-01-22 21:15:00+01:00",
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"2023-01-22 21:30:00+01:00",
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"2023-01-22 21:45:00+01:00",
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"2023-01-22 22:00:00+01:00",
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"2023-01-22 22:15:00+01:00",
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"2023-01-22 22:30:00+01:00",
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"2023-01-22 22:45:00+01:00",
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"2023-01-22 23:00:00+01:00",
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"2023-01-22 23:15:00+01:00",
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"2023-01-22 23:30:00+01:00",
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"2023-01-22 23:45:00+01:00",
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"2023-01-23 00:00:00+01:00",
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"2023-01-23 00:15:00+01:00",
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"2023-01-23 00:30:00+01:00",
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"2023-01-23 00:45:00+01:00",
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"2023-01-23 01:00:00+01:00",
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"2023-01-23 01:15:00+01:00",
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"2023-01-23 01:30:00+01:00",
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"2023-01-23 01:45:00+01:00",
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"2023-01-23 02:00:00+01:00",
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"2023-01-23 02:15:00+01:00",
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"2023-01-23 02:30:00+01:00",
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"2023-01-23 02:45:00+01:00",
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"2023-01-23 03:00:00+01:00",
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"2023-01-23 03:15:00+01:00",
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"2023-01-23 03:30:00+01:00",
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"2023-01-23 03:45:00+01:00",
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"2023-01-23 04:00:00+01:00",
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"2023-01-23 04:15:00+01:00",
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"2023-01-23 04:30:00+01:00",
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"2023-01-23 04:45:00+01:00",
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"2023-01-23 05:00:00+01:00",
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"2023-01-23 05:15:00+01:00",
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"2023-01-23 05:30:00+01:00",
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"2023-01-23 05:45:00+01:00",
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"2023-01-23 06:00:00+01:00",
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"2023-01-23 06:15:00+01:00",
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"2023-01-23 06:30:00+01:00",
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"2023-01-23 06:45:00+01:00",
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"2023-01-23 07:00:00+01:00",
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"2023-01-23 07:15:00+01:00",
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"2023-01-23 07:30:00+01:00",
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"2023-01-23 07:45:00+01:00",
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"2023-01-23 08:00:00+01:00",
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"2023-01-23 08:15:00+01:00",
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"2023-01-23 08:30:00+01:00",
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"2023-01-23 08:45:00+01:00",
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"2023-01-23 09:00:00+01:00",
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"2023-01-23 09:15:00+01:00",
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"2023-01-23 09:30:00+01:00",
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"2023-01-23 09:45:00+01:00",
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"2023-01-23 10:00:00+01:00",
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"2023-01-23 10:15:00+01:00",
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"2023-01-23 10:30:00+01:00",
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"2023-01-23 10:45:00+01:00",
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"2023-01-23 11:00:00+01:00",
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"2023-01-23 11:15:00+01:00",
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"2023-01-23 11:30:00+01:00",
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"2023-01-23 11:45:00+01:00",
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"2023-01-23 12:00:00+01:00",
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"2023-01-23 12:15:00+01:00",
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"2023-01-23 12:30:00+01:00",
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"2023-01-23 12:45:00+01:00",
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"2023-01-23 13:00:00+01:00",
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"2023-01-23 13:15:00+01:00",
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"2023-01-23 13:30:00+01:00",
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"2023-01-23 13:45:00+01:00",
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"2023-01-23 14:00:00+01:00",
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"2023-01-23 14:15:00+01:00",
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"2023-01-23 14:30:00+01:00",
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"2023-01-23 14:45:00+01:00",
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"2023-01-23 15:00:00+01:00",
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"2023-01-23 15:15:00+01:00",
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"2023-01-23 15:30:00+01:00",
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"2023-01-23 15:45:00+01:00",
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"2023-01-23 16:00:00+01:00",
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"2023-01-23 16:15:00+01:00",
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"2023-01-23 16:30:00+01:00",
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"2023-01-23 16:45:00+01:00",
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"2023-01-23 17:00:00+01:00",
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"2023-01-23 17:15:00+01:00",
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"2023-01-23 17:30:00+01:00",
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"2023-01-23 17:45:00+01:00",
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"2023-01-23 18:00:00+01:00",
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"2023-01-23 18:15:00+01:00",
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"2023-01-23 18:30:00+01:00",
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"2023-01-23 18:45:00+01:00",
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"2023-01-23 19:00:00+01:00",
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"2023-01-23 19:15:00+01:00",
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"2023-01-23 19:30:00+01:00",
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"2023-01-23 19:45:00+01:00",
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"2023-01-23 20:00:00+01:00",
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"2023-01-23 20:15:00+01:00",
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"2023-01-23 20:30:00+01:00",
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"2023-01-23 20:45:00+01:00",
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"2023-01-23 21:00:00+01:00",
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"2023-01-23 21:15:00+01:00",
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"2023-01-23 21:30:00+01:00",
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"2023-01-23 21:45:00+01:00",
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"2023-01-23 22:00:00+01:00",
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"2023-01-23 22:15:00+01:00",
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"2023-01-23 22:30:00+01:00",
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"2023-01-23 22:45:00+01:00",
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"2023-01-23 23:00:00+01:00",
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"2023-01-23 23:15:00+01:00",
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"2023-01-23 23:30:00+01:00",
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"2023-01-23 23:45:00+01:00",
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"2023-01-24 00:00:00+01:00",
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"2023-01-24 00:15:00+01:00",
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"2023-01-24 00:30:00+01:00",
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"2023-01-24 00:45:00+01:00",
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"2023-01-24 01:00:00+01:00",
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"2023-01-24 01:15:00+01:00",
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"2023-01-24 01:30:00+01:00",
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"2023-01-24 01:45:00+01:00",
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"2023-01-24 02:00:00+01:00",
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"2023-01-24 02:15:00+01:00",
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"2023-01-24 02:30:00+01:00",
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"2023-01-24 02:45:00+01:00",
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"2023-01-24 03:00:00+01:00",
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"2023-01-24 03:15:00+01:00",
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"2023-01-24 03:30:00+01:00",
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"2023-01-24 03:45:00+01:00",
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"2023-01-24 04:00:00+01:00",
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"2023-01-24 04:15:00+01:00",
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"2023-01-24 04:30:00+01:00",
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"2023-01-24 04:45:00+01:00",
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"2023-01-24 05:00:00+01:00",
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"2023-01-24 05:15:00+01:00",
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"2023-01-24 05:30:00+01:00",
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"2023-01-24 05:45:00+01:00",
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"2023-01-24 06:00:00+01:00",
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"2023-01-24 06:15:00+01:00",
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"2023-01-24 06:30:00+01:00",
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"2023-01-24 06:45:00+01:00",
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"2023-01-24 07:00:00+01:00",
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"2023-01-24 07:15:00+01:00",
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"2023-01-24 07:30:00+01:00",
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"2023-01-24 07:45:00+01:00",
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"2023-01-24 08:00:00+01:00",
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"2023-01-24 08:15:00+01:00",
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"2023-01-24 08:30:00+01:00",
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"2023-01-24 08:45:00+01:00",
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"2023-01-24 09:00:00+01:00",
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"2023-01-24 09:15:00+01:00",
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"2023-01-24 09:30:00+01:00",
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"2023-01-24 09:45:00+01:00",
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"2023-01-24 10:00:00+01:00",
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"2023-01-24 10:15:00+01:00",
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"2023-01-24 10:30:00+01:00",
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"2023-01-24 10:45:00+01:00",
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"2023-01-24 11:00:00+01:00",
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"2023-01-24 11:15:00+01:00",
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"2023-01-24 11:30:00+01:00",
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"2023-01-24 11:45:00+01:00",
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"2023-01-24 12:00:00+01:00",
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"2023-01-24 12:15:00+01:00",
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"2023-01-24 12:30:00+01:00",
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"2023-01-24 12:45:00+01:00",
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"2023-01-24 13:00:00+01:00",
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"2023-01-24 13:15:00+01:00",
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"2023-01-24 13:30:00+01:00",
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"2023-01-24 13:45:00+01:00",
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"2023-01-24 14:00:00+01:00",
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"2023-01-24 14:15:00+01:00",
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"2023-01-24 14:30:00+01:00",
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"2023-01-28 00:30:00+01:00",
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"2023-01-28 00:45:00+01:00",
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"2023-01-28 01:00:00+01:00",
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"2023-01-28 01:15:00+01:00",
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"2023-01-28 01:30:00+01:00",
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"2023-01-28 01:45:00+01:00",
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"2023-01-28 02:00:00+01:00",
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"2023-01-28 02:15:00+01:00",
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"2023-01-28 02:30:00+01:00",
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"2023-01-28 02:45:00+01:00",
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"2023-01-28 03:15:00+01:00",
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"2023-01-28 03:30:00+01:00",
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"2023-01-28 03:45:00+01:00",
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"2023-01-28 04:00:00+01:00",
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"2023-01-28 04:15:00+01:00",
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"2023-01-28 04:30:00+01:00",
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"2023-01-28 04:45:00+01:00",
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"2023-01-28 05:00:00+01:00",
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"2023-01-28 05:15:00+01:00",
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"2023-01-28 05:30:00+01:00",
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"2023-01-28 05:45:00+01:00",
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"2023-01-28 06:00:00+01:00",
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"2023-01-28 06:15:00+01:00",
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"2023-01-28 06:30:00+01:00",
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"2023-01-28 06:45:00+01:00",
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"2023-01-28 07:15:00+01:00",
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"2023-01-28 07:45:00+01:00",
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"2023-01-28 08:15:00+01:00",
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"2023-01-28 08:30:00+01:00",
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"2023-01-28 08:45:00+01:00",
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"2023-01-28 09:15:00+01:00",
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"2023-01-28 09:30:00+01:00",
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"2023-01-28 09:45:00+01:00",
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"2023-01-28 10:15:00+01:00",
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"2023-01-28 10:30:00+01:00",
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"2023-01-28 10:45:00+01:00",
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"2023-01-28 11:00:00+01:00",
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"2023-01-28 11:15:00+01:00",
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"2023-01-28 11:30:00+01:00",
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"2023-01-28 11:45:00+01:00",
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"2023-01-28 12:00:00+01:00",
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"2023-01-28 12:15:00+01:00",
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"2023-01-28 12:30:00+01:00",
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"2023-01-28 12:45:00+01:00",
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"2023-01-28 13:15:00+01:00",
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"2023-01-28 13:30:00+01:00",
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"2023-01-28 13:45:00+01:00",
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"2023-01-28 14:15:00+01:00",
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"2023-01-28 14:30:00+01:00",
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"2023-01-28 14:45:00+01:00",
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"2023-01-28 15:15:00+01:00",
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"2023-01-28 15:30:00+01:00",
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"2023-01-28 15:45:00+01:00",
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"2023-01-28 17:15:00+01:00",
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"2023-01-28 17:30:00+01:00",
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"2023-01-28 17:45:00+01:00",
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"2023-01-28 18:15:00+01:00",
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"2023-01-28 18:30:00+01:00",
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"2023-01-28 18:45:00+01:00",
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"2023-01-28 19:15:00+01:00",
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"2023-01-28 19:30:00+01:00",
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"2023-01-28 19:45:00+01:00",
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"2023-01-28 20:00:00+01:00",
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"2023-01-28 20:15:00+01:00",
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"2023-01-28 20:30:00+01:00",
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"2023-01-28 20:45:00+01:00",
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"2023-01-28 21:15:00+01:00",
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"2023-01-28 21:30:00+01:00",
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"2023-01-28 21:45:00+01:00",
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"2023-01-28 22:15:00+01:00",
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"2023-01-28 23:15:00+01:00",
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"2023-01-28 23:30:00+01:00",
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"2023-01-29 00:00:00+01:00",
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"2023-01-29 00:15:00+01:00",
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"2023-01-29 00:30:00+01:00",
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"2023-01-29 00:45:00+01:00",
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"2023-01-29 01:00:00+01:00",
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"2023-01-29 01:15:00+01:00",
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"2023-01-29 01:30:00+01:00",
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"2023-01-29 01:45:00+01:00",
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"2023-01-29 02:00:00+01:00",
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"2023-01-29 02:15:00+01:00",
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"2023-01-29 02:30:00+01:00",
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"2023-01-29 02:45:00+01:00",
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"2023-01-29 03:00:00+01:00",
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"2023-01-29 03:15:00+01:00",
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"2023-01-29 03:30:00+01:00",
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"2023-01-29 03:45:00+01:00",
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"2023-01-29 04:00:00+01:00",
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"2023-01-29 04:15:00+01:00",
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"2023-01-29 04:30:00+01:00",
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"2023-01-29 04:45:00+01:00",
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"2023-01-29 05:00:00+01:00",
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"2023-01-29 05:15:00+01:00",
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"2023-01-29 05:30:00+01:00",
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"2023-01-29 05:45:00+01:00",
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"2023-01-29 06:00:00+01:00",
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"2023-01-29 06:15:00+01:00",
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"2023-01-29 06:30:00+01:00",
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"2023-01-29 06:45:00+01:00",
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"2023-01-29 07:00:00+01:00",
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"2023-01-29 07:15:00+01:00",
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"2023-01-29 07:30:00+01:00",
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"2023-01-29 07:45:00+01:00",
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"2023-01-29 08:00:00+01:00",
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"2023-01-29 08:15:00+01:00",
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"2023-01-29 08:30:00+01:00",
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"2023-01-29 08:45:00+01:00",
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"2023-01-29 09:15:00+01:00",
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"2023-01-29 09:30:00+01:00",
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"2023-01-29 09:45:00+01:00",
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"2023-01-29 10:00:00+01:00",
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"2023-01-29 10:15:00+01:00",
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"2023-01-29 10:30:00+01:00",
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"2023-01-29 10:45:00+01:00",
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"2023-01-29 11:00:00+01:00",
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"2023-01-29 11:15:00+01:00",
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"2023-01-29 11:30:00+01:00",
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"2023-01-29 11:45:00+01:00",
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"2023-01-29 12:00:00+01:00",
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"2023-01-29 12:15:00+01:00",
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"2023-01-29 12:30:00+01:00",
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"2023-01-29 12:45:00+01:00",
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"2023-01-29 13:00:00+01:00",
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"2023-01-29 13:15:00+01:00",
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"2023-01-29 13:30:00+01:00",
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"2023-01-29 13:45:00+01:00",
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"2023-01-29 14:00:00+01:00",
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"2023-01-29 14:15:00+01:00",
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"2023-01-29 14:30:00+01:00",
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"2023-01-29 14:45:00+01:00",
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"2023-01-29 15:00:00+01:00",
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"2023-01-29 15:15:00+01:00",
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"2023-01-29 15:30:00+01:00",
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"2023-01-29 15:45:00+01:00",
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"2023-01-29 16:00:00+01:00",
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"2023-01-29 16:15:00+01:00",
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"2023-01-29 16:30:00+01:00",
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"2023-01-29 16:45:00+01:00",
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"2023-01-29 17:00:00+01:00",
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"2023-01-29 17:15:00+01:00",
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"2023-01-29 17:30:00+01:00",
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"2023-01-29 17:45:00+01:00",
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"2023-01-29 18:00:00+01:00",
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"2023-01-29 18:15:00+01:00",
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"2023-01-29 18:30:00+01:00",
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"2023-01-29 18:45:00+01:00",
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"2023-01-29 19:00:00+01:00",
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"2023-01-29 19:15:00+01:00",
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"2023-01-29 19:30:00+01:00",
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"2023-01-29 19:45:00+01:00",
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"2023-01-29 20:00:00+01:00",
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"2023-01-29 20:15:00+01:00",
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"2023-01-29 20:30:00+01:00",
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"2023-01-29 20:45:00+01:00",
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"2023-01-29 21:00:00+01:00",
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"2023-01-29 21:15:00+01:00",
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"2023-01-29 21:30:00+01:00",
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"2023-01-29 21:45:00+01:00",
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"2023-01-29 22:00:00+01:00",
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"2023-01-29 22:15:00+01:00",
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"2023-01-29 22:30:00+01:00",
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"2023-01-29 22:45:00+01:00",
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"2023-01-29 23:00:00+01:00",
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"2023-01-29 23:15:00+01:00",
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"2023-01-29 23:30:00+01:00",
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"2023-01-29 23:45:00+01:00",
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"2023-01-30 00:00:00+01:00",
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"2023-01-30 00:15:00+01:00",
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"2023-01-30 00:30:00+01:00",
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"2023-01-30 00:45:00+01:00",
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"2023-01-30 01:00:00+01:00",
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"2023-01-30 01:15:00+01:00",
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"2023-01-30 01:30:00+01:00",
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"2023-01-30 01:45:00+01:00",
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"2023-01-30 02:00:00+01:00",
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"2023-01-30 02:15:00+01:00",
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"2023-01-30 02:30:00+01:00",
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"2023-01-30 02:45:00+01:00",
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"2023-01-30 03:00:00+01:00",
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"2023-01-30 03:15:00+01:00",
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"2023-01-30 03:30:00+01:00",
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"2023-01-30 03:45:00+01:00",
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"2023-01-30 04:00:00+01:00",
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"2023-01-30 04:15:00+01:00",
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"2023-01-30 04:30:00+01:00",
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"2023-01-30 04:45:00+01:00",
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"2023-01-30 05:00:00+01:00",
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"2023-01-30 05:15:00+01:00",
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"2023-01-30 05:30:00+01:00",
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"2023-01-30 05:45:00+01:00",
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"2023-01-30 06:00:00+01:00",
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"2023-01-30 06:15:00+01:00",
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"2023-01-30 06:30:00+01:00",
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"2023-01-30 06:45:00+01:00",
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"2023-01-30 07:00:00+01:00",
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"2023-01-30 07:15:00+01:00",
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"2023-01-30 07:30:00+01:00",
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"2023-01-30 07:45:00+01:00",
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"2023-01-30 08:00:00+01:00",
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"2023-01-30 08:15:00+01:00",
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"2023-01-30 08:30:00+01:00",
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"2023-01-30 08:45:00+01:00",
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"2023-01-30 09:00:00+01:00",
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"2023-01-30 09:15:00+01:00",
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"2023-01-30 09:30:00+01:00",
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"2023-01-30 09:45:00+01:00",
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"2023-01-30 10:00:00+01:00",
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"2023-01-30 10:15:00+01:00",
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"2023-01-30 10:30:00+01:00",
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"2023-01-30 10:45:00+01:00",
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"2023-01-30 11:00:00+01:00",
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"2023-01-30 11:15:00+01:00",
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"2023-01-30 11:30:00+01:00",
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"2023-01-30 11:45:00+01:00",
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"2023-01-30 12:00:00+01:00",
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"2023-01-30 12:15:00+01:00",
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"2023-01-30 12:30:00+01:00",
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"2023-01-30 12:45:00+01:00",
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"2023-01-30 13:00:00+01:00",
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"2023-01-30 13:15:00+01:00",
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"2023-01-30 13:30:00+01:00",
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"2023-01-30 13:45:00+01:00",
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"2023-01-30 14:00:00+01:00",
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"2023-01-30 14:15:00+01:00",
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"2023-01-30 14:30:00+01:00",
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"2023-01-30 14:45:00+01:00",
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"2023-01-30 15:00:00+01:00",
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"2023-01-30 15:15:00+01:00",
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"2023-01-30 15:30:00+01:00",
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"2023-01-30 15:45:00+01:00",
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"2023-01-30 16:00:00+01:00",
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"2023-01-30 16:15:00+01:00",
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"2023-01-30 16:30:00+01:00",
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"2023-01-30 16:45:00+01:00",
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"2023-01-30 17:00:00+01:00",
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"2023-01-30 17:15:00+01:00",
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"2023-01-30 17:30:00+01:00",
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"2023-01-30 17:45:00+01:00",
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"2023-01-30 18:00:00+01:00",
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"2023-01-30 18:15:00+01:00",
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"2023-01-30 18:30:00+01:00",
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"2023-01-30 18:45:00+01:00",
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"2023-01-30 19:00:00+01:00",
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"2023-01-30 19:15:00+01:00",
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"2023-01-30 19:30:00+01:00",
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"2023-01-30 19:45:00+01:00",
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"2023-01-30 20:00:00+01:00",
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"2023-01-30 20:15:00+01:00",
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"2023-01-30 20:30:00+01:00",
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"2023-01-30 20:45:00+01:00",
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"2023-01-30 21:00:00+01:00",
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"2023-01-30 21:15:00+01:00",
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"2023-01-30 21:30:00+01:00",
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"2023-01-30 21:45:00+01:00",
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"2023-01-30 22:00:00+01:00",
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"2023-01-30 22:15:00+01:00",
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"2023-01-30 22:30:00+01:00",
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"2023-01-30 22:45:00+01:00",
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"2023-01-30 23:00:00+01:00",
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"2023-01-30 23:15:00+01:00",
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"2023-01-30 23:30:00+01:00",
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"2023-01-30 23:45:00+01:00",
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"2023-01-31 00:00:00+01:00",
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"2023-01-31 00:15:00+01:00",
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"2023-01-31 00:30:00+01:00",
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"2023-01-31 00:45:00+01:00",
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"2023-01-31 01:00:00+01:00",
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"2023-01-31 01:15:00+01:00",
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"2023-01-31 01:30:00+01:00",
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"2023-01-31 01:45:00+01:00",
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"2023-01-31 02:00:00+01:00",
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"2023-01-31 02:15:00+01:00",
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"2023-01-31 02:30:00+01:00",
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"2023-01-31 02:45:00+01:00",
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"2023-01-31 03:00:00+01:00",
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"2023-01-31 03:15:00+01:00",
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"2023-01-31 03:30:00+01:00",
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"2023-01-31 03:45:00+01:00",
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"2023-01-31 04:00:00+01:00",
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"2023-01-31 04:15:00+01:00",
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"2023-01-31 04:30:00+01:00",
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"2023-01-31 04:45:00+01:00",
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"2023-01-31 05:00:00+01:00",
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"2023-01-31 05:15:00+01:00",
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"2023-01-31 05:30:00+01:00",
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"2023-01-31 05:45:00+01:00",
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"2023-01-31 06:00:00+01:00",
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"2023-01-31 06:15:00+01:00",
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"2023-01-31 06:30:00+01:00",
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"2023-01-31 06:45:00+01:00",
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"2023-01-31 07:00:00+01:00",
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"2023-01-31 07:15:00+01:00",
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"2023-01-31 07:30:00+01:00",
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"2023-01-31 07:45:00+01:00",
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"2023-01-31 08:00:00+01:00",
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"2023-01-31 08:15:00+01:00",
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"2023-01-31 08:30:00+01:00",
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"2023-01-31 08:45:00+01:00",
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"2023-01-31 09:00:00+01:00",
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"2023-01-31 09:15:00+01:00",
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"2023-01-31 09:30:00+01:00",
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"2023-01-31 09:45:00+01:00",
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"2023-01-31 10:00:00+01:00",
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"2023-01-31 10:15:00+01:00",
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"2023-01-31 10:30:00+01:00",
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"2023-01-31 10:45:00+01:00",
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"2023-01-31 11:00:00+01:00",
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"2023-01-31 11:15:00+01:00",
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"2023-01-31 11:30:00+01:00",
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"2023-01-31 11:45:00+01:00",
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"2023-01-31 12:00:00+01:00",
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"2023-01-31 12:15:00+01:00",
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"2023-01-31 12:30:00+01:00",
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"2023-01-31 12:45:00+01:00",
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"2023-01-31 13:00:00+01:00",
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"2023-01-31 13:15:00+01:00",
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"2023-01-31 13:30:00+01:00",
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"2023-01-31 13:45:00+01:00",
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"2023-01-31 14:00:00+01:00",
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"2023-01-31 14:15:00+01:00",
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"2023-01-31 14:30:00+01:00",
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"2023-01-31 14:45:00+01:00",
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"2023-01-31 15:00:00+01:00",
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"2023-01-31 15:15:00+01:00",
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"2023-01-31 15:30:00+01:00",
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"2023-01-31 15:45:00+01:00",
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"2023-01-31 16:00:00+01:00",
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"2023-01-31 16:15:00+01:00",
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"2023-01-31 16:30:00+01:00",
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"2023-01-31 16:45:00+01:00",
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"2023-01-31 17:00:00+01:00",
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"2023-01-31 17:15:00+01:00",
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"2023-01-31 17:30:00+01:00",
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"2023-01-31 17:45:00+01:00",
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"2023-01-31 18:15:00+01:00",
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"2023-01-31 18:30:00+01:00",
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"2023-01-31 18:45:00+01:00",
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"2023-01-31 19:00:00+01:00",
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"2023-01-31 19:15:00+01:00",
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"2023-01-31 19:30:00+01:00",
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"2023-01-31 19:45:00+01:00",
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"2023-01-31 20:00:00+01:00",
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"2023-01-31 20:15:00+01:00",
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"2023-01-31 20:30:00+01:00",
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"2023-01-31 20:45:00+01:00",
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"2023-01-31 21:00:00+01:00",
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"2023-01-31 21:15:00+01:00",
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"2023-01-31 21:30:00+01:00",
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"2023-01-31 21:45:00+01:00",
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"2023-01-31 22:15:00+01:00",
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"2023-01-31 22:30:00+01:00",
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"2023-01-31 22:45:00+01:00",
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"2023-01-31 23:00:00+01:00",
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"2023-01-31 23:15:00+01:00",
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"2023-01-31 23:30:00+01:00",
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"2023-01-31 23:45:00+01:00",
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"2023-02-01 00:00:00+01:00",
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"2023-02-01 00:15:00+01:00",
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"2023-02-01 00:30:00+01:00",
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"2023-02-01 00:45:00+01:00",
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"2023-02-01 01:00:00+01:00",
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"2023-02-01 01:15:00+01:00",
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"2023-02-01 01:30:00+01:00",
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"2023-02-01 01:45:00+01:00",
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"2023-02-01 02:00:00+01:00",
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"2023-02-01 02:15:00+01:00",
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"2023-02-01 02:30:00+01:00",
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"2023-02-01 02:45:00+01:00",
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"2023-02-01 03:00:00+01:00",
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"2023-02-01 03:15:00+01:00",
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"2023-02-01 03:30:00+01:00",
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"2023-02-01 03:45:00+01:00",
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"2023-02-01 04:00:00+01:00",
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"2023-02-01 04:15:00+01:00",
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"2023-02-01 04:30:00+01:00",
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"2023-02-01 04:45:00+01:00",
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"2023-02-01 05:00:00+01:00",
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"2023-02-01 05:15:00+01:00",
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"2023-02-01 05:30:00+01:00",
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"2023-02-01 05:45:00+01:00",
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"2023-02-01 06:00:00+01:00",
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"2023-02-01 06:15:00+01:00",
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"2023-02-01 06:30:00+01:00",
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"2023-02-01 06:45:00+01:00",
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"2023-02-01 07:00:00+01:00",
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"2023-02-01 07:15:00+01:00",
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"2023-02-01 07:30:00+01:00",
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"2023-02-01 07:45:00+01:00",
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"2023-02-01 08:00:00+01:00",
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"2023-02-01 08:15:00+01:00",
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"2023-02-01 08:30:00+01:00",
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"2023-02-01 08:45:00+01:00",
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"2023-02-01 09:00:00+01:00",
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"2023-02-01 09:15:00+01:00",
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"2023-02-01 09:30:00+01:00",
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"2023-02-01 09:45:00+01:00",
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"2023-02-01 10:00:00+01:00",
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"2023-02-01 10:15:00+01:00",
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"2023-02-01 10:30:00+01:00",
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"2023-02-01 10:45:00+01:00",
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"2023-02-01 11:00:00+01:00",
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"2023-02-01 11:15:00+01:00",
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"2023-02-01 11:30:00+01:00",
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"2023-02-01 11:45:00+01:00",
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"2023-02-01 12:00:00+01:00",
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"2023-02-01 12:15:00+01:00",
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"2023-02-01 12:30:00+01:00",
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"2023-02-01 12:45:00+01:00",
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"2023-02-01 13:00:00+01:00",
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"2023-02-01 13:15:00+01:00",
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"2023-02-01 13:30:00+01:00",
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"2023-02-01 13:45:00+01:00",
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"2023-02-01 14:00:00+01:00",
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"2023-02-01 14:15:00+01:00",
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"2023-02-01 14:30:00+01:00",
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"2023-02-01 14:45:00+01:00",
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"2023-02-01 15:00:00+01:00",
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"2023-02-01 15:15:00+01:00",
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"2023-02-01 15:30:00+01:00",
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"2023-02-01 15:45:00+01:00",
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"2023-02-01 16:00:00+01:00",
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"2023-02-01 16:15:00+01:00",
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"2023-02-01 16:30:00+01:00",
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"2023-02-01 16:45:00+01:00",
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"2023-02-01 17:00:00+01:00",
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"2023-02-01 17:15:00+01:00",
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"2023-02-01 17:30:00+01:00",
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"2023-02-01 17:45:00+01:00",
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"2023-02-01 18:00:00+01:00",
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"2023-02-01 18:15:00+01:00",
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"2023-02-01 18:30:00+01:00",
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"2023-02-01 18:45:00+01:00",
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"2023-02-01 19:00:00+01:00",
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"2023-02-01 19:15:00+01:00",
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"2023-02-01 19:30:00+01:00",
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"2023-02-01 19:45:00+01:00",
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"2023-02-01 20:00:00+01:00",
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"2023-02-01 20:15:00+01:00",
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"2023-02-01 20:30:00+01:00",
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"2023-02-01 20:45:00+01:00",
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"2023-02-01 21:00:00+01:00",
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"2023-02-01 21:15:00+01:00",
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"2023-02-01 21:30:00+01:00",
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"2023-02-01 21:45:00+01:00",
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"2023-02-01 22:00:00+01:00",
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"2023-02-01 22:15:00+01:00",
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"2023-02-01 22:30:00+01:00",
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"2023-02-01 22:45:00+01:00",
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"2023-02-01 23:00:00+01:00",
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"2023-02-01 23:15:00+01:00",
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"2023-02-01 23:30:00+01:00",
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"2023-02-01 23:45:00+01:00",
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"2023-02-02 00:00:00+01:00",
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"2023-02-02 00:15:00+01:00",
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"2023-02-02 00:30:00+01:00",
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"2023-02-02 00:45:00+01:00",
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"2023-02-02 01:00:00+01:00",
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"2023-02-02 01:15:00+01:00",
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"2023-02-02 01:30:00+01:00",
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"2023-02-02 01:45:00+01:00",
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"2023-02-02 02:00:00+01:00",
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"2023-02-02 02:15:00+01:00",
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"2023-02-02 02:30:00+01:00",
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"2023-02-02 02:45:00+01:00",
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"2023-02-02 03:00:00+01:00",
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"2023-02-02 03:15:00+01:00",
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"2023-02-02 03:30:00+01:00",
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"2023-02-02 03:45:00+01:00",
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"2023-02-02 04:00:00+01:00",
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"2023-02-02 04:15:00+01:00",
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"2023-02-02 04:30:00+01:00",
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"2023-02-02 04:45:00+01:00",
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"2023-02-02 05:00:00+01:00",
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"2023-02-02 05:15:00+01:00",
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"2023-02-02 05:30:00+01:00",
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"2023-02-02 05:45:00+01:00",
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"2023-02-02 06:00:00+01:00",
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"2023-02-02 06:15:00+01:00",
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"2023-02-02 06:30:00+01:00",
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"2023-02-02 06:45:00+01:00",
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"2023-02-02 07:00:00+01:00",
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"2023-02-02 07:15:00+01:00",
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"2023-02-02 07:30:00+01:00",
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"2023-02-02 07:45:00+01:00",
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"2023-02-02 08:00:00+01:00",
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"2023-02-02 08:15:00+01:00",
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"2023-02-02 08:30:00+01:00",
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"2023-02-02 08:45:00+01:00",
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"2023-02-02 09:00:00+01:00",
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"2023-02-02 09:15:00+01:00",
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"2023-02-02 09:30:00+01:00",
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"2023-02-02 09:45:00+01:00",
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"2023-02-02 10:00:00+01:00",
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"2023-02-02 10:15:00+01:00",
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"2023-02-02 10:30:00+01:00",
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"2023-02-02 10:45:00+01:00",
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"2023-02-02 11:00:00+01:00",
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"2023-02-02 11:15:00+01:00",
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"2023-02-02 11:30:00+01:00",
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"2023-02-02 11:45:00+01:00",
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"2023-02-02 12:00:00+01:00",
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"2023-02-02 12:15:00+01:00",
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"2023-02-02 12:30:00+01:00",
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"2023-02-02 12:45:00+01:00",
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"2023-02-02 13:00:00+01:00",
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"2023-02-02 13:15:00+01:00",
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"2023-02-02 13:30:00+01:00",
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"2023-02-02 13:45:00+01:00",
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"2023-02-02 14:00:00+01:00",
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"2023-02-02 14:15:00+01:00",
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"2023-02-02 14:30:00+01:00",
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"2023-02-02 14:45:00+01:00",
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"2023-02-02 15:00:00+01:00",
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"2023-02-02 15:15:00+01:00",
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"2023-02-02 15:30:00+01:00",
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"2023-02-02 15:45:00+01:00",
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"2023-02-02 16:00:00+01:00",
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"2023-02-02 16:15:00+01:00",
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"2023-02-02 16:30:00+01:00",
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"2023-02-02 16:45:00+01:00",
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"2023-02-02 17:00:00+01:00",
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"2023-02-02 17:15:00+01:00",
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"2023-02-02 17:30:00+01:00",
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"2023-02-02 17:45:00+01:00",
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"2023-02-02 18:00:00+01:00",
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"2023-02-02 18:15:00+01:00",
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"2023-02-02 18:30:00+01:00",
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"2023-02-02 18:45:00+01:00",
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"2023-02-02 19:00:00+01:00",
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"2023-02-02 19:15:00+01:00",
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"2023-02-02 19:30:00+01:00",
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"2023-02-02 19:45:00+01:00",
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"2023-02-02 20:00:00+01:00",
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"2023-02-02 20:15:00+01:00",
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"2023-02-02 20:30:00+01:00",
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"2023-02-02 20:45:00+01:00",
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"2023-02-02 21:00:00+01:00",
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"2023-02-02 21:15:00+01:00",
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"2023-02-02 21:30:00+01:00",
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"2023-02-02 21:45:00+01:00",
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"2023-02-02 22:00:00+01:00",
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"2023-02-02 22:15:00+01:00",
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"2023-02-02 22:30:00+01:00",
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"2023-02-02 22:45:00+01:00",
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"2023-02-02 23:00:00+01:00",
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"2023-02-02 23:15:00+01:00",
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"2023-02-02 23:30:00+01:00",
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"2023-02-02 23:45:00+01:00",
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"2023-02-03 00:00:00+01:00",
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"2023-02-03 00:15:00+01:00",
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"2023-02-03 00:30:00+01:00",
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"2023-02-03 00:45:00+01:00",
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"2023-02-03 01:00:00+01:00",
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"2023-02-03 01:15:00+01:00",
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"2023-02-03 01:30:00+01:00",
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"2023-02-03 01:45:00+01:00",
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"2023-02-03 02:00:00+01:00",
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"2023-02-03 02:15:00+01:00",
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"2023-02-03 02:30:00+01:00",
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"2023-02-03 02:45:00+01:00",
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"2023-02-03 03:00:00+01:00",
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"2023-02-03 03:15:00+01:00",
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"2023-02-03 03:30:00+01:00",
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"2023-02-03 03:45:00+01:00",
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"2023-02-03 04:00:00+01:00",
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"2023-02-03 04:15:00+01:00",
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"2023-02-03 04:30:00+01:00",
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"2023-02-03 04:45:00+01:00",
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"2023-02-03 05:00:00+01:00",
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"2023-02-03 05:15:00+01:00",
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"2023-02-03 05:30:00+01:00",
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"2023-02-03 05:45:00+01:00",
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"2023-02-03 06:00:00+01:00",
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"2023-02-03 06:15:00+01:00",
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"2023-02-03 06:30:00+01:00",
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"2023-02-03 06:45:00+01:00",
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"2023-02-03 07:00:00+01:00",
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"2023-02-03 07:15:00+01:00",
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"2023-02-03 07:30:00+01:00",
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"2023-02-03 07:45:00+01:00",
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"2023-02-03 08:00:00+01:00",
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"2023-02-03 08:15:00+01:00",
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"2023-02-03 08:30:00+01:00",
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"2023-02-03 08:45:00+01:00",
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"2023-02-03 09:00:00+01:00",
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"2023-02-03 09:15:00+01:00",
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"2023-02-03 09:30:00+01:00",
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"2023-02-03 09:45:00+01:00",
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"2023-02-03 10:00:00+01:00",
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"2023-02-03 10:15:00+01:00",
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"2023-02-03 10:30:00+01:00",
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"2023-02-03 10:45:00+01:00",
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"2023-02-03 11:00:00+01:00",
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"2023-02-03 11:15:00+01:00",
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"2023-02-03 11:30:00+01:00",
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"2023-02-03 11:45:00+01:00",
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"2023-02-03 12:00:00+01:00",
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"2023-02-03 12:15:00+01:00",
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"2023-02-03 12:30:00+01:00",
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"2023-02-03 12:45:00+01:00",
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"2023-02-03 13:00:00+01:00",
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"2023-02-03 13:15:00+01:00",
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"2023-02-03 13:30:00+01:00",
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"2023-02-03 13:45:00+01:00",
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"2023-02-03 14:00:00+01:00",
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"2023-02-03 14:15:00+01:00",
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"2023-02-03 14:30:00+01:00",
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"2023-02-03 14:45:00+01:00",
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"2023-02-03 15:00:00+01:00",
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"2023-02-03 15:15:00+01:00",
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"2023-02-03 15:30:00+01:00",
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"2023-02-03 15:45:00+01:00",
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"2023-02-03 16:00:00+01:00",
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"2023-02-03 16:15:00+01:00",
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"2023-02-03 16:30:00+01:00",
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"2023-02-03 16:45:00+01:00",
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"2023-02-03 17:00:00+01:00",
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"2023-02-03 17:15:00+01:00",
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"2023-02-03 17:30:00+01:00",
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"2023-02-03 17:45:00+01:00",
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"2023-02-03 18:00:00+01:00",
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"2023-02-03 18:15:00+01:00",
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"2023-02-03 18:30:00+01:00",
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"2023-02-03 18:45:00+01:00",
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"2023-02-03 19:00:00+01:00",
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"2023-02-03 19:15:00+01:00",
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"2023-02-03 19:30:00+01:00",
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"2023-02-03 19:45:00+01:00",
|
|
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"2023-01-04 02:30:00+01:00",
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"2023-01-04 02:45:00+01:00",
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"2023-01-04 03:00:00+01:00",
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"2023-01-04 03:15:00+01:00",
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"2023-01-04 03:30:00+01:00",
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"2023-01-04 03:45:00+01:00",
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"2023-01-04 04:00:00+01:00",
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"2023-01-04 04:15:00+01:00",
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"2023-01-04 04:30:00+01:00",
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"2023-01-04 04:45:00+01:00",
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"2023-01-04 05:15:00+01:00",
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"2023-01-04 05:30:00+01:00",
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"2023-01-04 05:45:00+01:00",
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"2023-01-04 06:15:00+01:00",
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"2023-01-04 07:15:00+01:00",
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"2023-01-04 08:15:00+01:00",
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"2023-01-04 08:30:00+01:00",
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"2023-01-04 08:45:00+01:00",
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"2023-01-04 09:15:00+01:00",
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"2023-01-04 09:45:00+01:00",
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"2023-01-04 10:15:00+01:00",
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"2023-01-04 10:30:00+01:00",
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"2023-01-04 10:45:00+01:00",
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"2023-01-04 11:00:00+01:00",
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"2023-01-04 11:15:00+01:00",
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"2023-01-04 11:30:00+01:00",
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"2023-01-04 11:45:00+01:00",
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"2023-01-04 12:00:00+01:00",
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"2023-01-04 12:15:00+01:00",
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"2023-01-04 12:30:00+01:00",
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"2023-01-04 12:45:00+01:00",
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"2023-01-04 13:00:00+01:00",
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"2023-01-04 13:15:00+01:00",
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"2023-01-04 14:15:00+01:00",
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"2023-01-04 15:30:00+01:00",
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"2023-01-04 15:45:00+01:00",
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"2023-01-04 16:30:00+01:00",
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"2023-01-04 16:45:00+01:00",
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"2023-01-04 17:15:00+01:00",
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"2023-01-04 17:30:00+01:00",
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"2023-01-04 17:45:00+01:00",
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"2023-01-04 19:15:00+01:00",
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"2023-01-04 19:30:00+01:00",
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"2023-01-04 19:45:00+01:00",
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"2023-01-04 20:15:00+01:00",
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"2023-01-04 20:30:00+01:00",
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"2023-01-04 20:45:00+01:00",
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"2023-01-04 21:15:00+01:00",
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"2023-01-04 21:30:00+01:00",
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"2023-01-04 21:45:00+01:00",
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"2023-01-04 22:15:00+01:00",
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"2023-01-04 22:45:00+01:00",
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"2023-01-04 23:15:00+01:00",
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"2023-01-04 23:30:00+01:00",
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"2023-01-04 23:45:00+01:00",
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"2023-01-05 00:15:00+01:00",
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"2023-01-05 01:15:00+01:00",
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"2023-01-05 02:00:00+01:00",
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"2023-01-05 02:15:00+01:00",
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"2023-01-05 02:30:00+01:00",
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"2023-01-05 02:45:00+01:00",
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"2023-01-05 03:00:00+01:00",
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"2023-01-05 03:15:00+01:00",
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"2023-01-05 03:30:00+01:00",
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"2023-01-05 03:45:00+01:00",
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"2023-01-05 04:00:00+01:00",
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"2023-01-05 04:15:00+01:00",
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"2023-01-05 04:30:00+01:00",
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"2023-01-05 04:45:00+01:00",
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"2023-01-05 05:15:00+01:00",
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"2023-01-05 05:30:00+01:00",
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"2023-01-05 05:45:00+01:00",
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"2023-01-05 06:15:00+01:00",
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"2023-01-05 06:30:00+01:00",
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"2023-01-05 06:45:00+01:00",
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"2023-01-05 07:00:00+01:00",
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"2023-01-05 07:15:00+01:00",
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"2023-01-05 07:30:00+01:00",
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"2023-01-05 07:45:00+01:00",
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"2023-01-05 08:15:00+01:00",
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"2023-01-05 08:30:00+01:00",
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"2023-01-05 08:45:00+01:00",
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"2023-01-05 09:00:00+01:00",
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"2023-01-05 09:15:00+01:00",
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"2023-01-05 09:30:00+01:00",
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"2023-01-05 09:45:00+01:00",
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"2023-01-05 10:15:00+01:00",
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"2023-01-05 10:30:00+01:00",
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"2023-01-05 10:45:00+01:00",
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"2023-01-05 11:00:00+01:00",
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"2023-01-05 11:15:00+01:00",
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"2023-01-05 11:30:00+01:00",
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"2023-01-05 11:45:00+01:00",
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"2023-01-05 12:00:00+01:00",
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"2023-01-05 12:15:00+01:00",
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"2023-01-05 12:30:00+01:00",
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"2023-01-05 12:45:00+01:00",
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"2023-01-05 13:00:00+01:00",
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"2023-01-05 13:15:00+01:00",
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"2023-01-05 13:30:00+01:00",
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"2023-01-05 13:45:00+01:00",
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"2023-01-05 14:00:00+01:00",
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"2023-01-05 14:15:00+01:00",
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"2023-01-05 14:30:00+01:00",
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"2023-01-05 14:45:00+01:00",
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"2023-01-05 15:00:00+01:00",
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"2023-01-05 15:15:00+01:00",
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"2023-01-05 15:30:00+01:00",
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"2023-01-05 15:45:00+01:00",
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"2023-01-05 16:00:00+01:00",
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"2023-01-05 16:15:00+01:00",
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"2023-01-05 16:30:00+01:00",
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"2023-01-05 16:45:00+01:00",
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"2023-01-05 17:00:00+01:00",
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"2023-01-05 17:15:00+01:00",
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"2023-01-05 17:30:00+01:00",
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"2023-01-05 17:45:00+01:00",
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"2023-01-05 18:00:00+01:00",
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"2023-01-05 18:15:00+01:00",
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"2023-01-05 18:30:00+01:00",
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"2023-01-05 18:45:00+01:00",
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"2023-01-05 19:00:00+01:00",
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"2023-01-05 19:15:00+01:00",
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"2023-01-05 19:30:00+01:00",
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"2023-01-05 19:45:00+01:00",
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"2023-01-05 20:00:00+01:00",
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"2023-01-05 20:15:00+01:00",
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"2023-01-05 20:30:00+01:00",
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"2023-01-05 20:45:00+01:00",
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"2023-01-05 21:00:00+01:00",
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"2023-01-05 21:15:00+01:00",
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"2023-01-05 21:30:00+01:00",
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"2023-01-05 21:45:00+01:00",
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"2023-01-05 22:00:00+01:00",
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"2023-01-05 22:15:00+01:00",
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"2023-01-05 22:30:00+01:00",
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"2023-01-05 22:45:00+01:00",
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"2023-01-05 23:00:00+01:00",
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"2023-01-05 23:15:00+01:00",
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"2023-01-05 23:30:00+01:00",
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"2023-01-05 23:45:00+01:00",
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"2023-01-06 00:00:00+01:00",
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"2023-01-06 00:15:00+01:00",
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"2023-01-06 00:30:00+01:00",
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"2023-01-06 00:45:00+01:00",
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"2023-01-06 01:00:00+01:00",
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"2023-01-06 01:15:00+01:00",
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"2023-01-06 01:30:00+01:00",
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"2023-01-06 01:45:00+01:00",
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"2023-01-06 02:00:00+01:00",
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"2023-01-06 02:15:00+01:00",
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"2023-01-06 02:30:00+01:00",
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"2023-01-06 02:45:00+01:00",
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"2023-01-06 03:00:00+01:00",
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"2023-01-06 03:15:00+01:00",
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"2023-01-06 03:30:00+01:00",
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"2023-01-06 03:45:00+01:00",
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"2023-01-06 04:00:00+01:00",
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"2023-01-06 04:15:00+01:00",
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"2023-01-06 04:30:00+01:00",
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"2023-01-06 04:45:00+01:00",
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"2023-01-06 05:00:00+01:00",
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"2023-01-06 05:15:00+01:00",
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"2023-01-06 05:30:00+01:00",
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"2023-01-06 05:45:00+01:00",
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"2023-01-06 06:00:00+01:00",
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"2023-01-06 06:15:00+01:00",
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"2023-01-06 06:30:00+01:00",
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"2023-01-06 06:45:00+01:00",
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"2023-01-06 07:00:00+01:00",
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"2023-01-06 07:15:00+01:00",
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"2023-01-06 07:30:00+01:00",
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"2023-01-06 07:45:00+01:00",
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"2023-01-06 08:00:00+01:00",
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"2023-01-06 08:15:00+01:00",
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"2023-01-06 08:30:00+01:00",
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"2023-01-06 08:45:00+01:00",
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"2023-01-06 09:00:00+01:00",
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"2023-01-06 09:15:00+01:00",
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"2023-01-06 09:30:00+01:00",
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"2023-01-06 09:45:00+01:00",
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"2023-01-06 10:00:00+01:00",
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"2023-01-06 10:15:00+01:00",
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"2023-01-06 10:30:00+01:00",
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"2023-01-06 10:45:00+01:00",
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"2023-01-06 11:00:00+01:00",
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"2023-01-06 11:15:00+01:00",
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"2023-01-06 11:30:00+01:00",
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"2023-01-06 11:45:00+01:00",
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"2023-01-06 12:00:00+01:00",
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"2023-01-06 12:15:00+01:00",
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"2023-01-06 12:30:00+01:00",
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"2023-01-06 12:45:00+01:00",
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"2023-01-06 13:00:00+01:00",
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"2023-01-06 13:15:00+01:00",
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"2023-01-06 13:30:00+01:00",
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"2023-01-06 13:45:00+01:00",
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"2023-01-06 14:00:00+01:00",
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"2023-01-06 14:15:00+01:00",
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"2023-01-06 14:30:00+01:00",
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"2023-01-06 14:45:00+01:00",
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"2023-01-06 15:00:00+01:00",
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"2023-01-06 15:15:00+01:00",
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"2023-01-06 15:30:00+01:00",
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"2023-01-06 15:45:00+01:00",
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"2023-01-06 16:00:00+01:00",
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"2023-01-06 16:15:00+01:00",
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"2023-01-06 16:30:00+01:00",
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"2023-01-06 16:45:00+01:00",
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"2023-01-06 17:00:00+01:00",
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"2023-01-06 17:15:00+01:00",
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"2023-01-06 17:30:00+01:00",
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"2023-01-06 17:45:00+01:00",
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"2023-01-06 18:00:00+01:00",
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"2023-01-06 18:15:00+01:00",
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"2023-01-06 18:30:00+01:00",
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"2023-01-06 18:45:00+01:00",
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"2023-01-06 19:00:00+01:00",
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"2023-01-06 19:15:00+01:00",
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"2023-01-06 19:30:00+01:00",
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"2023-01-06 19:45:00+01:00",
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"2023-01-06 20:00:00+01:00",
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"2023-01-06 20:15:00+01:00",
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"2023-01-06 20:30:00+01:00",
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"2023-01-06 20:45:00+01:00",
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"2023-01-06 21:00:00+01:00",
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"2023-01-06 21:15:00+01:00",
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"2023-01-06 21:30:00+01:00",
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"2023-01-06 21:45:00+01:00",
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"2023-01-06 22:00:00+01:00",
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"2023-01-06 22:15:00+01:00",
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"2023-01-06 22:30:00+01:00",
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"2023-01-06 22:45:00+01:00",
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"2023-01-06 23:00:00+01:00",
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"2023-01-06 23:15:00+01:00",
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"2023-01-06 23:30:00+01:00",
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"2023-01-06 23:45:00+01:00",
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"2023-01-07 00:00:00+01:00",
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"2023-01-07 00:15:00+01:00",
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"2023-01-07 00:30:00+01:00",
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"2023-01-07 00:45:00+01:00",
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"2023-01-07 01:00:00+01:00",
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"2023-01-07 01:15:00+01:00",
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"2023-01-07 01:30:00+01:00",
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"2023-01-07 01:45:00+01:00",
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"2023-01-07 02:00:00+01:00",
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"2023-01-07 02:15:00+01:00",
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"2023-01-07 02:30:00+01:00",
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"2023-01-07 02:45:00+01:00",
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"2023-01-07 03:00:00+01:00",
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"2023-01-07 03:15:00+01:00",
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"2023-01-07 03:30:00+01:00",
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"2023-01-07 03:45:00+01:00",
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"2023-01-07 04:00:00+01:00",
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"2023-01-07 04:15:00+01:00",
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"2023-01-07 04:30:00+01:00",
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"2023-01-07 04:45:00+01:00",
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"2023-01-07 05:00:00+01:00",
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"2023-01-07 05:15:00+01:00",
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"2023-01-07 05:30:00+01:00",
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"2023-01-07 05:45:00+01:00",
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"2023-01-07 06:00:00+01:00",
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"2023-01-07 06:15:00+01:00",
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"2023-01-07 06:30:00+01:00",
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"2023-01-07 06:45:00+01:00",
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"2023-01-07 07:00:00+01:00",
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"2023-01-07 07:15:00+01:00",
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"2023-01-07 07:30:00+01:00",
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"2023-01-07 07:45:00+01:00",
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"2023-01-07 08:00:00+01:00",
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"2023-01-07 08:15:00+01:00",
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"2023-01-07 08:30:00+01:00",
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"2023-01-07 08:45:00+01:00",
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"2023-01-07 09:00:00+01:00",
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"2023-01-07 09:15:00+01:00",
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"2023-01-07 09:30:00+01:00",
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"2023-01-07 09:45:00+01:00",
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"2023-01-07 10:00:00+01:00",
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"2023-01-07 10:15:00+01:00",
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"2023-01-07 10:30:00+01:00",
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"2023-01-07 10:45:00+01:00",
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"2023-01-07 11:00:00+01:00",
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"2023-01-07 11:15:00+01:00",
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"2023-01-07 11:30:00+01:00",
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"2023-01-07 11:45:00+01:00",
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"2023-01-07 12:00:00+01:00",
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"2023-01-07 12:15:00+01:00",
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"2023-01-07 12:30:00+01:00",
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"2023-01-07 12:45:00+01:00",
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"2023-01-07 13:00:00+01:00",
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"2023-01-07 13:15:00+01:00",
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"2023-01-07 13:30:00+01:00",
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"2023-01-07 13:45:00+01:00",
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"2023-01-07 14:00:00+01:00",
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"2023-01-07 14:15:00+01:00",
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"2023-01-07 14:30:00+01:00",
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"2023-01-07 14:45:00+01:00",
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"2023-01-07 15:00:00+01:00",
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"2023-01-07 15:15:00+01:00",
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"2023-01-07 15:30:00+01:00",
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"2023-01-07 15:45:00+01:00",
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"2023-01-07 16:00:00+01:00",
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"2023-01-07 16:15:00+01:00",
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"2023-01-07 16:30:00+01:00",
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"2023-01-07 16:45:00+01:00",
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"2023-01-07 17:00:00+01:00",
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"2023-01-07 17:15:00+01:00",
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"2023-01-07 17:30:00+01:00",
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"2023-01-07 17:45:00+01:00",
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"2023-01-07 18:00:00+01:00",
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"2023-01-07 18:15:00+01:00",
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"2023-01-07 18:30:00+01:00",
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"2023-01-07 18:45:00+01:00",
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"2023-01-07 19:00:00+01:00",
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"2023-01-07 19:15:00+01:00",
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"2023-01-07 19:30:00+01:00",
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"2023-01-07 19:45:00+01:00",
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"2023-01-07 20:00:00+01:00",
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"2023-01-07 20:15:00+01:00",
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"2023-01-07 20:30:00+01:00",
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"2023-01-07 20:45:00+01:00",
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"2023-01-07 21:00:00+01:00",
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"2023-01-07 21:15:00+01:00",
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"2023-01-07 21:30:00+01:00",
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"2023-01-07 21:45:00+01:00",
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"2023-01-07 22:00:00+01:00",
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"2023-01-07 22:15:00+01:00",
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"2023-01-07 22:30:00+01:00",
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"2023-01-07 22:45:00+01:00",
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"2023-01-07 23:00:00+01:00",
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"2023-01-07 23:15:00+01:00",
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"2023-01-07 23:30:00+01:00",
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"2023-01-07 23:45:00+01:00",
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"2023-01-08 00:00:00+01:00",
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"2023-01-08 00:15:00+01:00",
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"2023-01-08 00:30:00+01:00",
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"2023-01-08 00:45:00+01:00",
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"2023-01-08 01:00:00+01:00",
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"2023-01-08 01:15:00+01:00",
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"2023-01-08 01:30:00+01:00",
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"2023-01-08 01:45:00+01:00",
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"2023-01-08 02:00:00+01:00",
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"2023-01-08 02:15:00+01:00",
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"2023-01-08 02:30:00+01:00",
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"2023-01-08 02:45:00+01:00",
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"2023-01-08 03:00:00+01:00",
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"2023-01-08 03:15:00+01:00",
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"2023-01-08 03:30:00+01:00",
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"2023-01-08 03:45:00+01:00",
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"2023-01-08 04:00:00+01:00",
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"2023-01-08 04:15:00+01:00",
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"2023-01-08 04:30:00+01:00",
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"2023-01-08 04:45:00+01:00",
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"2023-01-08 05:00:00+01:00",
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"2023-01-08 05:15:00+01:00",
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"2023-01-08 05:30:00+01:00",
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"2023-01-08 05:45:00+01:00",
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"2023-01-08 06:00:00+01:00",
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"2023-01-08 06:15:00+01:00",
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"2023-01-08 06:30:00+01:00",
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"2023-01-08 06:45:00+01:00",
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"2023-01-08 07:00:00+01:00",
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"2023-01-08 07:15:00+01:00",
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"2023-01-08 07:30:00+01:00",
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"2023-01-08 07:45:00+01:00",
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"2023-01-08 08:00:00+01:00",
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"2023-01-08 08:15:00+01:00",
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"2023-01-08 08:30:00+01:00",
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"2023-01-08 08:45:00+01:00",
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"2023-01-08 09:00:00+01:00",
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"2023-01-08 09:15:00+01:00",
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"2023-01-08 09:30:00+01:00",
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"2023-01-08 09:45:00+01:00",
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"2023-01-08 10:00:00+01:00",
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"2023-01-08 10:15:00+01:00",
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"2023-01-08 10:30:00+01:00",
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"2023-01-08 10:45:00+01:00",
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"2023-01-08 11:00:00+01:00",
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"2023-01-08 11:15:00+01:00",
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"2023-01-08 11:30:00+01:00",
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"2023-01-08 11:45:00+01:00",
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"2023-01-08 12:00:00+01:00",
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"2023-01-08 12:15:00+01:00",
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"2023-01-08 12:30:00+01:00",
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"2023-01-08 12:45:00+01:00",
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"2023-01-08 13:00:00+01:00",
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"2023-01-08 13:15:00+01:00",
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"2023-01-08 13:30:00+01:00",
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"2023-01-08 13:45:00+01:00",
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"2023-01-08 14:00:00+01:00",
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"2023-01-08 14:15:00+01:00",
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"2023-01-08 14:30:00+01:00",
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"2023-01-08 14:45:00+01:00",
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"2023-01-08 15:00:00+01:00",
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"2023-01-08 15:15:00+01:00",
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"2023-01-08 15:30:00+01:00",
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"2023-01-08 15:45:00+01:00",
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"2023-01-08 16:00:00+01:00",
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"2023-01-08 16:15:00+01:00",
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"2023-01-08 16:30:00+01:00",
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"2023-01-08 16:45:00+01:00",
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"2023-01-08 17:00:00+01:00",
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"2023-01-08 17:15:00+01:00",
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"2023-01-08 17:30:00+01:00",
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"2023-01-08 17:45:00+01:00",
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"2023-01-08 18:00:00+01:00",
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"2023-01-08 18:15:00+01:00",
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"2023-01-08 18:30:00+01:00",
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"2023-01-08 18:45:00+01:00",
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"2023-01-08 19:00:00+01:00",
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"2023-01-08 19:15:00+01:00",
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"2023-01-08 19:30:00+01:00",
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"2023-01-08 19:45:00+01:00",
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"2023-01-08 20:00:00+01:00",
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"2023-01-08 20:15:00+01:00",
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"2023-01-08 20:30:00+01:00",
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"2023-01-08 20:45:00+01:00",
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"2023-01-08 21:00:00+01:00",
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"2023-01-08 21:15:00+01:00",
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"2023-01-08 21:30:00+01:00",
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"2023-01-08 21:45:00+01:00",
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"2023-01-08 22:00:00+01:00",
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"2023-01-08 22:15:00+01:00",
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"2023-01-08 22:30:00+01:00",
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"2023-01-08 22:45:00+01:00",
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"2023-01-08 23:00:00+01:00",
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"2023-01-08 23:15:00+01:00",
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"2023-01-08 23:30:00+01:00",
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"2023-01-08 23:45:00+01:00",
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"2023-01-09 00:00:00+01:00",
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"2023-01-09 00:15:00+01:00",
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"2023-01-09 00:30:00+01:00",
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"2023-01-09 00:45:00+01:00",
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"2023-01-09 01:00:00+01:00",
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"2023-01-09 01:15:00+01:00",
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"2023-01-09 01:30:00+01:00",
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"2023-01-09 01:45:00+01:00",
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"2023-01-09 02:00:00+01:00",
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"2023-01-09 02:15:00+01:00",
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"2023-01-09 02:30:00+01:00",
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"2023-01-09 02:45:00+01:00",
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"2023-01-09 03:00:00+01:00",
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"2023-01-09 03:15:00+01:00",
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"2023-01-09 03:30:00+01:00",
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"2023-01-09 03:45:00+01:00",
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"2023-01-09 04:00:00+01:00",
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"2023-01-09 04:15:00+01:00",
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"2023-01-09 04:30:00+01:00",
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"2023-01-09 04:45:00+01:00",
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"2023-01-09 05:00:00+01:00",
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"2023-01-09 05:15:00+01:00",
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"2023-01-09 05:30:00+01:00",
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"2023-01-09 05:45:00+01:00",
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"2023-01-09 06:00:00+01:00",
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"2023-01-09 06:15:00+01:00",
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"2023-01-09 06:30:00+01:00",
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"2023-01-09 06:45:00+01:00",
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"2023-01-09 07:00:00+01:00",
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"2023-01-09 07:15:00+01:00",
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"2023-01-09 07:30:00+01:00",
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"2023-01-09 07:45:00+01:00",
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"2023-01-09 08:00:00+01:00",
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"2023-01-09 08:15:00+01:00",
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"2023-01-09 08:30:00+01:00",
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"2023-01-09 08:45:00+01:00",
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"2023-01-09 09:00:00+01:00",
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"2023-01-09 09:15:00+01:00",
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"2023-01-09 09:30:00+01:00",
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"2023-01-09 09:45:00+01:00",
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"2023-01-09 10:00:00+01:00",
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"2023-01-09 10:15:00+01:00",
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"2023-01-09 10:30:00+01:00",
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"2023-01-09 10:45:00+01:00",
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"2023-01-09 11:00:00+01:00",
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"2023-01-09 11:15:00+01:00",
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"2023-01-09 11:30:00+01:00",
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"2023-01-09 11:45:00+01:00",
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"2023-01-09 12:00:00+01:00",
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"2023-01-09 12:15:00+01:00",
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"2023-01-09 12:30:00+01:00",
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"2023-01-09 12:45:00+01:00",
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"2023-01-09 13:00:00+01:00",
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"2023-01-09 13:15:00+01:00",
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"2023-01-09 13:30:00+01:00",
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"2023-01-09 13:45:00+01:00",
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"2023-01-09 14:00:00+01:00",
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"2023-01-09 14:15:00+01:00",
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"2023-01-09 14:30:00+01:00",
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"2023-01-09 14:45:00+01:00",
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"2023-01-09 15:00:00+01:00",
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"2023-01-09 15:15:00+01:00",
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"2023-01-09 15:30:00+01:00",
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"2023-01-09 15:45:00+01:00",
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"2023-01-09 16:00:00+01:00",
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"2023-01-09 16:15:00+01:00",
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"2023-01-09 16:30:00+01:00",
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"2023-01-09 16:45:00+01:00",
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"2023-01-09 17:00:00+01:00",
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"2023-01-09 17:15:00+01:00",
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"2023-01-09 17:30:00+01:00",
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"2023-01-09 17:45:00+01:00",
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"2023-01-09 18:00:00+01:00",
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"2023-01-09 18:15:00+01:00",
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"2023-01-09 18:30:00+01:00",
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"2023-01-09 18:45:00+01:00",
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"2023-01-09 19:00:00+01:00",
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"2023-01-09 19:15:00+01:00",
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"2023-01-09 19:30:00+01:00",
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"2023-01-09 19:45:00+01:00",
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"2023-01-09 20:00:00+01:00",
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"2023-01-09 20:15:00+01:00",
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"2023-01-09 20:30:00+01:00",
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"2023-01-09 20:45:00+01:00",
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"2023-01-09 21:00:00+01:00",
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"2023-01-09 21:15:00+01:00",
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"2023-01-09 21:30:00+01:00",
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"2023-01-09 21:45:00+01:00",
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"2023-01-09 22:00:00+01:00",
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"2023-01-09 22:15:00+01:00",
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"2023-01-09 22:30:00+01:00",
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"2023-01-09 22:45:00+01:00",
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"2023-01-09 23:00:00+01:00",
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"2023-01-09 23:15:00+01:00",
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"2023-01-09 23:30:00+01:00",
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"2023-01-09 23:45:00+01:00",
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"2023-01-10 00:00:00+01:00",
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"2023-01-10 00:15:00+01:00",
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"2023-01-10 00:30:00+01:00",
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"2023-01-10 00:45:00+01:00",
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"2023-01-10 01:00:00+01:00",
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"2023-01-10 01:15:00+01:00",
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"2023-01-10 01:30:00+01:00",
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"2023-01-10 01:45:00+01:00",
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"2023-01-10 02:00:00+01:00",
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"2023-01-10 02:15:00+01:00",
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"2023-01-10 02:30:00+01:00",
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"2023-01-10 02:45:00+01:00",
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"2023-01-10 03:00:00+01:00",
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"2023-01-10 03:15:00+01:00",
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"2023-01-10 03:30:00+01:00",
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"2023-01-10 03:45:00+01:00",
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"2023-01-10 04:00:00+01:00",
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"2023-01-10 04:15:00+01:00",
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"2023-01-10 04:30:00+01:00",
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"2023-01-10 04:45:00+01:00",
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"2023-01-10 05:00:00+01:00",
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"2023-01-10 05:15:00+01:00",
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"2023-01-10 05:30:00+01:00",
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"2023-01-10 05:45:00+01:00",
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"2023-01-10 06:00:00+01:00",
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"2023-01-10 06:15:00+01:00",
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"2023-01-10 06:30:00+01:00",
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"2023-01-10 06:45:00+01:00",
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"2023-01-10 07:00:00+01:00",
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"2023-01-10 07:15:00+01:00",
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"2023-01-10 07:30:00+01:00",
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"2023-01-10 07:45:00+01:00",
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"2023-01-10 08:00:00+01:00",
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"2023-01-10 08:15:00+01:00",
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"2023-01-10 08:30:00+01:00",
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"2023-01-10 08:45:00+01:00",
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"2023-01-10 09:00:00+01:00",
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"2023-01-10 09:15:00+01:00",
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"2023-01-10 09:30:00+01:00",
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"2023-01-10 09:45:00+01:00",
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"2023-01-10 10:00:00+01:00",
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"2023-01-10 10:15:00+01:00",
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"2023-01-10 10:30:00+01:00",
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"2023-01-10 10:45:00+01:00",
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"2023-01-10 11:00:00+01:00",
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"2023-01-10 11:15:00+01:00",
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"2023-01-10 11:30:00+01:00",
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"2023-01-10 11:45:00+01:00",
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"2023-01-10 12:00:00+01:00",
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"2023-01-10 12:15:00+01:00",
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"2023-01-10 12:30:00+01:00",
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"2023-01-10 12:45:00+01:00",
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"2023-01-10 13:00:00+01:00",
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"2023-01-10 13:15:00+01:00",
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"2023-01-10 13:30:00+01:00",
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"2023-01-10 13:45:00+01:00",
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"2023-01-10 14:00:00+01:00",
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"2023-01-10 14:15:00+01:00",
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"2023-01-10 14:30:00+01:00",
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"2023-01-10 14:45:00+01:00",
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"2023-01-10 15:00:00+01:00",
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"2023-01-10 15:15:00+01:00",
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"2023-01-10 15:30:00+01:00",
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"2023-01-10 15:45:00+01:00",
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"2023-01-10 16:00:00+01:00",
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"2023-01-10 16:15:00+01:00",
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"2023-01-10 16:30:00+01:00",
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"2023-01-10 16:45:00+01:00",
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"2023-01-10 17:00:00+01:00",
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"2023-01-10 17:15:00+01:00",
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"2023-01-10 17:30:00+01:00",
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"2023-01-10 17:45:00+01:00",
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"2023-01-10 18:00:00+01:00",
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"2023-01-10 18:15:00+01:00",
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"2023-01-10 18:30:00+01:00",
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"2023-01-10 18:45:00+01:00",
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"2023-01-10 19:00:00+01:00",
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"2023-01-10 19:15:00+01:00",
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"2023-01-10 19:30:00+01:00",
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"2023-01-10 19:45:00+01:00",
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"2023-01-10 20:00:00+01:00",
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"2023-01-10 20:15:00+01:00",
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"2023-01-10 20:30:00+01:00",
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"2023-01-10 20:45:00+01:00",
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"2023-01-10 21:00:00+01:00",
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"2023-01-10 21:15:00+01:00",
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"2023-01-10 21:30:00+01:00",
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"2023-01-10 21:45:00+01:00",
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"2023-01-10 22:00:00+01:00",
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"2023-01-10 22:15:00+01:00",
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"2023-01-10 22:30:00+01:00",
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"2023-01-10 22:45:00+01:00",
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"2023-01-10 23:00:00+01:00",
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"2023-01-10 23:15:00+01:00",
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"2023-01-10 23:30:00+01:00",
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"2023-01-10 23:45:00+01:00",
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"2023-01-11 00:00:00+01:00",
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"2023-01-11 00:15:00+01:00",
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"2023-01-11 00:30:00+01:00",
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"2023-01-11 00:45:00+01:00",
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"2023-01-11 01:00:00+01:00",
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"2023-01-11 01:15:00+01:00",
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"2023-01-11 01:30:00+01:00",
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"2023-01-11 01:45:00+01:00",
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"2023-01-11 02:00:00+01:00",
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"2023-01-11 02:15:00+01:00",
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"2023-01-11 02:30:00+01:00",
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"2023-01-11 02:45:00+01:00",
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"2023-01-11 03:00:00+01:00",
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"2023-01-11 03:15:00+01:00",
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"2023-01-11 03:30:00+01:00",
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"2023-01-11 03:45:00+01:00",
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"2023-01-11 04:00:00+01:00",
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"2023-01-11 04:15:00+01:00",
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"2023-01-11 04:30:00+01:00",
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"2023-01-11 04:45:00+01:00",
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"2023-01-11 05:00:00+01:00",
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"2023-01-11 05:15:00+01:00",
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"2023-01-11 05:30:00+01:00",
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"2023-01-11 05:45:00+01:00",
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"2023-01-11 06:00:00+01:00",
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"2023-01-11 06:15:00+01:00",
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"2023-01-11 06:30:00+01:00",
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"2023-01-11 06:45:00+01:00",
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"2023-01-11 07:00:00+01:00",
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"2023-01-11 07:15:00+01:00",
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"2023-01-11 07:30:00+01:00",
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"2023-01-11 07:45:00+01:00",
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"2023-01-11 08:00:00+01:00",
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"2023-01-11 08:15:00+01:00",
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"2023-01-11 08:30:00+01:00",
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"2023-01-11 08:45:00+01:00",
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"2023-01-11 09:00:00+01:00",
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"2023-01-11 09:15:00+01:00",
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"2023-01-11 09:30:00+01:00",
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"2023-01-11 09:45:00+01:00",
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"2023-01-11 10:15:00+01:00",
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"2023-01-11 10:30:00+01:00",
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"2023-01-11 10:45:00+01:00",
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"2023-01-11 11:00:00+01:00",
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"2023-01-11 11:15:00+01:00",
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"2023-01-11 11:30:00+01:00",
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"2023-01-11 11:45:00+01:00",
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"2023-01-11 12:00:00+01:00",
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"2023-01-11 12:15:00+01:00",
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"2023-01-11 12:30:00+01:00",
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"2023-01-11 12:45:00+01:00",
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"2023-01-11 13:00:00+01:00",
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"2023-01-11 13:15:00+01:00",
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"2023-01-11 13:30:00+01:00",
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"2023-01-11 13:45:00+01:00",
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"2023-01-11 14:15:00+01:00",
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"2023-01-11 14:30:00+01:00",
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"2023-01-11 14:45:00+01:00",
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"2023-01-11 15:00:00+01:00",
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"2023-01-11 15:15:00+01:00",
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"2023-01-11 15:30:00+01:00",
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"2023-01-11 15:45:00+01:00",
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"2023-01-11 16:00:00+01:00",
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"2023-01-11 16:15:00+01:00",
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"2023-01-11 16:30:00+01:00",
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"2023-01-11 16:45:00+01:00",
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"2023-01-11 17:00:00+01:00",
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"2023-01-11 17:15:00+01:00",
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"2023-01-11 17:30:00+01:00",
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"2023-01-11 17:45:00+01:00",
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"2023-01-11 18:15:00+01:00",
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"2023-01-11 18:30:00+01:00",
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"2023-01-11 18:45:00+01:00",
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"2023-01-11 19:00:00+01:00",
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"2023-01-11 19:15:00+01:00",
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"2023-01-11 19:30:00+01:00",
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"2023-01-11 19:45:00+01:00",
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"2023-01-11 20:00:00+01:00",
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"2023-01-11 20:15:00+01:00",
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"2023-01-11 20:30:00+01:00",
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"2023-01-11 20:45:00+01:00",
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"2023-01-11 21:00:00+01:00",
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"2023-01-11 21:15:00+01:00",
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"2023-01-11 21:30:00+01:00",
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"2023-01-11 21:45:00+01:00",
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"2023-01-11 22:00:00+01:00",
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"2023-01-11 22:15:00+01:00",
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"2023-01-11 22:30:00+01:00",
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"2023-01-11 22:45:00+01:00",
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"2023-01-11 23:00:00+01:00",
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"2023-01-11 23:15:00+01:00",
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"2023-01-11 23:30:00+01:00",
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"2023-01-11 23:45:00+01:00",
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"2023-01-12 00:00:00+01:00",
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"2023-01-12 00:15:00+01:00",
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"2023-01-12 00:30:00+01:00",
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"2023-01-12 00:45:00+01:00",
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"2023-01-12 01:00:00+01:00",
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"2023-01-12 01:15:00+01:00",
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"2023-01-12 01:30:00+01:00",
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"2023-01-12 01:45:00+01:00",
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"2023-01-12 02:00:00+01:00",
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"2023-01-12 02:15:00+01:00",
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"2023-01-12 02:30:00+01:00",
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"2023-01-12 02:45:00+01:00",
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"2023-01-12 03:00:00+01:00",
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"2023-01-12 03:15:00+01:00",
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"2023-01-12 03:30:00+01:00",
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"2023-01-12 03:45:00+01:00",
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"2023-01-12 04:00:00+01:00",
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"2023-01-12 04:15:00+01:00",
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"2023-01-12 04:30:00+01:00",
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"2023-01-12 04:45:00+01:00",
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"2023-01-12 05:00:00+01:00",
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"2023-01-12 05:15:00+01:00",
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"2023-01-12 05:30:00+01:00",
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"2023-01-12 05:45:00+01:00",
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"2023-01-12 06:00:00+01:00",
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"2023-01-12 06:15:00+01:00",
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"2023-01-12 06:30:00+01:00",
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"2023-01-12 06:45:00+01:00",
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"2023-01-12 07:00:00+01:00",
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"2023-01-12 07:15:00+01:00",
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"2023-01-12 07:30:00+01:00",
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"2023-01-12 07:45:00+01:00",
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"2023-01-12 08:00:00+01:00",
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"2023-01-12 08:15:00+01:00",
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"2023-01-12 08:30:00+01:00",
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"2023-01-12 08:45:00+01:00",
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"2023-01-12 09:00:00+01:00",
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"2023-01-12 09:15:00+01:00",
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"2023-01-12 09:30:00+01:00",
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"2023-01-12 09:45:00+01:00",
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"2023-01-12 10:00:00+01:00",
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"2023-01-12 10:15:00+01:00",
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"2023-01-12 10:30:00+01:00",
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"2023-01-12 10:45:00+01:00",
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"2023-01-12 11:00:00+01:00",
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"2023-01-12 11:15:00+01:00",
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"2023-01-12 11:30:00+01:00",
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"2023-01-12 11:45:00+01:00",
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"2023-01-12 12:00:00+01:00",
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"2023-01-12 12:15:00+01:00",
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"2023-01-12 12:30:00+01:00",
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"2023-01-12 12:45:00+01:00",
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"2023-01-12 13:00:00+01:00",
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"2023-01-12 13:15:00+01:00",
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"2023-01-12 13:30:00+01:00",
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"2023-01-12 13:45:00+01:00",
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"2023-01-12 14:00:00+01:00",
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"2023-01-12 14:15:00+01:00",
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"2023-01-12 14:30:00+01:00",
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"2023-01-12 14:45:00+01:00",
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"2023-01-12 15:00:00+01:00",
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"2023-01-12 15:15:00+01:00",
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"2023-01-12 15:30:00+01:00",
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"2023-01-12 15:45:00+01:00",
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"2023-01-12 16:00:00+01:00",
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"2023-01-12 16:15:00+01:00",
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"2023-01-12 16:30:00+01:00",
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"2023-01-12 16:45:00+01:00",
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"2023-01-12 17:00:00+01:00",
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"2023-01-12 17:15:00+01:00",
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"2023-01-12 17:30:00+01:00",
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"2023-01-12 17:45:00+01:00",
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"2023-01-12 18:00:00+01:00",
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"2023-01-12 18:15:00+01:00",
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"2023-01-12 18:30:00+01:00",
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"2023-01-12 18:45:00+01:00",
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"2023-01-12 19:00:00+01:00",
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"2023-01-12 19:15:00+01:00",
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"2023-01-12 19:30:00+01:00",
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"2023-01-12 19:45:00+01:00",
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"2023-01-12 20:00:00+01:00",
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"2023-01-12 20:15:00+01:00",
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"2023-01-12 20:30:00+01:00",
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"2023-01-12 20:45:00+01:00",
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"2023-01-12 21:00:00+01:00",
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"2023-01-12 21:15:00+01:00",
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"2023-01-12 21:30:00+01:00",
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"2023-01-12 21:45:00+01:00",
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"2023-01-12 22:00:00+01:00",
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"2023-01-12 22:15:00+01:00",
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"2023-01-12 22:30:00+01:00",
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"2023-01-12 22:45:00+01:00",
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"2023-01-12 23:00:00+01:00",
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"2023-01-12 23:15:00+01:00",
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"2023-01-12 23:30:00+01:00",
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"2023-01-12 23:45:00+01:00",
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"2023-01-13 00:00:00+01:00",
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"2023-01-13 00:15:00+01:00",
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"2023-01-13 00:30:00+01:00",
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"2023-01-13 00:45:00+01:00",
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"2023-01-13 01:00:00+01:00",
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"2023-01-13 01:15:00+01:00",
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"2023-01-13 01:30:00+01:00",
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"2023-01-13 01:45:00+01:00",
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"2023-01-13 02:00:00+01:00",
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"2023-01-13 02:15:00+01:00",
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"2023-01-13 02:30:00+01:00",
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"2023-01-13 02:45:00+01:00",
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"2023-01-13 03:00:00+01:00",
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"2023-01-13 03:15:00+01:00",
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"2023-01-13 03:30:00+01:00",
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"2023-01-13 03:45:00+01:00",
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"2023-01-13 04:00:00+01:00",
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"2023-01-13 04:15:00+01:00",
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"2023-01-13 04:30:00+01:00",
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"2023-01-13 04:45:00+01:00",
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"2023-01-13 05:00:00+01:00",
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"2023-01-13 05:15:00+01:00",
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"2023-01-13 05:30:00+01:00",
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"2023-01-13 05:45:00+01:00",
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"2023-01-13 06:00:00+01:00",
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"2023-01-13 06:15:00+01:00",
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"2023-01-13 06:30:00+01:00",
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"2023-01-13 06:45:00+01:00",
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"2023-01-13 07:00:00+01:00",
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"2023-01-13 07:15:00+01:00",
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"2023-01-13 07:30:00+01:00",
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"2023-01-13 07:45:00+01:00",
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"2023-01-13 08:00:00+01:00",
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"2023-01-13 08:15:00+01:00",
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"2023-01-13 08:30:00+01:00",
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"2023-01-13 08:45:00+01:00",
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"2023-01-13 09:00:00+01:00",
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"2023-01-13 09:15:00+01:00",
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"2023-01-13 09:30:00+01:00",
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"2023-01-13 09:45:00+01:00",
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"2023-01-13 10:00:00+01:00",
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"2023-01-13 10:15:00+01:00",
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"2023-01-13 10:30:00+01:00",
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"2023-01-13 10:45:00+01:00",
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"2023-01-13 11:00:00+01:00",
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"2023-01-13 11:15:00+01:00",
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"2023-01-13 11:30:00+01:00",
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"2023-01-13 11:45:00+01:00",
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"2023-01-13 12:00:00+01:00",
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"2023-01-13 12:15:00+01:00",
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"2023-01-13 12:30:00+01:00",
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"2023-01-13 12:45:00+01:00",
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"2023-01-13 13:00:00+01:00",
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"2023-01-13 13:15:00+01:00",
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"2023-01-13 13:30:00+01:00",
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"2023-01-13 13:45:00+01:00",
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"2023-01-13 14:00:00+01:00",
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"2023-01-13 14:15:00+01:00",
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"2023-01-13 14:30:00+01:00",
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"2023-01-13 14:45:00+01:00",
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"2023-01-13 15:00:00+01:00",
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"2023-01-13 15:15:00+01:00",
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"2023-01-13 15:30:00+01:00",
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"2023-01-13 15:45:00+01:00",
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"2023-01-13 16:00:00+01:00",
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"2023-01-13 16:15:00+01:00",
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"2023-01-13 16:30:00+01:00",
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"2023-01-13 16:45:00+01:00",
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"2023-01-13 17:00:00+01:00",
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"2023-01-13 17:15:00+01:00",
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"2023-01-13 17:30:00+01:00",
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"2023-01-13 17:45:00+01:00",
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"2023-01-13 18:00:00+01:00",
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"2023-01-13 18:15:00+01:00",
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"2023-01-13 18:30:00+01:00",
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"2023-01-13 18:45:00+01:00",
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"2023-01-13 19:00:00+01:00",
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"2023-01-13 19:15:00+01:00",
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"2023-01-13 19:30:00+01:00",
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"2023-01-13 19:45:00+01:00",
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"2023-01-13 20:00:00+01:00",
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"2023-01-13 20:15:00+01:00",
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"2023-01-13 20:30:00+01:00",
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"2023-01-13 20:45:00+01:00",
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"2023-01-13 21:00:00+01:00",
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"2023-01-13 21:15:00+01:00",
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"2023-01-13 21:30:00+01:00",
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"2023-01-13 21:45:00+01:00",
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"2023-01-13 22:00:00+01:00",
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"2023-01-13 22:15:00+01:00",
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"2023-01-13 22:30:00+01:00",
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"2023-01-13 22:45:00+01:00",
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"2023-01-13 23:00:00+01:00",
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"2023-01-13 23:15:00+01:00",
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"2023-01-13 23:30:00+01:00",
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"2023-01-13 23:45:00+01:00",
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"2023-01-14 00:00:00+01:00",
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"2023-01-14 00:15:00+01:00",
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"2023-01-14 00:30:00+01:00",
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"2023-01-14 00:45:00+01:00",
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"2023-01-14 01:00:00+01:00",
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"2023-01-14 01:15:00+01:00",
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"2023-01-14 01:30:00+01:00",
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"2023-01-14 01:45:00+01:00",
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"2023-01-14 02:00:00+01:00",
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"2023-01-14 02:15:00+01:00",
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"2023-01-14 02:30:00+01:00",
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"2023-01-14 02:45:00+01:00",
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"2023-01-14 03:00:00+01:00",
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"2023-01-14 03:15:00+01:00",
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"2023-01-14 03:30:00+01:00",
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"2023-01-14 03:45:00+01:00",
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"2023-01-14 04:00:00+01:00",
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"2023-01-14 04:15:00+01:00",
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"2023-01-14 04:30:00+01:00",
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"2023-01-14 04:45:00+01:00",
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"2023-01-14 05:00:00+01:00",
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"2023-01-14 05:15:00+01:00",
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"2023-01-14 05:30:00+01:00",
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"2023-01-14 05:45:00+01:00",
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"2023-01-14 06:00:00+01:00",
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"2023-01-14 06:15:00+01:00",
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"2023-01-14 06:30:00+01:00",
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"2023-01-14 06:45:00+01:00",
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"2023-01-14 07:00:00+01:00",
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"2023-01-14 07:15:00+01:00",
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"2023-01-14 07:30:00+01:00",
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"2023-01-14 07:45:00+01:00",
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"2023-01-14 08:00:00+01:00",
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"2023-01-14 08:15:00+01:00",
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"2023-01-14 08:30:00+01:00",
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"2023-01-14 08:45:00+01:00",
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"2023-01-14 09:00:00+01:00",
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"2023-01-14 09:15:00+01:00",
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"2023-01-14 09:30:00+01:00",
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"2023-01-14 09:45:00+01:00",
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"2023-01-14 10:00:00+01:00",
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"2023-01-14 10:15:00+01:00",
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"2023-01-14 10:30:00+01:00",
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"2023-01-14 10:45:00+01:00",
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"2023-01-14 11:00:00+01:00",
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"2023-01-14 11:15:00+01:00",
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"2023-01-14 11:30:00+01:00",
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"2023-01-14 11:45:00+01:00",
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"2023-01-14 12:00:00+01:00",
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"2023-01-14 12:15:00+01:00",
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"2023-01-14 12:30:00+01:00",
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"2023-01-14 12:45:00+01:00",
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"2023-01-14 13:00:00+01:00",
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"2023-01-14 13:15:00+01:00",
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"2023-01-14 13:30:00+01:00",
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"2023-01-14 13:45:00+01:00",
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"2023-01-14 14:00:00+01:00",
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"2023-01-14 14:15:00+01:00",
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"2023-01-14 14:30:00+01:00",
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"2023-01-14 14:45:00+01:00",
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"2023-01-14 15:15:00+01:00",
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"2023-01-14 15:30:00+01:00",
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"2023-01-14 15:45:00+01:00",
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"2023-01-14 16:00:00+01:00",
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"2023-01-14 16:15:00+01:00",
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"2023-01-14 16:30:00+01:00",
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"2023-01-14 16:45:00+01:00",
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"2023-01-14 17:00:00+01:00",
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"2023-01-14 17:15:00+01:00",
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"2023-01-14 17:30:00+01:00",
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"2023-01-14 17:45:00+01:00",
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"2023-01-14 18:00:00+01:00",
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"2023-01-14 18:15:00+01:00",
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"2023-01-14 18:30:00+01:00",
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"2023-01-14 18:45:00+01:00",
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"2023-01-14 19:15:00+01:00",
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"2023-01-14 19:30:00+01:00",
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"2023-01-14 19:45:00+01:00",
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"2023-01-14 20:00:00+01:00",
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"2023-01-14 20:15:00+01:00",
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"2023-01-14 20:30:00+01:00",
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"2023-01-14 20:45:00+01:00",
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"2023-01-14 21:00:00+01:00",
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"2023-01-14 21:15:00+01:00",
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"2023-01-14 21:30:00+01:00",
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"2023-01-14 21:45:00+01:00",
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"2023-01-14 22:00:00+01:00",
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"2023-01-14 22:15:00+01:00",
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"2023-01-14 23:00:00+01:00",
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"2023-01-14 23:15:00+01:00",
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"2023-01-14 23:30:00+01:00",
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"2023-01-14 23:45:00+01:00",
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"2023-01-15 00:00:00+01:00",
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"2023-01-15 00:15:00+01:00",
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"2023-01-15 00:30:00+01:00",
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"2023-01-15 00:45:00+01:00",
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"2023-01-15 01:00:00+01:00",
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"2023-01-15 01:15:00+01:00",
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"2023-01-15 01:30:00+01:00",
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"2023-01-15 01:45:00+01:00",
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"2023-01-15 02:00:00+01:00",
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"2023-01-15 02:15:00+01:00",
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"2023-01-15 02:30:00+01:00",
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"2023-01-15 02:45:00+01:00",
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"2023-01-15 03:00:00+01:00",
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"2023-01-15 03:15:00+01:00",
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"2023-01-15 03:30:00+01:00",
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"2023-01-15 03:45:00+01:00",
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"2023-01-15 04:00:00+01:00",
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"2023-01-15 04:15:00+01:00",
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"2023-01-15 04:30:00+01:00",
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"2023-01-15 04:45:00+01:00",
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"2023-01-15 05:00:00+01:00",
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"2023-01-15 05:15:00+01:00",
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"2023-01-15 05:30:00+01:00",
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"2023-01-15 05:45:00+01:00",
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"2023-01-15 06:00:00+01:00",
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"2023-01-15 06:15:00+01:00",
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"2023-01-15 06:30:00+01:00",
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"2023-01-15 06:45:00+01:00",
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"2023-01-15 07:00:00+01:00",
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"2023-01-15 07:15:00+01:00",
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"2023-01-15 07:30:00+01:00",
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"2023-01-15 07:45:00+01:00",
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"2023-01-15 08:00:00+01:00",
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"2023-01-15 08:15:00+01:00",
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"2023-01-15 08:30:00+01:00",
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"2023-01-15 08:45:00+01:00",
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"2023-01-15 09:00:00+01:00",
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"2023-01-15 09:15:00+01:00",
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"2023-01-15 09:30:00+01:00",
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"2023-01-15 09:45:00+01:00",
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"2023-01-15 10:00:00+01:00",
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"2023-01-15 10:15:00+01:00",
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"2023-01-15 10:30:00+01:00",
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"2023-01-15 10:45:00+01:00",
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"2023-01-15 11:00:00+01:00",
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"2023-01-15 11:15:00+01:00",
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"2023-01-15 11:30:00+01:00",
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"2023-01-15 11:45:00+01:00",
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"2023-01-15 12:00:00+01:00",
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"2023-01-15 12:15:00+01:00",
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"2023-01-15 12:30:00+01:00",
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"2023-01-15 12:45:00+01:00",
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"2023-01-15 13:00:00+01:00",
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"2023-01-15 13:15:00+01:00",
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"2023-01-15 13:30:00+01:00",
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"2023-01-15 13:45:00+01:00",
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"2023-01-15 14:00:00+01:00",
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"2023-01-15 14:15:00+01:00",
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"2023-01-15 14:30:00+01:00",
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"2023-01-15 14:45:00+01:00",
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"2023-01-15 15:00:00+01:00",
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"2023-01-15 15:15:00+01:00",
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"2023-01-15 15:30:00+01:00",
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"2023-01-15 15:45:00+01:00",
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"2023-01-15 16:00:00+01:00",
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"2023-01-15 16:15:00+01:00",
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"2023-01-15 16:30:00+01:00",
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"2023-01-15 16:45:00+01:00",
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"2023-01-15 17:00:00+01:00",
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"2023-01-15 17:15:00+01:00",
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"2023-01-15 17:30:00+01:00",
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"2023-01-15 17:45:00+01:00",
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"2023-01-15 18:00:00+01:00",
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"2023-01-15 18:15:00+01:00",
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"2023-01-15 18:30:00+01:00",
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"2023-01-15 18:45:00+01:00",
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"2023-01-15 19:00:00+01:00",
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"2023-01-15 19:15:00+01:00",
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"2023-01-15 19:30:00+01:00",
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"2023-01-15 19:45:00+01:00",
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"2023-01-15 20:00:00+01:00",
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"2023-01-15 20:15:00+01:00",
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"2023-01-15 20:30:00+01:00",
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"2023-01-15 20:45:00+01:00",
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"2023-01-15 21:00:00+01:00",
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"2023-01-15 21:15:00+01:00",
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"2023-01-15 21:30:00+01:00",
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"2023-01-15 21:45:00+01:00",
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"2023-01-15 22:00:00+01:00",
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"2023-01-15 22:15:00+01:00",
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"2023-01-15 22:30:00+01:00",
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"2023-01-15 22:45:00+01:00",
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"2023-01-15 23:00:00+01:00",
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"2023-01-15 23:15:00+01:00",
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"2023-01-15 23:30:00+01:00",
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"2023-01-15 23:45:00+01:00",
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"2023-01-16 00:00:00+01:00",
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"2023-01-16 00:15:00+01:00",
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"2023-01-16 00:30:00+01:00",
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"2023-01-16 00:45:00+01:00",
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"2023-01-16 01:00:00+01:00",
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"2023-01-16 01:15:00+01:00",
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"2023-01-16 01:30:00+01:00",
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"2023-01-16 01:45:00+01:00",
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"2023-01-16 02:00:00+01:00",
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"2023-01-16 02:15:00+01:00",
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"2023-01-16 02:30:00+01:00",
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"2023-01-16 02:45:00+01:00",
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"2023-01-16 03:00:00+01:00",
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"2023-01-16 03:15:00+01:00",
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"2023-01-16 03:30:00+01:00",
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"2023-01-16 03:45:00+01:00",
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"2023-01-16 04:00:00+01:00",
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"2023-01-16 04:15:00+01:00",
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"2023-01-16 04:30:00+01:00",
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"2023-01-16 04:45:00+01:00",
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"2023-01-16 05:00:00+01:00",
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"2023-01-16 05:15:00+01:00",
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"2023-01-16 05:30:00+01:00",
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"2023-01-16 05:45:00+01:00",
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"2023-01-16 06:00:00+01:00",
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"2023-01-16 06:15:00+01:00",
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"2023-01-16 06:30:00+01:00",
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"2023-01-16 06:45:00+01:00",
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"2023-01-16 07:00:00+01:00",
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"2023-01-16 07:15:00+01:00",
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"2023-01-16 07:30:00+01:00",
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"2023-01-16 07:45:00+01:00",
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"2023-01-16 08:00:00+01:00",
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"2023-01-16 08:15:00+01:00",
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"2023-01-16 08:30:00+01:00",
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"2023-01-16 08:45:00+01:00",
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"2023-01-16 09:00:00+01:00",
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"2023-01-16 09:15:00+01:00",
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"2023-01-16 09:30:00+01:00",
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"2023-01-16 09:45:00+01:00",
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"2023-01-16 10:00:00+01:00",
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"2023-01-16 10:15:00+01:00",
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"2023-01-16 10:30:00+01:00",
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"2023-01-16 10:45:00+01:00",
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"2023-01-16 11:00:00+01:00",
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"2023-01-16 11:15:00+01:00",
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"2023-01-16 11:30:00+01:00",
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"2023-01-16 11:45:00+01:00",
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"2023-01-16 12:00:00+01:00",
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"2023-01-16 12:15:00+01:00",
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"2023-01-16 12:30:00+01:00",
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"2023-01-16 12:45:00+01:00",
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"2023-01-16 13:00:00+01:00",
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"2023-01-16 13:15:00+01:00",
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"2023-01-16 13:30:00+01:00",
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"2023-01-16 13:45:00+01:00",
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"2023-01-16 14:00:00+01:00",
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"2023-01-16 14:15:00+01:00",
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"2023-01-16 14:30:00+01:00",
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"2023-01-16 14:45:00+01:00",
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"2023-01-16 15:00:00+01:00",
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"2023-01-16 15:15:00+01:00",
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"2023-01-16 15:30:00+01:00",
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"2023-01-16 15:45:00+01:00",
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"2023-01-16 16:00:00+01:00",
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"2023-01-16 16:15:00+01:00",
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"2023-01-16 16:30:00+01:00",
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"2023-01-16 16:45:00+01:00",
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"2023-01-16 17:00:00+01:00",
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"2023-01-16 17:15:00+01:00",
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"2023-01-16 17:30:00+01:00",
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"2023-01-16 17:45:00+01:00",
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"2023-01-16 18:00:00+01:00",
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"2023-01-16 18:15:00+01:00",
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"2023-01-16 18:30:00+01:00",
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"2023-01-16 18:45:00+01:00",
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"2023-01-16 19:00:00+01:00",
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"2023-01-16 19:15:00+01:00",
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"2023-01-16 19:30:00+01:00",
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"2023-01-16 19:45:00+01:00",
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"2023-01-16 20:00:00+01:00",
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"2023-01-16 20:15:00+01:00",
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"2023-01-16 20:30:00+01:00",
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"2023-01-16 20:45:00+01:00",
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"2023-01-16 21:00:00+01:00",
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"2023-01-16 21:15:00+01:00",
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"2023-01-16 21:30:00+01:00",
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"2023-01-16 21:45:00+01:00",
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"2023-01-16 22:00:00+01:00",
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"2023-01-16 22:15:00+01:00",
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"2023-01-16 22:30:00+01:00",
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"2023-01-16 22:45:00+01:00",
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"2023-01-16 23:00:00+01:00",
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"2023-01-16 23:15:00+01:00",
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"2023-01-16 23:30:00+01:00",
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"2023-01-16 23:45:00+01:00",
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"2023-01-17 00:00:00+01:00",
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"2023-01-17 00:15:00+01:00",
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"2023-01-17 00:30:00+01:00",
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"2023-01-17 00:45:00+01:00",
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"2023-01-17 01:00:00+01:00",
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"2023-01-17 01:15:00+01:00",
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"2023-01-17 01:30:00+01:00",
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"2023-01-17 01:45:00+01:00",
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"2023-01-17 02:00:00+01:00",
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"2023-01-17 02:15:00+01:00",
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"2023-01-17 02:30:00+01:00",
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"2023-01-17 02:45:00+01:00",
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"2023-01-17 03:00:00+01:00",
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"2023-01-17 03:15:00+01:00",
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"2023-01-17 03:30:00+01:00",
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"2023-01-17 03:45:00+01:00",
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"2023-01-17 04:00:00+01:00",
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"2023-01-17 04:15:00+01:00",
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"2023-01-17 04:30:00+01:00",
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"2023-01-17 04:45:00+01:00",
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"2023-01-17 05:00:00+01:00",
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"2023-01-17 05:15:00+01:00",
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"2023-01-17 05:30:00+01:00",
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"2023-01-17 05:45:00+01:00",
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"2023-01-17 06:00:00+01:00",
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"2023-01-17 06:15:00+01:00",
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"2023-01-17 06:30:00+01:00",
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"2023-01-17 06:45:00+01:00",
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"2023-01-17 07:00:00+01:00",
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"2023-01-17 07:15:00+01:00",
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"2023-01-17 07:30:00+01:00",
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"2023-01-17 07:45:00+01:00",
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"2023-01-17 08:00:00+01:00",
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"2023-01-17 08:15:00+01:00",
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"2023-01-17 08:30:00+01:00",
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"2023-01-17 08:45:00+01:00",
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"2023-01-17 09:00:00+01:00",
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"2023-01-17 09:15:00+01:00",
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"2023-01-17 09:30:00+01:00",
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"2023-01-17 09:45:00+01:00",
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"2023-01-17 10:00:00+01:00",
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"2023-01-17 10:15:00+01:00",
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"2023-01-17 10:30:00+01:00",
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"2023-01-17 10:45:00+01:00",
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"2023-01-17 11:00:00+01:00",
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"2023-01-17 11:15:00+01:00",
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"2023-01-17 11:30:00+01:00",
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"2023-01-17 11:45:00+01:00",
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"2023-01-17 12:00:00+01:00",
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"2023-01-17 12:15:00+01:00",
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"2023-01-17 12:30:00+01:00",
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"2023-01-17 12:45:00+01:00",
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"2023-01-17 13:00:00+01:00",
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"2023-01-17 13:15:00+01:00",
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"2023-01-17 13:30:00+01:00",
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"2023-01-17 13:45:00+01:00",
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"2023-01-17 14:00:00+01:00",
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"2023-01-17 14:15:00+01:00",
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"2023-01-17 14:30:00+01:00",
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"2023-01-17 14:45:00+01:00",
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"2023-01-17 15:00:00+01:00",
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"2023-01-17 15:15:00+01:00",
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"2023-01-17 15:30:00+01:00",
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"2023-01-17 15:45:00+01:00",
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"2023-01-17 16:00:00+01:00",
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"2023-01-17 16:15:00+01:00",
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"2023-01-17 16:30:00+01:00",
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"2023-01-17 16:45:00+01:00",
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"2023-01-17 17:00:00+01:00",
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"2023-01-17 17:15:00+01:00",
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"2023-01-17 17:30:00+01:00",
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"2023-01-17 17:45:00+01:00",
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"2023-01-17 18:00:00+01:00",
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"2023-01-17 18:15:00+01:00",
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"2023-01-17 18:30:00+01:00",
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"2023-01-17 18:45:00+01:00",
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"2023-01-17 19:00:00+01:00",
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"2023-01-17 19:15:00+01:00",
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"2023-01-17 19:30:00+01:00",
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"2023-01-17 19:45:00+01:00",
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"2023-01-17 20:00:00+01:00",
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"2023-01-17 20:15:00+01:00",
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"2023-01-17 20:30:00+01:00",
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"2023-01-17 20:45:00+01:00",
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"2023-01-17 21:00:00+01:00",
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"2023-01-17 21:15:00+01:00",
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"2023-01-17 21:30:00+01:00",
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"2023-01-17 21:45:00+01:00",
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"2023-01-17 22:00:00+01:00",
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"2023-01-17 22:15:00+01:00",
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"2023-01-17 22:30:00+01:00",
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"2023-01-17 22:45:00+01:00",
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"2023-01-17 23:00:00+01:00",
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"2023-01-17 23:15:00+01:00",
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"2023-01-17 23:30:00+01:00",
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"2023-01-17 23:45:00+01:00",
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"2023-01-18 00:00:00+01:00",
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"2023-01-18 00:15:00+01:00",
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"2023-01-18 00:30:00+01:00",
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"2023-01-18 00:45:00+01:00",
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"2023-01-18 01:00:00+01:00",
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"2023-01-18 01:15:00+01:00",
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"2023-01-18 01:30:00+01:00",
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"2023-01-18 01:45:00+01:00",
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"2023-01-18 02:00:00+01:00",
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"2023-01-18 02:15:00+01:00",
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"2023-01-18 02:30:00+01:00",
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"2023-01-18 02:45:00+01:00",
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"2023-01-18 03:00:00+01:00",
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"2023-01-18 03:15:00+01:00",
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"2023-01-18 03:30:00+01:00",
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"2023-01-18 03:45:00+01:00",
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"2023-01-18 04:00:00+01:00",
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"2023-01-18 04:15:00+01:00",
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"2023-01-18 04:30:00+01:00",
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"2023-01-18 04:45:00+01:00",
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"2023-01-18 05:00:00+01:00",
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"2023-01-18 05:15:00+01:00",
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"2023-01-18 05:30:00+01:00",
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"2023-01-18 05:45:00+01:00",
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"2023-01-18 06:00:00+01:00",
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"2023-01-18 06:15:00+01:00",
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"2023-01-18 06:30:00+01:00",
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"2023-01-18 06:45:00+01:00",
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"2023-01-18 07:00:00+01:00",
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"2023-01-18 07:15:00+01:00",
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"2023-01-18 07:30:00+01:00",
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"2023-01-18 07:45:00+01:00",
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"2023-01-18 08:00:00+01:00",
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"2023-01-18 08:15:00+01:00",
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"2023-01-18 08:30:00+01:00",
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"2023-01-18 08:45:00+01:00",
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"2023-01-18 09:00:00+01:00",
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"2023-01-18 09:15:00+01:00",
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"2023-01-18 09:30:00+01:00",
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"2023-01-18 09:45:00+01:00",
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"2023-01-18 10:00:00+01:00",
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"2023-01-18 10:15:00+01:00",
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"2023-01-18 10:30:00+01:00",
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"2023-01-18 10:45:00+01:00",
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"2023-01-18 11:00:00+01:00",
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"2023-01-18 11:15:00+01:00",
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"2023-01-18 11:30:00+01:00",
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"2023-01-18 11:45:00+01:00",
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"2023-01-18 12:00:00+01:00",
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"2023-01-18 12:15:00+01:00",
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"2023-01-18 12:30:00+01:00",
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"2023-01-18 12:45:00+01:00",
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"2023-01-18 13:00:00+01:00",
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"2023-01-18 13:15:00+01:00",
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"2023-01-18 13:30:00+01:00",
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"2023-01-18 13:45:00+01:00",
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"2023-01-18 14:00:00+01:00",
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"2023-01-18 14:15:00+01:00",
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"2023-01-18 14:30:00+01:00",
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"2023-01-18 14:45:00+01:00",
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"2023-01-18 15:00:00+01:00",
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"2023-01-18 15:15:00+01:00",
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"2023-01-18 15:30:00+01:00",
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"2023-01-18 15:45:00+01:00",
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"2023-01-18 16:00:00+01:00",
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"2023-01-18 16:15:00+01:00",
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"2023-01-18 16:30:00+01:00",
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"2023-01-18 16:45:00+01:00",
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"2023-01-18 17:00:00+01:00",
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"2023-01-18 17:15:00+01:00",
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"2023-01-18 17:30:00+01:00",
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"2023-01-18 17:45:00+01:00",
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"2023-01-18 18:00:00+01:00",
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"2023-01-18 18:15:00+01:00",
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"2023-01-18 18:30:00+01:00",
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"2023-01-18 18:45:00+01:00",
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"2023-01-18 19:00:00+01:00",
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"2023-01-18 19:15:00+01:00",
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"2023-01-18 19:30:00+01:00",
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"2023-01-18 19:45:00+01:00",
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"2023-01-18 20:00:00+01:00",
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"2023-01-18 20:15:00+01:00",
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"2023-01-18 20:30:00+01:00",
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"2023-01-18 20:45:00+01:00",
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"2023-01-18 21:00:00+01:00",
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"2023-01-18 21:15:00+01:00",
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"2023-01-18 21:30:00+01:00",
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"2023-01-18 21:45:00+01:00",
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"2023-01-18 22:00:00+01:00",
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"2023-01-18 22:15:00+01:00",
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"2023-01-18 22:30:00+01:00",
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"2023-01-18 22:45:00+01:00",
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"2023-01-18 23:00:00+01:00",
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"2023-01-18 23:15:00+01:00",
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"2023-01-18 23:30:00+01:00",
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"2023-01-18 23:45:00+01:00",
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"2023-01-19 00:00:00+01:00",
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"2023-01-19 00:15:00+01:00",
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"2023-01-19 00:30:00+01:00",
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"2023-01-19 00:45:00+01:00",
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"2023-01-19 01:00:00+01:00",
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"2023-01-19 01:15:00+01:00",
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"2023-01-19 01:30:00+01:00",
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"2023-01-19 01:45:00+01:00",
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"2023-01-19 02:00:00+01:00",
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"2023-01-19 02:15:00+01:00",
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"2023-01-19 02:30:00+01:00",
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"2023-01-19 02:45:00+01:00",
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"2023-01-19 03:00:00+01:00",
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"2023-01-19 03:15:00+01:00",
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"2023-01-19 03:30:00+01:00",
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"2023-01-19 03:45:00+01:00",
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"2023-01-19 04:00:00+01:00",
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"2023-01-19 04:15:00+01:00",
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"2023-01-19 04:30:00+01:00",
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"2023-01-19 04:45:00+01:00",
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"2023-01-19 05:00:00+01:00",
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"2023-01-19 05:15:00+01:00",
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"2023-01-19 05:30:00+01:00",
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"2023-01-19 05:45:00+01:00",
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"2023-01-19 06:00:00+01:00",
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"2023-01-19 06:15:00+01:00",
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"2023-01-19 06:30:00+01:00",
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"2023-01-19 06:45:00+01:00",
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"2023-01-19 07:00:00+01:00",
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"2023-01-19 07:15:00+01:00",
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"2023-01-19 07:30:00+01:00",
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"2023-01-19 07:45:00+01:00",
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"2023-01-19 08:00:00+01:00",
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"2023-01-19 08:15:00+01:00",
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"2023-01-19 08:30:00+01:00",
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"2023-01-19 08:45:00+01:00",
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"2023-01-19 09:00:00+01:00",
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"2023-01-19 09:15:00+01:00",
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"2023-01-19 09:30:00+01:00",
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"2023-01-19 09:45:00+01:00",
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"2023-01-19 10:00:00+01:00",
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"2023-01-19 10:15:00+01:00",
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"2023-01-19 10:30:00+01:00",
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"2023-01-19 10:45:00+01:00",
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"2023-01-19 11:00:00+01:00",
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"2023-01-19 11:15:00+01:00",
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"2023-01-19 11:30:00+01:00",
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"2023-01-19 11:45:00+01:00",
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"2023-01-19 12:00:00+01:00",
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"2023-01-19 12:15:00+01:00",
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"2023-01-19 12:30:00+01:00",
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"2023-01-19 12:45:00+01:00",
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"2023-01-19 13:00:00+01:00",
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"2023-01-19 13:15:00+01:00",
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"2023-01-19 13:30:00+01:00",
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"2023-01-19 13:45:00+01:00",
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"2023-01-19 14:00:00+01:00",
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"2023-01-19 14:15:00+01:00",
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"2023-01-19 14:30:00+01:00",
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"2023-01-19 14:45:00+01:00",
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"2023-01-19 15:00:00+01:00",
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"2023-01-19 15:15:00+01:00",
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"2023-01-19 15:30:00+01:00",
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"2023-01-19 15:45:00+01:00",
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"2023-01-19 16:00:00+01:00",
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"2023-01-19 16:15:00+01:00",
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"2023-01-19 16:30:00+01:00",
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"2023-01-19 16:45:00+01:00",
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"2023-01-19 17:00:00+01:00",
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"2023-01-19 17:15:00+01:00",
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"2023-01-19 17:30:00+01:00",
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"2023-01-19 17:45:00+01:00",
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"2023-01-19 18:00:00+01:00",
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"2023-01-19 18:15:00+01:00",
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"2023-01-19 18:30:00+01:00",
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"2023-01-19 18:45:00+01:00",
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"2023-01-19 19:00:00+01:00",
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"2023-01-19 19:15:00+01:00",
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"2023-01-19 19:30:00+01:00",
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"2023-01-19 19:45:00+01:00",
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"2023-01-19 20:00:00+01:00",
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"2023-01-19 20:15:00+01:00",
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"2023-01-19 20:30:00+01:00",
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"2023-01-19 20:45:00+01:00",
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"2023-01-19 21:00:00+01:00",
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"2023-01-19 21:15:00+01:00",
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"2023-01-19 21:30:00+01:00",
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"2023-01-19 21:45:00+01:00",
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"2023-01-19 22:00:00+01:00",
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"2023-01-19 22:15:00+01:00",
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"2023-01-19 22:30:00+01:00",
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"2023-01-19 22:45:00+01:00",
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"2023-01-19 23:00:00+01:00",
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"2023-01-19 23:15:00+01:00",
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"2023-01-19 23:30:00+01:00",
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"2023-01-19 23:45:00+01:00",
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"2023-01-20 00:00:00+01:00",
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"2023-01-20 00:15:00+01:00",
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"2023-01-20 00:30:00+01:00",
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"2023-01-20 00:45:00+01:00",
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"2023-01-20 01:00:00+01:00",
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"2023-01-20 01:15:00+01:00",
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"2023-01-20 01:30:00+01:00",
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"2023-01-20 01:45:00+01:00",
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"2023-01-20 02:00:00+01:00",
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"2023-01-20 02:15:00+01:00",
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"2023-01-20 02:30:00+01:00",
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"2023-01-20 02:45:00+01:00",
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"2023-01-20 03:00:00+01:00",
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"2023-01-20 03:15:00+01:00",
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"2023-01-20 03:30:00+01:00",
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"2023-01-20 03:45:00+01:00",
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"2023-01-20 04:00:00+01:00",
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"2023-01-20 04:15:00+01:00",
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"2023-01-20 04:30:00+01:00",
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"2023-01-20 04:45:00+01:00",
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"2023-01-20 05:00:00+01:00",
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"2023-01-20 05:15:00+01:00",
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"2023-01-20 05:30:00+01:00",
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"2023-01-20 05:45:00+01:00",
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"2023-01-20 06:00:00+01:00",
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"2023-01-20 06:15:00+01:00",
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"2023-01-20 06:30:00+01:00",
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"2023-01-20 06:45:00+01:00",
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"2023-01-20 07:00:00+01:00",
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"2023-01-20 07:15:00+01:00",
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"2023-01-20 07:30:00+01:00",
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"2023-01-20 07:45:00+01:00",
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"2023-01-20 08:00:00+01:00",
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"2023-01-20 08:15:00+01:00",
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"2023-01-20 08:30:00+01:00",
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"2023-01-20 08:45:00+01:00",
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"2023-01-20 09:00:00+01:00",
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"2023-01-20 09:15:00+01:00",
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"2023-01-20 09:30:00+01:00",
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"2023-01-20 09:45:00+01:00",
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"2023-01-20 10:00:00+01:00",
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"2023-01-20 10:15:00+01:00",
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"2023-01-20 10:30:00+01:00",
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"2023-01-20 10:45:00+01:00",
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"2023-01-20 11:00:00+01:00",
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"2023-01-20 11:15:00+01:00",
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"2023-01-20 11:30:00+01:00",
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"2023-01-20 11:45:00+01:00",
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"2023-01-20 12:00:00+01:00",
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"2023-01-20 12:15:00+01:00",
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"2023-01-20 12:30:00+01:00",
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"2023-01-20 12:45:00+01:00",
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"2023-01-20 13:00:00+01:00",
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"2023-01-20 13:15:00+01:00",
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"2023-01-20 13:30:00+01:00",
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"2023-01-20 13:45:00+01:00",
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"2023-01-20 14:00:00+01:00",
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"2023-01-20 14:15:00+01:00",
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"2023-01-20 14:30:00+01:00",
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"2023-01-20 14:45:00+01:00",
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"2023-01-20 15:00:00+01:00",
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"2023-01-20 15:15:00+01:00",
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"2023-01-20 15:30:00+01:00",
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"2023-01-20 15:45:00+01:00",
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"2023-01-20 16:00:00+01:00",
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"2023-01-20 16:15:00+01:00",
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"2023-01-20 16:30:00+01:00",
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"2023-01-20 16:45:00+01:00",
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"2023-01-20 17:00:00+01:00",
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"2023-01-20 17:15:00+01:00",
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"2023-01-20 17:30:00+01:00",
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"2023-01-20 17:45:00+01:00",
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"2023-01-20 18:00:00+01:00",
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"2023-01-20 18:15:00+01:00",
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"2023-01-20 18:30:00+01:00",
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"2023-01-20 18:45:00+01:00",
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"2023-01-20 19:00:00+01:00",
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"2023-01-20 19:15:00+01:00",
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"2023-01-20 19:30:00+01:00",
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"2023-01-20 19:45:00+01:00",
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"2023-01-20 20:00:00+01:00",
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"2023-01-20 20:15:00+01:00",
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"2023-01-20 20:30:00+01:00",
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"2023-01-20 20:45:00+01:00",
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"2023-01-20 21:00:00+01:00",
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"2023-01-20 21:15:00+01:00",
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"2023-01-20 21:30:00+01:00",
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"2023-01-20 21:45:00+01:00",
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"2023-01-20 22:00:00+01:00",
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"2023-01-20 22:15:00+01:00",
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"2023-01-20 22:30:00+01:00",
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"2023-01-20 22:45:00+01:00",
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"2023-01-20 23:00:00+01:00",
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"2023-01-20 23:15:00+01:00",
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"2023-01-20 23:30:00+01:00",
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"2023-01-20 23:45:00+01:00",
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"2023-01-21 00:00:00+01:00",
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"2023-01-21 00:15:00+01:00",
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"2023-01-21 00:30:00+01:00",
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"2023-01-21 00:45:00+01:00",
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"2023-01-21 01:00:00+01:00",
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"2023-01-21 01:15:00+01:00",
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"2023-01-21 01:30:00+01:00",
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"2023-01-21 01:45:00+01:00",
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"2023-01-21 02:00:00+01:00",
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"2023-01-21 02:15:00+01:00",
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"2023-01-21 02:30:00+01:00",
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"2023-01-21 02:45:00+01:00",
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"2023-01-21 03:00:00+01:00",
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"2023-01-21 03:15:00+01:00",
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"2023-01-21 03:30:00+01:00",
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"2023-01-21 03:45:00+01:00",
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"2023-01-21 04:15:00+01:00",
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"2023-01-21 04:30:00+01:00",
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"2023-01-21 04:45:00+01:00",
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"2023-01-21 05:15:00+01:00",
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"2023-01-21 06:15:00+01:00",
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"2023-01-21 07:15:00+01:00",
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"2023-01-21 07:45:00+01:00",
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"2023-01-21 08:15:00+01:00",
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"2023-01-21 08:45:00+01:00",
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"2023-01-21 09:15:00+01:00",
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"2023-01-21 09:30:00+01:00",
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"2023-01-21 10:15:00+01:00",
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"2023-01-21 11:15:00+01:00",
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"2023-01-21 11:30:00+01:00",
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"2023-01-21 12:15:00+01:00",
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"2023-01-21 12:30:00+01:00",
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"2023-01-21 12:45:00+01:00",
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"2023-01-21 13:15:00+01:00",
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"2023-01-21 17:15:00+01:00",
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"2023-01-21 20:15:00+01:00",
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"2023-01-21 20:30:00+01:00",
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"2023-01-21 20:45:00+01:00",
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"2023-01-21 21:15:00+01:00",
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"2023-01-21 23:15:00+01:00",
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"2023-01-22 00:15:00+01:00",
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"2023-01-22 01:15:00+01:00",
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"2023-01-22 02:15:00+01:00",
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"2023-01-22 03:15:00+01:00",
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"2023-01-22 03:30:00+01:00",
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"2023-01-22 03:45:00+01:00",
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"2023-01-22 04:15:00+01:00",
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"2023-01-22 04:45:00+01:00",
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"2023-01-22 05:15:00+01:00",
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"2023-01-22 05:30:00+01:00",
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"2023-01-22 06:15:00+01:00",
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"2023-01-22 06:45:00+01:00",
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"2023-01-22 07:15:00+01:00",
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"2023-01-22 07:30:00+01:00",
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"2023-01-22 07:45:00+01:00",
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"2023-01-22 08:15:00+01:00",
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"2023-01-22 08:30:00+01:00",
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"2023-01-22 09:15:00+01:00",
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"2023-01-22 09:30:00+01:00",
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"2023-01-22 09:45:00+01:00",
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"2023-01-22 10:15:00+01:00",
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"2023-01-22 10:30:00+01:00",
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"2023-01-22 10:45:00+01:00",
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"2023-01-22 11:15:00+01:00",
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"2023-01-22 11:30:00+01:00",
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"2023-01-22 11:45:00+01:00",
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"2023-01-22 12:00:00+01:00",
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"2023-01-22 12:15:00+01:00",
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"2023-01-22 12:30:00+01:00",
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"2023-01-22 12:45:00+01:00",
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"2023-01-22 13:15:00+01:00",
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"2023-01-22 13:30:00+01:00",
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"2023-01-22 13:45:00+01:00",
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"2023-01-22 14:15:00+01:00",
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"2023-01-22 14:30:00+01:00",
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"2023-01-22 14:45:00+01:00",
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"2023-01-22 15:00:00+01:00",
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"2023-01-22 15:15:00+01:00",
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"2023-01-22 15:30:00+01:00",
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"2023-01-22 15:45:00+01:00",
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"2023-01-22 16:15:00+01:00",
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"2023-01-22 16:30:00+01:00",
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"2023-01-22 16:45:00+01:00",
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"2023-01-22 17:00:00+01:00",
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"2023-01-22 17:15:00+01:00",
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"2023-01-22 17:30:00+01:00",
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"2023-01-22 17:45:00+01:00",
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"2023-01-22 18:00:00+01:00",
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"2023-01-22 18:15:00+01:00",
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"2023-01-22 18:30:00+01:00",
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"2023-01-22 18:45:00+01:00",
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"2023-01-22 19:00:00+01:00",
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"2023-01-22 19:15:00+01:00",
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"2023-01-22 19:30:00+01:00",
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"2023-01-22 19:45:00+01:00",
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"2023-01-22 20:00:00+01:00",
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"2023-01-22 20:15:00+01:00",
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"2023-01-22 20:30:00+01:00",
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"2023-01-22 20:45:00+01:00",
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"2023-01-22 21:00:00+01:00",
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"2023-01-22 21:15:00+01:00",
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"2023-01-22 21:30:00+01:00",
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"2023-01-22 21:45:00+01:00",
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"2023-01-22 22:00:00+01:00",
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"2023-01-22 22:15:00+01:00",
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"2023-01-22 22:30:00+01:00",
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"2023-01-22 22:45:00+01:00",
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"2023-01-22 23:00:00+01:00",
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"2023-01-22 23:15:00+01:00",
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"2023-01-22 23:30:00+01:00",
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"2023-01-22 23:45:00+01:00",
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"2023-01-23 00:00:00+01:00",
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"2023-01-23 00:15:00+01:00",
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"2023-01-23 00:30:00+01:00",
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"2023-01-23 00:45:00+01:00",
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"2023-01-23 01:00:00+01:00",
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"2023-01-23 01:15:00+01:00",
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"2023-01-23 01:30:00+01:00",
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"2023-01-23 01:45:00+01:00",
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"2023-01-23 02:00:00+01:00",
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"2023-01-23 02:15:00+01:00",
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"2023-01-23 02:30:00+01:00",
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"2023-01-23 02:45:00+01:00",
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"2023-01-23 03:00:00+01:00",
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"2023-01-23 03:15:00+01:00",
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"2023-01-23 03:30:00+01:00",
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"2023-01-23 03:45:00+01:00",
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"2023-01-23 04:00:00+01:00",
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"2023-01-23 04:15:00+01:00",
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"2023-01-23 04:30:00+01:00",
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"2023-01-23 04:45:00+01:00",
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"2023-01-23 05:00:00+01:00",
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"2023-01-23 05:15:00+01:00",
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"2023-01-23 05:30:00+01:00",
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"2023-01-23 05:45:00+01:00",
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"2023-01-23 06:00:00+01:00",
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"2023-01-23 06:15:00+01:00",
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"2023-01-23 06:30:00+01:00",
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"2023-01-23 06:45:00+01:00",
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"2023-01-23 07:00:00+01:00",
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"2023-01-23 07:15:00+01:00",
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"2023-01-23 07:30:00+01:00",
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"2023-01-23 07:45:00+01:00",
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"2023-01-23 08:00:00+01:00",
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"2023-01-23 08:15:00+01:00",
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"2023-01-23 08:30:00+01:00",
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"2023-01-23 08:45:00+01:00",
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"2023-01-23 09:00:00+01:00",
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"2023-01-23 09:15:00+01:00",
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"2023-01-23 09:30:00+01:00",
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"2023-01-23 09:45:00+01:00",
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"2023-01-23 10:00:00+01:00",
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"2023-01-23 10:15:00+01:00",
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"2023-01-23 10:30:00+01:00",
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"2023-01-23 10:45:00+01:00",
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"2023-01-23 11:00:00+01:00",
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"2023-01-23 11:15:00+01:00",
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"2023-01-23 11:30:00+01:00",
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"2023-01-23 11:45:00+01:00",
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"2023-01-23 12:00:00+01:00",
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"2023-01-23 12:15:00+01:00",
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"2023-01-23 12:30:00+01:00",
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"2023-01-23 12:45:00+01:00",
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"2023-01-23 13:00:00+01:00",
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"2023-01-23 13:15:00+01:00",
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"2023-01-23 13:30:00+01:00",
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"2023-01-23 13:45:00+01:00",
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"2023-01-23 14:00:00+01:00",
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"2023-01-23 14:15:00+01:00",
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"2023-01-23 14:30:00+01:00",
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"2023-01-23 14:45:00+01:00",
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"2023-01-23 15:00:00+01:00",
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"2023-01-23 15:15:00+01:00",
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"2023-01-23 15:30:00+01:00",
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"2023-01-23 15:45:00+01:00",
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"2023-01-23 16:00:00+01:00",
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"2023-01-23 16:15:00+01:00",
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"2023-01-23 16:30:00+01:00",
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"2023-01-23 16:45:00+01:00",
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"2023-01-23 17:00:00+01:00",
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"2023-01-23 17:15:00+01:00",
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"2023-01-23 17:30:00+01:00",
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"2023-01-23 17:45:00+01:00",
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"2023-01-23 18:00:00+01:00",
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"2023-01-23 18:15:00+01:00",
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"2023-01-23 18:30:00+01:00",
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"2023-01-23 18:45:00+01:00",
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"2023-01-23 19:00:00+01:00",
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"2023-01-23 19:15:00+01:00",
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"2023-01-23 19:30:00+01:00",
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"2023-01-23 19:45:00+01:00",
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"2023-01-23 20:00:00+01:00",
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"2023-01-23 20:15:00+01:00",
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"2023-01-23 20:30:00+01:00",
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"2023-01-23 20:45:00+01:00",
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"2023-01-23 21:00:00+01:00",
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"2023-01-23 21:15:00+01:00",
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"2023-01-23 21:30:00+01:00",
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"2023-01-23 21:45:00+01:00",
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"2023-01-23 22:00:00+01:00",
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"2023-01-23 22:15:00+01:00",
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"2023-01-23 22:30:00+01:00",
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"2023-01-23 22:45:00+01:00",
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"2023-01-23 23:00:00+01:00",
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"2023-01-23 23:15:00+01:00",
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"2023-01-23 23:30:00+01:00",
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"2023-01-23 23:45:00+01:00",
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"2023-01-24 00:00:00+01:00",
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"2023-01-24 00:15:00+01:00",
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"2023-01-24 00:30:00+01:00",
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"2023-01-24 00:45:00+01:00",
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"2023-01-24 01:00:00+01:00",
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"2023-01-24 01:15:00+01:00",
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"2023-01-24 01:30:00+01:00",
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"2023-01-24 01:45:00+01:00",
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"2023-01-24 02:00:00+01:00",
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"2023-01-24 02:15:00+01:00",
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"2023-01-24 02:30:00+01:00",
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"2023-01-24 02:45:00+01:00",
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"2023-01-24 03:00:00+01:00",
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"2023-01-24 03:15:00+01:00",
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"2023-01-24 03:30:00+01:00",
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"2023-01-24 03:45:00+01:00",
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"2023-01-24 04:00:00+01:00",
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"2023-01-24 04:15:00+01:00",
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"2023-01-24 04:30:00+01:00",
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"2023-01-24 04:45:00+01:00",
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"2023-01-24 05:00:00+01:00",
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"2023-01-24 05:15:00+01:00",
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"2023-01-24 05:30:00+01:00",
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"2023-01-24 05:45:00+01:00",
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"2023-01-24 06:00:00+01:00",
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"2023-01-24 06:15:00+01:00",
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"2023-01-24 06:30:00+01:00",
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"2023-01-24 06:45:00+01:00",
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"2023-01-24 07:00:00+01:00",
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"2023-01-24 07:15:00+01:00",
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"2023-01-24 07:30:00+01:00",
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"2023-01-24 07:45:00+01:00",
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"2023-01-24 08:00:00+01:00",
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"2023-01-24 08:15:00+01:00",
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"2023-01-24 08:30:00+01:00",
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"2023-01-24 08:45:00+01:00",
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"2023-01-24 09:00:00+01:00",
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"2023-01-24 09:15:00+01:00",
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"2023-01-24 09:30:00+01:00",
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"2023-01-24 09:45:00+01:00",
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"2023-01-24 10:00:00+01:00",
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"2023-01-24 10:15:00+01:00",
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"2023-01-24 10:30:00+01:00",
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"2023-01-24 10:45:00+01:00",
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"2023-01-24 11:00:00+01:00",
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"2023-01-24 11:15:00+01:00",
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"2023-01-24 11:30:00+01:00",
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"2023-01-24 11:45:00+01:00",
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"2023-01-24 12:00:00+01:00",
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"2023-01-24 12:15:00+01:00",
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"2023-01-24 12:30:00+01:00",
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"2023-01-24 12:45:00+01:00",
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"2023-01-27 22:45:00+01:00",
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"2023-01-27 23:00:00+01:00",
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"2023-01-27 23:15:00+01:00",
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"2023-01-27 23:30:00+01:00",
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"2023-01-27 23:45:00+01:00",
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"2023-01-28 00:00:00+01:00",
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"2023-01-28 00:15:00+01:00",
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"2023-01-28 00:30:00+01:00",
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"2023-01-28 00:45:00+01:00",
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"2023-01-28 01:00:00+01:00",
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"2023-01-28 01:15:00+01:00",
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"2023-01-28 01:30:00+01:00",
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"2023-01-28 01:45:00+01:00",
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"2023-01-28 02:00:00+01:00",
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"2023-01-28 02:15:00+01:00",
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"2023-01-28 02:30:00+01:00",
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"2023-01-28 02:45:00+01:00",
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"2023-01-28 03:00:00+01:00",
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"2023-01-28 03:15:00+01:00",
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"2023-01-28 03:30:00+01:00",
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"2023-01-28 03:45:00+01:00",
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"2023-01-28 04:00:00+01:00",
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"2023-01-28 04:15:00+01:00",
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"2023-01-28 04:30:00+01:00",
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"2023-01-28 04:45:00+01:00",
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"2023-01-28 05:00:00+01:00",
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"2023-01-28 05:15:00+01:00",
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"2023-01-28 05:30:00+01:00",
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"2023-01-28 05:45:00+01:00",
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"2023-01-28 06:00:00+01:00",
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"2023-01-28 06:15:00+01:00",
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"2023-01-28 06:30:00+01:00",
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"2023-01-28 06:45:00+01:00",
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"2023-01-28 07:15:00+01:00",
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"2023-01-28 07:30:00+01:00",
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"2023-01-28 07:45:00+01:00",
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"2023-01-28 08:00:00+01:00",
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"2023-01-28 08:15:00+01:00",
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"2023-01-28 08:30:00+01:00",
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"2023-01-28 08:45:00+01:00",
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"2023-01-28 09:00:00+01:00",
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"2023-01-28 09:15:00+01:00",
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"2023-01-28 09:30:00+01:00",
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"2023-01-28 09:45:00+01:00",
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"2023-01-28 10:00:00+01:00",
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"2023-01-28 10:15:00+01:00",
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"2023-01-28 10:30:00+01:00",
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"2023-01-28 10:45:00+01:00",
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"2023-01-28 11:00:00+01:00",
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"2023-01-28 11:15:00+01:00",
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"2023-01-28 11:30:00+01:00",
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"2023-01-28 11:45:00+01:00",
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"2023-01-28 12:00:00+01:00",
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"2023-01-28 12:15:00+01:00",
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"2023-01-28 12:30:00+01:00",
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"2023-01-28 12:45:00+01:00",
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"2023-01-28 13:00:00+01:00",
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"2023-01-28 13:15:00+01:00",
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"2023-01-28 13:30:00+01:00",
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"2023-01-28 13:45:00+01:00",
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"2023-01-28 14:00:00+01:00",
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"2023-01-28 14:15:00+01:00",
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"2023-01-28 14:30:00+01:00",
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"2023-01-28 14:45:00+01:00",
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"2023-01-28 15:15:00+01:00",
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"2023-01-28 15:30:00+01:00",
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"2023-01-28 15:45:00+01:00",
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"2023-01-28 16:00:00+01:00",
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"2023-01-28 16:15:00+01:00",
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"2023-01-28 16:30:00+01:00",
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"2023-01-28 16:45:00+01:00",
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"2023-01-28 17:00:00+01:00",
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"2023-01-28 17:15:00+01:00",
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"2023-01-28 17:30:00+01:00",
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"2023-01-28 17:45:00+01:00",
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"2023-01-28 18:00:00+01:00",
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"2023-01-28 18:15:00+01:00",
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"2023-01-28 18:30:00+01:00",
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"2023-01-28 18:45:00+01:00",
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"2023-01-28 19:00:00+01:00",
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"2023-01-28 19:15:00+01:00",
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"2023-01-28 19:30:00+01:00",
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"2023-01-28 19:45:00+01:00",
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"2023-01-28 20:00:00+01:00",
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"2023-01-28 20:15:00+01:00",
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"2023-01-28 20:30:00+01:00",
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"2023-01-28 20:45:00+01:00",
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"2023-01-28 21:00:00+01:00",
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"2023-01-28 21:15:00+01:00",
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"2023-01-28 21:30:00+01:00",
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"2023-01-28 21:45:00+01:00",
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"2023-01-28 22:00:00+01:00",
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"2023-01-28 22:15:00+01:00",
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"2023-01-28 22:30:00+01:00",
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"2023-01-28 22:45:00+01:00",
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"2023-01-28 23:00:00+01:00",
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"2023-01-28 23:15:00+01:00",
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"2023-01-28 23:30:00+01:00",
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"2023-01-28 23:45:00+01:00",
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"2023-01-29 00:00:00+01:00",
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"2023-01-29 00:15:00+01:00",
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"2023-01-29 00:30:00+01:00",
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"2023-01-29 00:45:00+01:00",
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"2023-01-29 01:00:00+01:00",
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"2023-01-29 01:15:00+01:00",
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"2023-01-29 01:30:00+01:00",
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"2023-01-29 01:45:00+01:00",
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"2023-01-29 02:00:00+01:00",
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"2023-01-29 02:15:00+01:00",
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"2023-01-29 02:30:00+01:00",
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"2023-01-29 02:45:00+01:00",
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"2023-01-29 03:00:00+01:00",
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"2023-01-29 03:15:00+01:00",
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"2023-01-29 03:30:00+01:00",
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"2023-01-29 03:45:00+01:00",
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"2023-01-29 04:00:00+01:00",
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"2023-01-29 04:15:00+01:00",
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"2023-01-29 04:30:00+01:00",
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"2023-01-29 04:45:00+01:00",
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"2023-01-29 05:00:00+01:00",
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"2023-01-29 05:15:00+01:00",
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"2023-01-29 05:30:00+01:00",
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"2023-01-29 05:45:00+01:00",
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"2023-01-29 06:00:00+01:00",
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"2023-01-29 06:15:00+01:00",
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"2023-01-29 06:30:00+01:00",
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"2023-01-29 06:45:00+01:00",
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"2023-01-29 07:00:00+01:00",
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"2023-01-29 07:15:00+01:00",
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"2023-01-29 07:30:00+01:00",
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"2023-01-29 07:45:00+01:00",
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"2023-01-29 08:00:00+01:00",
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"2023-01-29 08:15:00+01:00",
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"2023-01-29 08:30:00+01:00",
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"2023-01-29 08:45:00+01:00",
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"2023-01-29 09:00:00+01:00",
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"2023-01-29 09:15:00+01:00",
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"2023-01-29 09:30:00+01:00",
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"2023-01-29 09:45:00+01:00",
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"2023-01-29 10:00:00+01:00",
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"2023-01-29 10:15:00+01:00",
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"2023-01-29 10:30:00+01:00",
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"2023-01-29 10:45:00+01:00",
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"2023-01-29 11:00:00+01:00",
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"2023-01-29 11:15:00+01:00",
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"2023-01-29 11:30:00+01:00",
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"2023-01-29 11:45:00+01:00",
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"2023-01-29 12:00:00+01:00",
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"2023-01-29 12:15:00+01:00",
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"2023-01-29 12:30:00+01:00",
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"2023-01-29 12:45:00+01:00",
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"2023-01-29 13:00:00+01:00",
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"2023-01-29 13:15:00+01:00",
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"2023-01-29 13:30:00+01:00",
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"2023-01-29 13:45:00+01:00",
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"2023-01-29 14:00:00+01:00",
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"2023-01-29 14:15:00+01:00",
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"2023-01-29 14:30:00+01:00",
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"2023-01-29 14:45:00+01:00",
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"2023-01-29 15:00:00+01:00",
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"2023-01-29 15:15:00+01:00",
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"2023-01-29 15:30:00+01:00",
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"2023-01-29 15:45:00+01:00",
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"2023-01-29 16:00:00+01:00",
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"2023-01-29 16:15:00+01:00",
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"2023-01-29 16:30:00+01:00",
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"2023-01-29 16:45:00+01:00",
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"2023-01-29 17:00:00+01:00",
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"2023-01-29 17:15:00+01:00",
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"2023-01-29 17:30:00+01:00",
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"2023-01-29 17:45:00+01:00",
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"2023-01-29 18:00:00+01:00",
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"2023-01-29 18:15:00+01:00",
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"2023-01-29 18:30:00+01:00",
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"2023-01-29 18:45:00+01:00",
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"2023-01-29 19:00:00+01:00",
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"2023-01-29 19:15:00+01:00",
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"2023-01-29 19:30:00+01:00",
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"2023-01-29 19:45:00+01:00",
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"2023-01-29 20:00:00+01:00",
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"2023-01-29 20:15:00+01:00",
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"2023-01-29 20:30:00+01:00",
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"2023-01-29 20:45:00+01:00",
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"2023-01-29 21:00:00+01:00",
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"2023-01-29 21:15:00+01:00",
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"2023-01-29 21:30:00+01:00",
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"2023-01-29 21:45:00+01:00",
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"2023-01-29 22:00:00+01:00",
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"2023-01-29 22:15:00+01:00",
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"2023-01-29 22:30:00+01:00",
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"2023-01-29 22:45:00+01:00",
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"2023-01-29 23:00:00+01:00",
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"2023-01-29 23:15:00+01:00",
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"2023-01-29 23:30:00+01:00",
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"2023-01-29 23:45:00+01:00",
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"2023-01-30 00:00:00+01:00",
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"2023-01-30 00:15:00+01:00",
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"2023-01-30 00:30:00+01:00",
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"2023-01-30 00:45:00+01:00",
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"2023-01-30 01:00:00+01:00",
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"2023-01-30 01:15:00+01:00",
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"2023-01-30 01:30:00+01:00",
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"2023-01-30 01:45:00+01:00",
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"2023-01-30 02:00:00+01:00",
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"2023-01-30 02:15:00+01:00",
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"2023-01-30 02:30:00+01:00",
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"2023-01-30 02:45:00+01:00",
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"2023-01-30 03:00:00+01:00",
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"2023-01-30 03:15:00+01:00",
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"2023-01-30 03:30:00+01:00",
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"2023-01-30 03:45:00+01:00",
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"2023-01-30 04:00:00+01:00",
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"2023-01-30 04:15:00+01:00",
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"2023-01-30 04:30:00+01:00",
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"2023-01-30 04:45:00+01:00",
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"2023-01-30 05:00:00+01:00",
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"2023-01-30 05:15:00+01:00",
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"2023-01-30 05:30:00+01:00",
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"2023-01-30 05:45:00+01:00",
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"2023-01-30 06:00:00+01:00",
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"2023-01-30 06:15:00+01:00",
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"2023-01-30 06:30:00+01:00",
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"2023-01-30 06:45:00+01:00",
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"2023-01-30 07:00:00+01:00",
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"2023-01-30 07:15:00+01:00",
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"2023-01-30 07:30:00+01:00",
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"2023-01-30 07:45:00+01:00",
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"2023-01-30 08:00:00+01:00",
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"2023-01-30 08:15:00+01:00",
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"2023-01-30 08:30:00+01:00",
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"2023-01-30 08:45:00+01:00",
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"2023-01-30 09:00:00+01:00",
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"2023-01-30 09:15:00+01:00",
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"2023-01-30 09:30:00+01:00",
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"2023-01-30 09:45:00+01:00",
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"2023-01-30 10:00:00+01:00",
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"2023-01-30 10:15:00+01:00",
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"2023-01-30 10:30:00+01:00",
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"2023-01-30 10:45:00+01:00",
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"2023-01-30 11:00:00+01:00",
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"2023-01-30 11:15:00+01:00",
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"2023-01-30 11:30:00+01:00",
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"2023-01-30 11:45:00+01:00",
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"2023-01-30 12:00:00+01:00",
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"2023-01-30 12:15:00+01:00",
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"2023-01-30 12:30:00+01:00",
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"2023-01-30 12:45:00+01:00",
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"2023-01-30 13:00:00+01:00",
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"2023-01-30 13:15:00+01:00",
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"2023-01-30 13:30:00+01:00",
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"2023-01-30 13:45:00+01:00",
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"2023-01-30 14:00:00+01:00",
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"2023-01-30 14:15:00+01:00",
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"2023-01-30 14:30:00+01:00",
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"2023-01-30 14:45:00+01:00",
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"2023-01-30 15:00:00+01:00",
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"2023-01-30 15:15:00+01:00",
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"2023-01-30 15:30:00+01:00",
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"2023-01-30 15:45:00+01:00",
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"2023-01-30 16:00:00+01:00",
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"2023-01-30 16:15:00+01:00",
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"2023-01-30 16:30:00+01:00",
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"2023-01-30 16:45:00+01:00",
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"2023-01-30 17:00:00+01:00",
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"2023-01-30 17:15:00+01:00",
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"2023-01-30 17:30:00+01:00",
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"2023-01-30 17:45:00+01:00",
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"2023-01-30 18:00:00+01:00",
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"2023-01-30 18:15:00+01:00",
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"2023-01-30 18:30:00+01:00",
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"2023-01-30 18:45:00+01:00",
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"2023-01-30 19:00:00+01:00",
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"2023-01-30 19:15:00+01:00",
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"2023-01-30 19:30:00+01:00",
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"2023-01-30 19:45:00+01:00",
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"2023-01-30 20:00:00+01:00",
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"2023-01-30 20:15:00+01:00",
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"2023-01-30 20:30:00+01:00",
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"2023-01-30 20:45:00+01:00",
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"2023-01-30 21:00:00+01:00",
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"2023-01-30 21:15:00+01:00",
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"2023-01-30 21:30:00+01:00",
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"2023-01-30 21:45:00+01:00",
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"2023-01-30 22:00:00+01:00",
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"2023-01-30 22:15:00+01:00",
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"2023-01-30 22:30:00+01:00",
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"2023-01-30 22:45:00+01:00",
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"2023-01-30 23:00:00+01:00",
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"2023-01-30 23:15:00+01:00",
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"2023-01-30 23:30:00+01:00",
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"2023-01-30 23:45:00+01:00",
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"2023-01-31 00:00:00+01:00",
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"2023-01-31 00:15:00+01:00",
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"2023-01-31 00:30:00+01:00",
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"2023-01-31 00:45:00+01:00",
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"2023-01-31 01:00:00+01:00",
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"2023-01-31 01:15:00+01:00",
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"2023-01-31 01:30:00+01:00",
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"2023-01-31 01:45:00+01:00",
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"2023-01-31 02:00:00+01:00",
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"2023-01-31 02:15:00+01:00",
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"2023-01-31 02:30:00+01:00",
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"2023-01-31 02:45:00+01:00",
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"2023-01-31 03:00:00+01:00",
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"2023-01-31 03:15:00+01:00",
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"2023-01-31 03:30:00+01:00",
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"2023-01-31 03:45:00+01:00",
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"2023-01-31 04:00:00+01:00",
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"2023-01-31 04:15:00+01:00",
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"2023-01-31 04:30:00+01:00",
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"2023-01-31 04:45:00+01:00",
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"2023-01-31 05:00:00+01:00",
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"2023-01-31 05:15:00+01:00",
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"2023-01-31 05:30:00+01:00",
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"2023-01-31 05:45:00+01:00",
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"2023-01-31 06:00:00+01:00",
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"2023-01-31 06:15:00+01:00",
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"2023-01-31 06:30:00+01:00",
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"2023-01-31 06:45:00+01:00",
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"2023-01-31 07:00:00+01:00",
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"2023-01-31 07:15:00+01:00",
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"2023-01-31 07:30:00+01:00",
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"2023-01-31 07:45:00+01:00",
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"2023-01-31 08:00:00+01:00",
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"2023-01-31 08:15:00+01:00",
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"2023-01-31 08:30:00+01:00",
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"2023-01-31 08:45:00+01:00",
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"2023-01-31 09:00:00+01:00",
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"2023-01-31 09:15:00+01:00",
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"2023-01-31 09:30:00+01:00",
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"2023-01-31 09:45:00+01:00",
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"2023-01-31 10:00:00+01:00",
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"2023-01-31 10:15:00+01:00",
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"2023-01-31 10:30:00+01:00",
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"2023-01-31 10:45:00+01:00",
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"2023-01-31 11:00:00+01:00",
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"2023-01-31 11:15:00+01:00",
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"2023-01-31 11:30:00+01:00",
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"2023-01-31 11:45:00+01:00",
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"2023-01-31 12:00:00+01:00",
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"2023-01-31 12:15:00+01:00",
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"2023-01-31 12:30:00+01:00",
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"2023-01-31 12:45:00+01:00",
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"2023-01-31 13:00:00+01:00",
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"2023-01-31 13:15:00+01:00",
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"2023-01-31 13:30:00+01:00",
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"2023-01-31 13:45:00+01:00",
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"2023-01-31 14:00:00+01:00",
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"2023-01-31 14:15:00+01:00",
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"2023-01-31 14:30:00+01:00",
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"2023-01-31 14:45:00+01:00",
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"2023-01-31 15:00:00+01:00",
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"2023-01-31 15:15:00+01:00",
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"2023-01-31 15:30:00+01:00",
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"2023-01-31 15:45:00+01:00",
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"2023-01-31 16:00:00+01:00",
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"2023-01-31 16:15:00+01:00",
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"2023-01-31 16:30:00+01:00",
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"2023-01-31 16:45:00+01:00",
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"2023-01-31 17:00:00+01:00",
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"2023-01-31 17:15:00+01:00",
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"2023-01-31 17:30:00+01:00",
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"2023-01-31 17:45:00+01:00",
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"2023-01-31 18:00:00+01:00",
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"2023-01-31 18:15:00+01:00",
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"2023-01-31 18:30:00+01:00",
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"2023-01-31 18:45:00+01:00",
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"2023-01-31 19:00:00+01:00",
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"2023-01-31 19:15:00+01:00",
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"2023-01-31 19:30:00+01:00",
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"2023-01-31 19:45:00+01:00",
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"2023-01-31 20:00:00+01:00",
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"2023-01-31 20:15:00+01:00",
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"2023-01-31 20:30:00+01:00",
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"2023-01-31 20:45:00+01:00",
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"2023-01-31 21:00:00+01:00",
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"2023-01-31 21:15:00+01:00",
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"2023-01-31 21:30:00+01:00",
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"2023-01-31 21:45:00+01:00",
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"2023-01-31 22:00:00+01:00",
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"2023-01-31 22:15:00+01:00",
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"2023-01-31 22:30:00+01:00",
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"2023-01-31 22:45:00+01:00",
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"2023-01-31 23:00:00+01:00",
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"2023-01-31 23:15:00+01:00",
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"2023-01-31 23:30:00+01:00",
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"2023-01-31 23:45:00+01:00",
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"2023-02-01 00:00:00+01:00",
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"2023-02-01 00:15:00+01:00",
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"2023-02-01 00:30:00+01:00",
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"2023-02-01 00:45:00+01:00",
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"2023-02-01 01:00:00+01:00",
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"2023-02-01 01:15:00+01:00",
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"2023-02-01 01:30:00+01:00",
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"2023-02-01 01:45:00+01:00",
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"2023-02-01 02:00:00+01:00",
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"2023-02-01 02:15:00+01:00",
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"2023-02-01 02:30:00+01:00",
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"2023-02-01 02:45:00+01:00",
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"2023-02-01 03:00:00+01:00",
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"2023-02-01 03:15:00+01:00",
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"2023-02-01 03:30:00+01:00",
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"2023-02-01 03:45:00+01:00",
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"2023-02-01 04:00:00+01:00",
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"2023-02-01 04:15:00+01:00",
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"2023-02-01 04:30:00+01:00",
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"2023-02-01 04:45:00+01:00",
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"2023-02-01 05:00:00+01:00",
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"2023-02-01 05:15:00+01:00",
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"2023-02-01 05:30:00+01:00",
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"2023-02-01 05:45:00+01:00",
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"2023-02-01 06:00:00+01:00",
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"2023-02-01 06:15:00+01:00",
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"2023-02-01 06:30:00+01:00",
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"2023-02-01 06:45:00+01:00",
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"2023-02-01 07:00:00+01:00",
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"2023-02-01 07:15:00+01:00",
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"2023-02-01 07:30:00+01:00",
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"2023-02-01 07:45:00+01:00",
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"2023-02-01 08:00:00+01:00",
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"2023-02-01 08:15:00+01:00",
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"2023-02-01 08:30:00+01:00",
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"2023-02-01 08:45:00+01:00",
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"2023-02-01 09:00:00+01:00",
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"2023-02-01 09:15:00+01:00",
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"2023-02-01 09:30:00+01:00",
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"2023-02-01 09:45:00+01:00",
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"2023-02-01 10:00:00+01:00",
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"2023-02-01 10:15:00+01:00",
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"2023-02-01 10:30:00+01:00",
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"2023-02-01 10:45:00+01:00",
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"2023-02-01 11:00:00+01:00",
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"2023-02-01 11:15:00+01:00",
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"2023-02-01 11:30:00+01:00",
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"2023-02-01 11:45:00+01:00",
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"2023-02-01 12:00:00+01:00",
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"2023-02-01 12:15:00+01:00",
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"2023-02-01 12:30:00+01:00",
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"2023-02-01 12:45:00+01:00",
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"2023-02-01 13:00:00+01:00",
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"2023-02-01 13:15:00+01:00",
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"2023-02-01 13:30:00+01:00",
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"2023-02-01 13:45:00+01:00",
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"2023-02-01 14:00:00+01:00",
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"2023-02-01 14:15:00+01:00",
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"2023-02-01 14:30:00+01:00",
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"2023-02-01 14:45:00+01:00",
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"2023-02-01 15:00:00+01:00",
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"2023-02-01 15:15:00+01:00",
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"2023-02-01 15:30:00+01:00",
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"2023-02-01 15:45:00+01:00",
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"2023-02-01 16:00:00+01:00",
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"2023-02-01 16:15:00+01:00",
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"2023-02-01 16:30:00+01:00",
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"2023-02-01 16:45:00+01:00",
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"2023-02-01 17:00:00+01:00",
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"2023-02-01 17:15:00+01:00",
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"2023-02-01 17:30:00+01:00",
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"2023-02-01 17:45:00+01:00",
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"2023-02-01 18:00:00+01:00",
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"2023-02-01 18:15:00+01:00",
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"2023-02-01 18:30:00+01:00",
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"2023-02-01 18:45:00+01:00",
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"2023-02-01 19:00:00+01:00",
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"2023-02-01 19:15:00+01:00",
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"2023-02-01 19:30:00+01:00",
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"2023-02-01 19:45:00+01:00",
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"2023-02-01 20:00:00+01:00",
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"2023-02-01 20:15:00+01:00",
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"2023-02-01 20:30:00+01:00",
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"2023-02-01 20:45:00+01:00",
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"2023-02-01 21:00:00+01:00",
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"2023-02-01 21:15:00+01:00",
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"2023-02-01 21:30:00+01:00",
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"2023-02-01 21:45:00+01:00",
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"2023-02-01 22:00:00+01:00",
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"2023-02-01 22:15:00+01:00",
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"2023-02-01 22:30:00+01:00",
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"2023-02-01 22:45:00+01:00",
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"2023-02-01 23:00:00+01:00",
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"2023-02-01 23:15:00+01:00",
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"2023-02-01 23:30:00+01:00",
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"2023-02-01 23:45:00+01:00",
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"2023-02-02 00:00:00+01:00",
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"2023-02-02 00:15:00+01:00",
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"2023-02-02 00:30:00+01:00",
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"2023-02-02 00:45:00+01:00",
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"2023-02-02 01:00:00+01:00",
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"2023-02-02 01:15:00+01:00",
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"2023-02-02 01:30:00+01:00",
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"2023-02-02 01:45:00+01:00",
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"2023-02-02 02:00:00+01:00",
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"2023-02-02 02:15:00+01:00",
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"2023-02-02 02:30:00+01:00",
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"2023-02-02 02:45:00+01:00",
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"2023-02-02 03:00:00+01:00",
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"2023-02-02 03:15:00+01:00",
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"2023-02-02 03:30:00+01:00",
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"2023-02-02 03:45:00+01:00",
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"2023-02-02 04:00:00+01:00",
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"2023-02-02 04:15:00+01:00",
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"2023-02-02 04:30:00+01:00",
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"2023-02-02 04:45:00+01:00",
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"2023-02-02 05:00:00+01:00",
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"2023-02-02 05:15:00+01:00",
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"2023-02-02 05:30:00+01:00",
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"2023-02-02 05:45:00+01:00",
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"2023-02-02 06:00:00+01:00",
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"2023-02-02 06:15:00+01:00",
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"2023-02-02 06:30:00+01:00",
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"2023-02-02 06:45:00+01:00",
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"2023-02-02 07:00:00+01:00",
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"2023-02-02 07:15:00+01:00",
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"2023-02-02 07:30:00+01:00",
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"2023-02-02 07:45:00+01:00",
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"2023-02-02 08:00:00+01:00",
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"2023-02-02 08:15:00+01:00",
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"2023-02-02 08:30:00+01:00",
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"2023-02-02 08:45:00+01:00",
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"2023-02-02 09:00:00+01:00",
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"2023-02-02 09:15:00+01:00",
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"2023-02-02 09:30:00+01:00",
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"2023-02-02 09:45:00+01:00",
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"2023-02-02 10:00:00+01:00",
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"2023-02-02 10:15:00+01:00",
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"2023-02-02 10:30:00+01:00",
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"2023-02-02 10:45:00+01:00",
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"2023-02-02 11:00:00+01:00",
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"2023-02-02 11:15:00+01:00",
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"2023-02-02 11:30:00+01:00",
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"2023-02-02 11:45:00+01:00",
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"2023-02-02 12:00:00+01:00",
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"2023-02-02 12:15:00+01:00",
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"2023-02-02 12:30:00+01:00",
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"2023-02-02 12:45:00+01:00",
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"2023-02-02 13:00:00+01:00",
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"2023-02-02 13:15:00+01:00",
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"2023-02-02 13:30:00+01:00",
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"2023-02-02 13:45:00+01:00",
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"2023-02-02 14:00:00+01:00",
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"2023-02-02 14:15:00+01:00",
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"2023-02-02 14:30:00+01:00",
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"2023-02-02 14:45:00+01:00",
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"2023-02-02 15:00:00+01:00",
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"2023-02-02 15:15:00+01:00",
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"2023-02-02 15:30:00+01:00",
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"2023-02-02 15:45:00+01:00",
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"2023-02-02 16:00:00+01:00",
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"2023-02-02 16:15:00+01:00",
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"2023-02-02 16:30:00+01:00",
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"2023-02-02 16:45:00+01:00",
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"2023-02-02 17:00:00+01:00",
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"2023-02-02 17:15:00+01:00",
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"2023-02-02 17:30:00+01:00",
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"2023-02-02 17:45:00+01:00",
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"2023-02-02 18:00:00+01:00",
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"2023-02-02 18:15:00+01:00",
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"2023-02-02 18:30:00+01:00",
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"2023-02-02 18:45:00+01:00",
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"2023-02-02 19:00:00+01:00",
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"2023-02-02 19:15:00+01:00",
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"2023-02-02 19:30:00+01:00",
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"2023-02-02 19:45:00+01:00",
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"2023-02-02 20:00:00+01:00",
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"2023-02-02 20:15:00+01:00",
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"2023-02-02 20:30:00+01:00",
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"2023-02-02 20:45:00+01:00",
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"2023-02-02 21:00:00+01:00",
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"2023-02-02 21:15:00+01:00",
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"2023-02-02 21:30:00+01:00",
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"2023-02-02 21:45:00+01:00",
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"2023-02-02 22:00:00+01:00",
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"2023-02-02 22:15:00+01:00",
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"2023-02-02 22:30:00+01:00",
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"2023-02-02 22:45:00+01:00",
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"2023-02-02 23:00:00+01:00",
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"2023-02-02 23:15:00+01:00",
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"2023-02-02 23:30:00+01:00",
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"2023-02-02 23:45:00+01:00",
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"2023-02-03 00:00:00+01:00",
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"2023-02-03 00:15:00+01:00",
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"2023-02-03 00:30:00+01:00",
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"2023-02-03 00:45:00+01:00",
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"2023-02-03 01:00:00+01:00",
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"2023-02-03 01:15:00+01:00",
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"2023-02-03 01:30:00+01:00",
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"2023-02-03 01:45:00+01:00",
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"2023-02-03 02:00:00+01:00",
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"2023-02-03 02:15:00+01:00",
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"2023-02-03 02:30:00+01:00",
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"2023-02-03 02:45:00+01:00",
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"2023-02-03 03:00:00+01:00",
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"2023-02-03 03:15:00+01:00",
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"2023-02-03 03:30:00+01:00",
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"2023-02-03 03:45:00+01:00",
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"2023-02-03 04:00:00+01:00",
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"2023-02-03 04:15:00+01:00",
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"2023-02-03 04:30:00+01:00",
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"2023-02-03 04:45:00+01:00",
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"2023-02-03 05:00:00+01:00",
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"2023-02-03 05:15:00+01:00",
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"2023-02-03 05:30:00+01:00",
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"2023-02-03 05:45:00+01:00",
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"2023-02-03 06:00:00+01:00",
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"2023-02-03 06:15:00+01:00",
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"2023-02-03 06:30:00+01:00",
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"2023-02-03 06:45:00+01:00",
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"2023-02-03 07:00:00+01:00",
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"2023-02-03 07:15:00+01:00",
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"2023-02-03 07:30:00+01:00",
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"2023-02-03 07:45:00+01:00",
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"2023-02-03 08:00:00+01:00",
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"2023-02-03 08:15:00+01:00",
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"2023-02-03 08:30:00+01:00",
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"2023-02-03 08:45:00+01:00",
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"2023-02-03 09:00:00+01:00",
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"2023-02-03 09:15:00+01:00",
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"2023-02-03 09:30:00+01:00",
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"2023-02-03 09:45:00+01:00",
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"2023-02-03 10:00:00+01:00",
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"2023-02-03 10:15:00+01:00",
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"2023-02-03 10:30:00+01:00",
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"2023-02-03 10:45:00+01:00",
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"2023-02-03 11:00:00+01:00",
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"2023-02-03 11:15:00+01:00",
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"2023-02-03 11:30:00+01:00",
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"2023-02-03 11:45:00+01:00",
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"2023-02-03 12:00:00+01:00",
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"2023-02-03 12:15:00+01:00",
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"2023-02-03 12:30:00+01:00",
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"2023-02-03 12:45:00+01:00",
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"2023-02-03 13:00:00+01:00",
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"2023-02-03 13:15:00+01:00",
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"2023-02-03 13:30:00+01:00",
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"2023-02-03 13:45:00+01:00",
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"2023-02-03 14:00:00+01:00",
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"2023-02-03 14:15:00+01:00",
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"2023-02-03 14:30:00+01:00",
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"2023-02-03 14:45:00+01:00",
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"2023-02-03 15:00:00+01:00",
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"2023-02-03 15:15:00+01:00",
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"2023-02-03 15:30:00+01:00",
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"2023-02-03 15:45:00+01:00",
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"2023-02-03 16:00:00+01:00",
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"2023-02-03 16:15:00+01:00",
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"2023-02-03 16:30:00+01:00",
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"2023-02-03 16:45:00+01:00",
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"2023-02-03 17:00:00+01:00",
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"2023-02-03 17:15:00+01:00",
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"2023-02-03 17:30:00+01:00",
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"2023-02-03 17:45:00+01:00",
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"2023-02-03 18:00:00+01:00",
|
|
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"metadata": {},
|
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"output_type": "display_data"
|
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}
|
|
],
|
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"source": [
|
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"s.demand.resample('15T').mean()[['Tsource (VDG)', 'Tsink (VDG)']].iplot()"
|
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]
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},
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{
|
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"cell_type": "code",
|
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"execution_count": 9,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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"\n",
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" .dataframe tbody tr th {\n",
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"\n",
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" .dataframe thead th {\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
|
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" <tr style=\"text-align: right;\">\n",
|
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" <th></th>\n",
|
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" <th>Tsource (VDG)</th>\n",
|
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" <th>Tsink (VDG)</th>\n",
|
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" <th>MW (VDG)</th>\n",
|
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" <th>Tsource (NDG)</th>\n",
|
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" <th>Tsink (NDG)</th>\n",
|
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" <th>MW (NDG)</th>\n",
|
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" <th>Total demand</th>\n",
|
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" </tr>\n",
|
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" </thead>\n",
|
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" <tbody>\n",
|
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" <tr>\n",
|
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" <th>count</th>\n",
|
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" <td>52560.0</td>\n",
|
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" <td>52560.0</td>\n",
|
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" <td>52560.0</td>\n",
|
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" <td>52560.0</td>\n",
|
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" <td>52560.0</td>\n",
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" <td>52560.0</td>\n",
|
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" <td>52560.0</td>\n",
|
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" </tr>\n",
|
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" <tr>\n",
|
|
" <th>mean</th>\n",
|
|
" <td>75.0</td>\n",
|
|
" <td>144.0</td>\n",
|
|
" <td>1.0</td>\n",
|
|
" <td>75.0</td>\n",
|
|
" <td>144.0</td>\n",
|
|
" <td>1.0</td>\n",
|
|
" <td>2.0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>std</th>\n",
|
|
" <td>0.0</td>\n",
|
|
" <td>0.0</td>\n",
|
|
" <td>0.0</td>\n",
|
|
" <td>0.0</td>\n",
|
|
" <td>0.0</td>\n",
|
|
" <td>0.0</td>\n",
|
|
" <td>0.0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>min</th>\n",
|
|
" <td>75.0</td>\n",
|
|
" <td>144.0</td>\n",
|
|
" <td>1.0</td>\n",
|
|
" <td>75.0</td>\n",
|
|
" <td>144.0</td>\n",
|
|
" <td>1.0</td>\n",
|
|
" <td>2.0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>25%</th>\n",
|
|
" <td>75.0</td>\n",
|
|
" <td>144.0</td>\n",
|
|
" <td>1.0</td>\n",
|
|
" <td>75.0</td>\n",
|
|
" <td>144.0</td>\n",
|
|
" <td>1.0</td>\n",
|
|
" <td>2.0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>50%</th>\n",
|
|
" <td>75.0</td>\n",
|
|
" <td>144.0</td>\n",
|
|
" <td>1.0</td>\n",
|
|
" <td>75.0</td>\n",
|
|
" <td>144.0</td>\n",
|
|
" <td>1.0</td>\n",
|
|
" <td>2.0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>75%</th>\n",
|
|
" <td>75.0</td>\n",
|
|
" <td>144.0</td>\n",
|
|
" <td>1.0</td>\n",
|
|
" <td>75.0</td>\n",
|
|
" <td>144.0</td>\n",
|
|
" <td>1.0</td>\n",
|
|
" <td>2.0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>max</th>\n",
|
|
" <td>75.0</td>\n",
|
|
" <td>144.0</td>\n",
|
|
" <td>1.0</td>\n",
|
|
" <td>75.0</td>\n",
|
|
" <td>144.0</td>\n",
|
|
" <td>1.0</td>\n",
|
|
" <td>2.0</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" Tsource (VDG) Tsink (VDG) MW (VDG) Tsource (NDG) Tsink (NDG) \\\n",
|
|
"count 52560.0 52560.0 52560.0 52560.0 52560.0 \n",
|
|
"mean 75.0 144.0 1.0 75.0 144.0 \n",
|
|
"std 0.0 0.0 0.0 0.0 0.0 \n",
|
|
"min 75.0 144.0 1.0 75.0 144.0 \n",
|
|
"25% 75.0 144.0 1.0 75.0 144.0 \n",
|
|
"50% 75.0 144.0 1.0 75.0 144.0 \n",
|
|
"75% 75.0 144.0 1.0 75.0 144.0 \n",
|
|
"max 75.0 144.0 1.0 75.0 144.0 \n",
|
|
"\n",
|
|
" MW (NDG) Total demand \n",
|
|
"count 52560.0 52560.0 \n",
|
|
"mean 1.0 2.0 \n",
|
|
"std 0.0 0.0 \n",
|
|
"min 1.0 2.0 \n",
|
|
"25% 1.0 2.0 \n",
|
|
"50% 1.0 2.0 \n",
|
|
"75% 1.0 2.0 \n",
|
|
"max 1.0 2.0 "
|
|
]
|
|
},
|
|
"execution_count": 9,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"s.demand.describe()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"source": [
|
|
"## Load in data"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 10,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"def add_afrr_prices(c, case):\n",
|
|
" try:\n",
|
|
" aFRR_signal = pd.read_csv(f'data/aFRR_{c.start}.csv', delimiter=';', decimal=',', index_col='datetime')\n",
|
|
" aFRR_signal.index = case.data.index\n",
|
|
" except:\n",
|
|
" data = get_tennet_data('balansdelta2017', pd.to_datetime(c.start), pd.to_datetime(c.end))\n",
|
|
" data.index = data[[\"datum\", \"tijd\"]].apply(lambda x: \" \".join(x), axis=1)\n",
|
|
" data.index = pd.to_datetime(data.index, format=\"%d-%m-%Y %H:%M\").tz_localize(\n",
|
|
" \"Europe/Amsterdam\", ambiguous=True\n",
|
|
" )\n",
|
|
" data = data[~data.index.duplicated(keep=\"first\")]\n",
|
|
" date_ix = pd.date_range(\n",
|
|
" data.index[0], data.index[-1], freq=\"1T\", tz=\"Europe/Amsterdam\"\n",
|
|
" )\n",
|
|
" data = data.reindex(date_ix)\n",
|
|
" aFRR_signal = data[['Hoogste_prijs_opregelen', 'Mid_prijs_opregelen', 'Laagste_prijs_afregelen']]\n",
|
|
" aFRR_signal.to_csv(f'data/aFRR_{c.start}.csv', sep=';', decimal=',', index_label='datetime')\n",
|
|
"\n",
|
|
" try:\n",
|
|
" aFRR_prices = pd.read_csv(f'data/aFRR_prices_{c.start}.csv', delimiter=';', decimal=',', index_col='datetime')\n",
|
|
" aFRR_prices.index = case.data.index\n",
|
|
" except:\n",
|
|
" data = get_aFRR_prices_nl(pd.to_datetime(c.start), pd.to_datetime(c.end))\n",
|
|
" data.index = pd.date_range(\n",
|
|
" start=c.start,\n",
|
|
" end=pd.to_datetime(c.end) + timedelta(days=1),\n",
|
|
" tz='Europe/Amsterdam', \n",
|
|
" freq='15T', \n",
|
|
" closed='left'\n",
|
|
" )\n",
|
|
" aFRR_prices = data.reindex(case.data.index, method='ffill')\n",
|
|
" aFRR_prices.to_csv(f'data/aFRR_prices_{c.start}.csv', sep=';', decimal=',', index_label='datetime')\n",
|
|
" \n",
|
|
" case.data = pd.concat([case.data, aFRR_signal, aFRR_prices], axis=1)\n",
|
|
" return case"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 11,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"def increase_volatility_by_factor(col, factor):\n",
|
|
" mean = col.mean()\n",
|
|
" diff_to_mean = col - mean\n",
|
|
" new_diff = diff_to_mean * factor\n",
|
|
" return mean + new_diff\n",
|
|
"\n",
|
|
"def multiply_by_factor(col, factor):\n",
|
|
" mean = col.mean()\n",
|
|
" diff_to_mean = col - mean\n",
|
|
" \n",
|
|
" cond = diff_to_mean > 0\n",
|
|
" diff_to_mean[cond] *= factor\n",
|
|
" diff_to_mean[~cond] /= factor\n",
|
|
" return mean + diff_to_mean"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 12,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"C:\\Users\\shahla.huseynova\\source\\repos\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\prices.py:531: FutureWarning:\n",
|
|
"\n",
|
|
"'T' is deprecated and will be removed in a future version, please use 'min' instead.\n",
|
|
"\n",
|
|
"C:\\Users\\shahla.huseynova\\source\\repos\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\prices.py:443: FutureWarning:\n",
|
|
"\n",
|
|
"'T' is deprecated and will be removed in a future version, please use 'min' instead.\n",
|
|
"\n",
|
|
"C:\\Users\\shahla.huseynova\\source\\repos\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\prices.py:531: FutureWarning:\n",
|
|
"\n",
|
|
"'T' is deprecated and will be removed in a future version, please use 'min' instead.\n",
|
|
"\n",
|
|
"C:\\Users\\shahla.huseynova\\source\\repos\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\prices.py:443: FutureWarning:\n",
|
|
"\n",
|
|
"'T' is deprecated and will be removed in a future version, please use 'min' instead.\n",
|
|
"\n",
|
|
"C:\\Users\\shahla.huseynova\\source\\repos\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\prices.py:531: FutureWarning:\n",
|
|
"\n",
|
|
"'T' is deprecated and will be removed in a future version, please use 'min' instead.\n",
|
|
"\n",
|
|
"C:\\Users\\shahla.huseynova\\source\\repos\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\prices.py:443: FutureWarning:\n",
|
|
"\n",
|
|
"'T' is deprecated and will be removed in a future version, please use 'min' instead.\n",
|
|
"\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"def load_data(c, s):\n",
|
|
" if hasattr(s, 'afrr_case'):\n",
|
|
" s.afrr_case = add_afrr_prices(c, s.afrr_case)\n",
|
|
" \n",
|
|
" for case in s.cases:\n",
|
|
" case.add_gasprices()\n",
|
|
" case.add_co2prices(perMWh=True)\n",
|
|
" \n",
|
|
" case.data['Gas prices (€/MWh)'] *= c.gas_price_multiplier\n",
|
|
" case.data['CO2 prices (€/MWh)'] *= c.co2_price_multiplier\n",
|
|
" case.data['CO2 prices (€/ton)'] *= c.co2_price_multiplier\n",
|
|
" \n",
|
|
" for case in s.optcases:\n",
|
|
" case.data['NEG'] = multiply_by_factor(case.data['NEG'], c.e_price_multiplier)\n",
|
|
" case.data['ForeNeg'] = multiply_by_factor(case.data['ForeNeg'], c.e_price_multiplier)\n",
|
|
" case.data['DAM'] = multiply_by_factor(case.data['DAM'], c.e_price_multiplier)\n",
|
|
" \n",
|
|
" case.data['NEG'] = increase_volatility_by_factor(case.data['NEG'], c.e_price_volatility_multiplier)\n",
|
|
" case.data['ForeNeg'] = increase_volatility_by_factor(case.data['ForeNeg'], c.e_price_volatility_multiplier)\n",
|
|
" \n",
|
|
" if hasattr(s, 'afrr_case'):\n",
|
|
" for case in [s.afrr_case]:\n",
|
|
" case.data['Hoogste_prijs_opregelen'] = multiply_by_factor(case.data['Hoogste_prijs_opregelen'], c.e_price_multiplier)\n",
|
|
" case.data['Hoogste_prijs_opregelen'] = increase_volatility_by_factor(case.data['Hoogste_prijs_opregelen'], c.e_price_volatility_multiplier)\n",
|
|
" case.data['aFRR_up'] = multiply_by_factor(case.data['aFRR_up'], c.e_price_multiplier)\n",
|
|
" case.data['aFRR_up'] = increase_volatility_by_factor(case.data['aFRR_up'], c.e_price_volatility_multiplier)\n",
|
|
"\n",
|
|
" s.demand[['Tsource (VDG)', 'Tsource (NDG)']] += c.tsource_delta\n",
|
|
" s.demand[['Tsink (VDG)', 'Tsink (NDG)']] += c.tsink_delta\n",
|
|
" for case in s.cases:\n",
|
|
" case.data = pd.concat([case.data, s.demand], axis=1) \n",
|
|
"\n",
|
|
" s.eb_ode_g = get_tax_rate('gas', 2020, 4)['EB+ODE'] * c.energy_tax_multiplier\n",
|
|
" s.eb_ode_e = get_tax_rate('electricity', 2020, 4)['EB+ODE'] * c.energy_tax_multiplier\n",
|
|
" s.grid_fees = get_grid_tariffs_electricity(c.grid_operator, 2020, c.connection_type)\n",
|
|
" s.grid_fee_per_MWh = s.grid_fees['kWh tarief'] * 1000\n",
|
|
" return s\n",
|
|
"\n",
|
|
"s = load_data(c, s)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 13,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<div>\n",
|
|
"<style scoped>\n",
|
|
" .dataframe tbody tr th:only-of-type {\n",
|
|
" vertical-align: middle;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe tbody tr th {\n",
|
|
" vertical-align: top;\n",
|
|
" }\n",
|
|
"\n",
|
|
" .dataframe thead th {\n",
|
|
" text-align: right;\n",
|
|
" }\n",
|
|
"</style>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>DAM</th>\n",
|
|
" <th>POS</th>\n",
|
|
" <th>NEG</th>\n",
|
|
" <th>ForeNeg</th>\n",
|
|
" <th>ForePos</th>\n",
|
|
" <th>Gas prices (€/MWh)</th>\n",
|
|
" <th>CO2 prices (€/ton)</th>\n",
|
|
" <th>CO2 prices (€/MWh)</th>\n",
|
|
" <th>Tsource (VDG)</th>\n",
|
|
" <th>Tsink (VDG)</th>\n",
|
|
" <th>MW (VDG)</th>\n",
|
|
" <th>Tsource (NDG)</th>\n",
|
|
" <th>Tsink (NDG)</th>\n",
|
|
" <th>MW (NDG)</th>\n",
|
|
" <th>Total demand</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>2023-01-01 00:00:00+01:00</th>\n",
|
|
" <td>-3.61</td>\n",
|
|
" <td>-209.4</td>\n",
|
|
" <td>-209.4</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>63.998</td>\n",
|
|
" <td>5.23</td>\n",
|
|
" <td>1.01</td>\n",
|
|
" <td>75.0</td>\n",
|
|
" <td>144.0</td>\n",
|
|
" <td>1.0</td>\n",
|
|
" <td>75.0</td>\n",
|
|
" <td>144.0</td>\n",
|
|
" <td>1.0</td>\n",
|
|
" <td>2.0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2023-01-01 00:01:00+01:00</th>\n",
|
|
" <td>-3.61</td>\n",
|
|
" <td>-209.4</td>\n",
|
|
" <td>-209.4</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>63.998</td>\n",
|
|
" <td>5.23</td>\n",
|
|
" <td>1.01</td>\n",
|
|
" <td>75.0</td>\n",
|
|
" <td>144.0</td>\n",
|
|
" <td>1.0</td>\n",
|
|
" <td>75.0</td>\n",
|
|
" <td>144.0</td>\n",
|
|
" <td>1.0</td>\n",
|
|
" <td>2.0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2023-01-01 00:02:00+01:00</th>\n",
|
|
" <td>-3.61</td>\n",
|
|
" <td>-209.4</td>\n",
|
|
" <td>-209.4</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>63.998</td>\n",
|
|
" <td>5.23</td>\n",
|
|
" <td>1.01</td>\n",
|
|
" <td>75.0</td>\n",
|
|
" <td>144.0</td>\n",
|
|
" <td>1.0</td>\n",
|
|
" <td>75.0</td>\n",
|
|
" <td>144.0</td>\n",
|
|
" <td>1.0</td>\n",
|
|
" <td>2.0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2023-01-01 00:03:00+01:00</th>\n",
|
|
" <td>-3.61</td>\n",
|
|
" <td>-209.4</td>\n",
|
|
" <td>-209.4</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>63.998</td>\n",
|
|
" <td>5.23</td>\n",
|
|
" <td>1.01</td>\n",
|
|
" <td>75.0</td>\n",
|
|
" <td>144.0</td>\n",
|
|
" <td>1.0</td>\n",
|
|
" <td>75.0</td>\n",
|
|
" <td>144.0</td>\n",
|
|
" <td>1.0</td>\n",
|
|
" <td>2.0</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>2023-01-01 00:04:00+01:00</th>\n",
|
|
" <td>-3.61</td>\n",
|
|
" <td>-209.4</td>\n",
|
|
" <td>-209.4</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>63.998</td>\n",
|
|
" <td>5.23</td>\n",
|
|
" <td>1.01</td>\n",
|
|
" <td>75.0</td>\n",
|
|
" <td>144.0</td>\n",
|
|
" <td>1.0</td>\n",
|
|
" <td>75.0</td>\n",
|
|
" <td>144.0</td>\n",
|
|
" <td>1.0</td>\n",
|
|
" <td>2.0</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" DAM POS NEG ForeNeg ForePos \\\n",
|
|
"2023-01-01 00:00:00+01:00 -3.61 -209.4 -209.4 NaN NaN \n",
|
|
"2023-01-01 00:01:00+01:00 -3.61 -209.4 -209.4 NaN NaN \n",
|
|
"2023-01-01 00:02:00+01:00 -3.61 -209.4 -209.4 NaN NaN \n",
|
|
"2023-01-01 00:03:00+01:00 -3.61 -209.4 -209.4 NaN NaN \n",
|
|
"2023-01-01 00:04:00+01:00 -3.61 -209.4 -209.4 NaN NaN \n",
|
|
"\n",
|
|
" Gas prices (€/MWh) CO2 prices (€/ton) \\\n",
|
|
"2023-01-01 00:00:00+01:00 63.998 5.23 \n",
|
|
"2023-01-01 00:01:00+01:00 63.998 5.23 \n",
|
|
"2023-01-01 00:02:00+01:00 63.998 5.23 \n",
|
|
"2023-01-01 00:03:00+01:00 63.998 5.23 \n",
|
|
"2023-01-01 00:04:00+01:00 63.998 5.23 \n",
|
|
"\n",
|
|
" CO2 prices (€/MWh) Tsource (VDG) Tsink (VDG) \\\n",
|
|
"2023-01-01 00:00:00+01:00 1.01 75.0 144.0 \n",
|
|
"2023-01-01 00:01:00+01:00 1.01 75.0 144.0 \n",
|
|
"2023-01-01 00:02:00+01:00 1.01 75.0 144.0 \n",
|
|
"2023-01-01 00:03:00+01:00 1.01 75.0 144.0 \n",
|
|
"2023-01-01 00:04:00+01:00 1.01 75.0 144.0 \n",
|
|
"\n",
|
|
" MW (VDG) Tsource (NDG) Tsink (NDG) MW (NDG) \\\n",
|
|
"2023-01-01 00:00:00+01:00 1.0 75.0 144.0 1.0 \n",
|
|
"2023-01-01 00:01:00+01:00 1.0 75.0 144.0 1.0 \n",
|
|
"2023-01-01 00:02:00+01:00 1.0 75.0 144.0 1.0 \n",
|
|
"2023-01-01 00:03:00+01:00 1.0 75.0 144.0 1.0 \n",
|
|
"2023-01-01 00:04:00+01:00 1.0 75.0 144.0 1.0 \n",
|
|
"\n",
|
|
" Total demand \n",
|
|
"2023-01-01 00:00:00+01:00 2.0 \n",
|
|
"2023-01-01 00:01:00+01:00 2.0 \n",
|
|
"2023-01-01 00:02:00+01:00 2.0 \n",
|
|
"2023-01-01 00:03:00+01:00 2.0 \n",
|
|
"2023-01-01 00:04:00+01:00 2.0 "
|
|
]
|
|
},
|
|
"execution_count": 13,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"s.hpcase.data.head()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"source": [
|
|
"## Assets"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"source": [
|
|
"### COP curve"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 14,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"def cop_curve(Tsink, Tsource):\n",
|
|
" Tsink += 273\n",
|
|
" Tsource += 273\n",
|
|
"\n",
|
|
" c1 = 0.267 * Tsink / (Tsink - Tsource)\n",
|
|
" c2 = 0.333 * Tsink / (Tsink - Tsource)\n",
|
|
" \n",
|
|
" return Polynomial([c2, c1])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 15,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/latex": [
|
|
"$x \\mapsto \\text{1.08290551} + \\text{0.86827559}\\,x$"
|
|
],
|
|
"text/plain": [
|
|
"Polynomial([1.08290551, 0.86827559], domain=[-1, 1], window=[-1, 1], symbol='x')"
|
|
]
|
|
},
|
|
"execution_count": 15,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"cop_curve(140, 13)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 16,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/latex": [
|
|
"$x \\mapsto \\text{2.05267164} + \\text{1.64583582}\\,x$"
|
|
],
|
|
"text/plain": [
|
|
"Polynomial([2.05267164, 1.64583582], domain=[-1, 1], window=[-1, 1], symbol='x')"
|
|
]
|
|
},
|
|
"execution_count": 16,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"cop_curve(140, 73)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 17,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"heatpump = Heatpump(\n",
|
|
" name='Heatpump',\n",
|
|
" max_th_power=1,\n",
|
|
" min_th_power=0,\n",
|
|
" cop_curve=cop_curve\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 18,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"#heatpump.get_cop(heat_output=load, Tsink=140, Tsource=13)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 19,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"#heatpump.get_cop(heat_output=load, Tsink=140, Tsource=99)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 20,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import itertools\n",
|
|
"\n",
|
|
"source_Ts = np.arange(25, 75) + 273\n",
|
|
"sink_Ts = np.arange(80, 170) + 273\n",
|
|
"\n",
|
|
"df = pd.DataFrame(columns=list(sink_Ts), index=list(source_Ts))\n",
|
|
"for sourceT, sinkT in itertools.product(source_Ts, sink_Ts):\n",
|
|
" df.loc[sourceT, sinkT] = heatpump.get_cop(heat_output=0.5, Tsink=sinkT, Tsource=sourceT)\n",
|
|
" \n",
|
|
"#df.to_csv('cops_at_50perc_load.csv', sep=';', decimal=',')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 21,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"sourceT = 63 + 273\n",
|
|
"sinkT = 140 + 273\n",
|
|
"loads = np.arange(0, 1, 0.01)\n",
|
|
"\n",
|
|
"cop_series = pd.Series(index=loads, dtype='float')\n",
|
|
"load_series = pd.Series(index=loads, dtype='float')\n",
|
|
"for load in loads:\n",
|
|
" cop = heatpump.get_cop(heat_output=load, Tsink=sinkT, Tsource=sourceT)\n",
|
|
" cop_series[load] = cop\n",
|
|
" load_series[load] = load / cop "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 22,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"application/vnd.plotly.v1+json": {
|
|
"config": {
|
|
"plotlyServerURL": "https://plot.ly"
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},
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"data": [
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{
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"line": {
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"shape": "linear",
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|
"width": 1.3
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},
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|
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"name": "None",
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],
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"layout": {
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"fig_load_curve = load_series.iplot(title=f'Heatpump Load curve at Tsource={sourceT} and Tsink={sinkT}', yTitle='E-load', xTitle='Thermal load in %', colors=recoygreen, asFigure=True, dimensions=(600,400))\n",
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"def cop_curve_new(Tsink, Tsource):\n",
|
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" Tsink += 273\n",
|
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" Tsource += 273\n",
|
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" Tlift = Tsink - Tsource\n",
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"\n",
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" c0 = 0.0005426*Tlift**2 - 0.1178*Tlift + 6.962\n",
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" c1 = 6.7058 \n",
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" c2 = -1.79\n",
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" \n",
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"source": [
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"sourceT = 63 + 273\n",
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"sinkT = 140 + 273\n",
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{
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"cell_type": "code",
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"execution_count": 26,
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"outputs": [],
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"source": [
|
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"heatpump = Heatpump(\n",
|
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" name='Heatpump',\n",
|
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" max_th_power=1,\n",
|
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" min_th_power=0,\n",
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")"
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"outputs": [],
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"source": [
|
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"import itertools\n",
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"\n",
|
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"source_Ts = np.arange(25, 75) + 273\n",
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"sink_Ts = np.arange(80, 170) + 273\n",
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"\n",
|
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"df = pd.DataFrame(columns=list(sink_Ts), index=list(source_Ts))\n",
|
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"for sourceT, sinkT in itertools.product(source_Ts, sink_Ts):\n",
|
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" df.loc[sourceT, sinkT] = heatpump.get_cop(heat_output=0.5, Tsink=sinkT, Tsource=sourceT)\n",
|
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" \n",
|
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]
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},
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{
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"cell_type": "code",
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"metadata": {
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"outputs": [],
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"source": [
|
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"sourceT = 63 + 273\n",
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"sinkT = 140 + 273\n",
|
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"loads = np.arange(0, 1, 0.01)\n",
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"\n",
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"cop_series = pd.Series(index=loads, dtype='float')\n",
|
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"load_series = pd.Series(index=loads, dtype='float')\n",
|
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"for load in loads:\n",
|
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" cop = heatpump.get_cop(heat_output=load, Tsink=sinkT, Tsource=sourceT)\n",
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" cop_series[load] = cop\n",
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" load_series[load] = load / cop "
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"if (notebookContainer) {{\n",
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" x.observe(notebookContainer, {childList: true});\n",
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"}}\n",
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"\n",
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"// Listen for the clearing of the current output cell\n",
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"var outputEl = gd.closest('.output');\n",
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"if (outputEl) {{\n",
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" x.observe(outputEl, {childList: true});\n",
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"}}\n",
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"\n",
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" }) }; }); </script> </div>"
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]
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},
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"metadata": {},
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"cop_series = pd.Series(index=sourceTs, dtype='float')\n",
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|
"\n",
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"for sourceT in sourceTs:\n",
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" cop = heatpump.get_cop(heat_output=load, Tsink=sinkT, Tsource=sourceT + 273)\n",
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" cop_series[sourceT] = cop\n",
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" \n",
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|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"def create_and_assign_assets(c, s):\n",
|
|
" heatpump_vdg = Heatpump(\n",
|
|
" name='Heatpump VDG',\n",
|
|
" max_th_power=c.hp_vdg_e_power,\n",
|
|
" min_th_power=c.hp_vdg_e_power * c.hp_min_load,\n",
|
|
" cop_curve=cop_curve_new\n",
|
|
" )\n",
|
|
"\n",
|
|
" heatpump_ndg = Heatpump(\n",
|
|
" name='Heatpump NDG',\n",
|
|
" max_th_power=c.hp_ndg_e_power,\n",
|
|
" min_th_power=c.hp_ndg_e_power * c.hp_min_load,\n",
|
|
" cop_curve=cop_curve_new\n",
|
|
" )\n",
|
|
"\n",
|
|
" capex_vdg = c.hp_capex*(heatpump_vdg.max_th_power) \n",
|
|
" capex_ndg = c.hp_capex*(heatpump_ndg.max_th_power)\n",
|
|
" heatpump_vdg.set_financials(capex=capex_vdg, opex=c.hp_opex*capex_vdg, devex=c.hp_devex*capex_vdg, lifetime=25)\n",
|
|
" heatpump_ndg.set_financials(capex=capex_ndg, opex=c.hp_opex*capex_ndg, devex=c.hp_devex*capex_ndg, lifetime=25)\n",
|
|
"\n",
|
|
" gasboiler = GasBoiler(\n",
|
|
" name='Gasboiler',\n",
|
|
" max_th_output=c.gb_power,\n",
|
|
" efficiency=c.gb_efficiency\n",
|
|
" )\n",
|
|
" gasboiler.set_financials(capex=0, opex=0, devex=0, lifetime=25)\n",
|
|
" \n",
|
|
" waterstorage = HotWaterStorage(\n",
|
|
" name='HotWaterStorage',\n",
|
|
" rated_power=c.storage_power, \n",
|
|
" capacity_per_volume=c.storage_cap_per_volume,\n",
|
|
" volume=c.storage_volume, \n",
|
|
" temperature=c.storage_temperature,\n",
|
|
" min_storagelevel=c.storage_min_level,\n",
|
|
" # initial_storagelevel=c.storage_initial_level\n",
|
|
" )\n",
|
|
" capex_ws = c.storage_capex_per_MW * waterstorage.max_power + c.storage_capex_per_MWh * waterstorage.capacity\n",
|
|
" opex_ws = c.storage_opex_perc_of_capex * capex_ws\n",
|
|
" waterstorage.set_financials(capex=capex_ws, opex=opex_ws, devex=0, lifetime=c.storage_lifetime)\n",
|
|
" \n",
|
|
" s.baseline.add_asset(gasboiler)\n",
|
|
" s.hpcase.add_asset(heatpump_vdg)\n",
|
|
" s.hpcase.add_asset(heatpump_ndg)\n",
|
|
" s.storage_case_PCM.add_asset(heatpump_vdg)\n",
|
|
" s.storage_case_PCM.add_asset(heatpump_ndg)\n",
|
|
" s.storage_case_PCM.add_asset(waterstorage)\n",
|
|
"# s.hpcase_sde.add_asset(heatpump_vdg)\n",
|
|
"# s.hpcase_sde.add_asset(heatpump_ndg)\n",
|
|
"# s.optcase1.add_asset(heatpump_vdg)\n",
|
|
"# s.optcase1.add_asset(heatpump_ndg)\n",
|
|
"# s.optcase1.add_asset(gasboiler)\n",
|
|
"# s.afrr_case.add_asset(heatpump_vdg)\n",
|
|
"# s.afrr_case.add_asset(heatpump_ndg)\n",
|
|
"# s.afrr_case.add_asset(gasboiler)\n",
|
|
" return s\n",
|
|
"\n",
|
|
"s = create_and_assign_assets(c, s)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 33,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"HotWaterStorage(name=HotWaterStorage, rated_power=25, capacity=50.0, temperature=95, min_storagelevel=2.5)"
|
|
]
|
|
},
|
|
"execution_count": 33,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"s.storage_case_PCM.assets['HotWaterStorage']"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"source": [
|
|
"## Optimization"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"source": [
|
|
"### Strategies"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 34,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"def baseline_sim(case):\n",
|
|
" gasboiler = list(case.assets.values())[0]\n",
|
|
" data = case.data\n",
|
|
" demand = (data['MW (VDG)'] + data['MW (NDG)']).to_list()\n",
|
|
"\n",
|
|
" minutes = iter(range(len(case.data)))\n",
|
|
" th_output = [0] * len(case.data)\n",
|
|
" gas_input = [0] * len(case.data)\n",
|
|
"\n",
|
|
" for m in minutes:\n",
|
|
" th_output[m], gas_input[m] = gasboiler.set_heat_output(demand[m])\n",
|
|
"\n",
|
|
" data['output_MW_th'] = np.array(th_output)\n",
|
|
" data['output_MWh_th'] = np.array(data['output_MW_th']/60)\n",
|
|
" data['gb_input_MW'] = np.array(gas_input)\n",
|
|
" data['gb_input_MWh'] = np.array(data['gb_input_MW']/60)\n",
|
|
" case.data = data.round(5)\n",
|
|
" return case"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 35,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"def hponly(case):\n",
|
|
" hp_vdg = case.assets['Heatpump VDG']\n",
|
|
" hp_ndg = case.assets['Heatpump NDG']\n",
|
|
" demand_vdg = case.data['MW (VDG)'].to_list()\n",
|
|
" demand_ndg = case.data['MW (NDG)'].to_list()\n",
|
|
" Tsink_vdg = case.data['Tsink (VDG)'].to_list()\n",
|
|
" Tsink_ndg = case.data['Tsink (NDG)'].to_list()\n",
|
|
" Tsource_vdg = case.data['Tsource (VDG)'].to_list()\n",
|
|
" Tsource_ndg = case.data['Tsource (NDG)'].to_list()\n",
|
|
"\n",
|
|
" hp_vdg_input = [0] * len(case.data)\n",
|
|
" hp_ndg_input = [0] * len(case.data)\n",
|
|
" hp_vdg_output = [0] * len(case.data)\n",
|
|
" hp_ndg_output = [0] * len(case.data)\n",
|
|
"\n",
|
|
" minutes = iter(range(len(case.data)))\n",
|
|
" for m in minutes:\n",
|
|
" demand = demand_vdg[m]\n",
|
|
" if demand != 0:\n",
|
|
" hp_vdg_input[m], hp_vdg_output[m] = hp_vdg.set_heat_output(\n",
|
|
" heat_output=demand,\n",
|
|
" Tsink=Tsink_vdg[m],\n",
|
|
" Tsource=Tsource_vdg[m]\n",
|
|
" )\n",
|
|
"\n",
|
|
" demand = demand_ndg[m]\n",
|
|
" if demand != 0:\n",
|
|
" hp_ndg_input[m], hp_ndg_output[m] = hp_ndg.set_heat_output(\n",
|
|
" heat_output=demand_ndg[m],\n",
|
|
" Tsink=Tsink_ndg[m],\n",
|
|
" Tsource=Tsource_ndg[m]\n",
|
|
" )\n",
|
|
"\n",
|
|
" case.data['hp_output_MW'] = np.array(hp_vdg_output) + np.array(hp_ndg_output)\n",
|
|
" case.data['hp_input_MW'] = np.array(hp_vdg_input) + np.array(hp_ndg_input)\n",
|
|
" case.data['cop'] = case.data['hp_output_MW'] / -case.data['hp_input_MW']\n",
|
|
" \n",
|
|
" for col in case.data.columns:\n",
|
|
" if col.endswith('MW'):\n",
|
|
" case.data[col + 'h'] = case.data[col] / 60\n",
|
|
"\n",
|
|
" case.data = case.data.round(3)\n",
|
|
" return case"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 36,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"Tref = 0\n",
|
|
"Cp = 4190 #J/kgK\n",
|
|
"MWtoJs = 1000_000\n",
|
|
"\n",
|
|
"def power_to_mass_flow(power_MW, Tsink, Tref, Cp):\n",
|
|
" return power_MW * MWtoJs /(Cp*(Tsink - Tref))\n",
|
|
"def energy_to_storage(hp_heat_output_MW, process_demand_MW):\n",
|
|
" return hp_heat_output_MW - process_demand_MW #MW\n",
|
|
"\n",
|
|
"def Tsource_calculation(Tstorage, discharge_power, Tsource, process_mass_flow): \n",
|
|
" discharge_mass_flow = power_to_mass_flow(discharge_power, Tstorage, Tref, Cp)\n",
|
|
" \n",
|
|
" combined_mass_flow = (discharge_mass_flow + process_mass_flow)\n",
|
|
" if combined_mass_flow == 0:\n",
|
|
" return Tsource\n",
|
|
" else: \n",
|
|
" return (Tstorage * discharge_mass_flow + Tsource * process_mass_flow) / combined_mass_flow"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 37,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"def hp_storage_opt_enginge(c, ws, hp_vdg, hp_ndg, pos, neg, dam, demand_vdg, demand_ndg, tsource_vdg, tsink_vdg, tsource_ndg, tsink_ndg):\n",
|
|
" \n",
|
|
" from_storage_vdg_MW = 0\n",
|
|
" to_storage_vdg_MW = 0 \n",
|
|
" from_storage_ndg_MW = 0\n",
|
|
" to_storage_ndg_MW = 0 \n",
|
|
" \n",
|
|
" if neg < dam - c.threshold:\n",
|
|
" # overproduce\n",
|
|
" if demand_vdg != 0:\n",
|
|
" desired_hp_load_vdg = min(demand_vdg + ws.charging_power_limit, hp_vdg.max_th_power)\n",
|
|
" e_load_vdg, th_load_vdg = hp_vdg.set_heat_output(desired_hp_load_vdg, tsink_vdg, tsource_vdg)\n",
|
|
"\n",
|
|
" to_storage_vdg_MW = th_load_vdg - demand_vdg\n",
|
|
" to_storage_vdg_MW = -ws.charge(round(to_storage_vdg_MW, 3))\n",
|
|
"\n",
|
|
" extra_charging_power_constraint = ws.max_power - to_storage_vdg_MW\n",
|
|
" else:\n",
|
|
" e_load_vdg, th_load_vdg = (0,0)\n",
|
|
" \n",
|
|
" if demand_ndg != 0:\n",
|
|
" desired_hp_load_ndg = min(\n",
|
|
" demand_ndg + min(ws.charging_power_limit, extra_charging_power_constraint), \n",
|
|
" hp_ndg.max_th_power\n",
|
|
" )\n",
|
|
" e_load_ndg, th_load_ndg = hp_ndg.set_heat_output(desired_hp_load_ndg, tsink_ndg, tsource_ndg)\n",
|
|
"\n",
|
|
" to_storage_ndg_MW = th_load_ndg - demand_ndg\n",
|
|
" to_storage_ndg_MW = -ws.charge(round(to_storage_ndg_MW, 3))\n",
|
|
" else:\n",
|
|
" e_load_ndg, th_load_ndg = (0,0)\n",
|
|
" \n",
|
|
"\n",
|
|
" elif pos > dam + c.threshold:\n",
|
|
" # take from storage\n",
|
|
" if demand_vdg != 0:\n",
|
|
" from_process_massflow_vdg = power_to_mass_flow(demand_vdg, tsink_vdg, Tref, Cp)\n",
|
|
" try:\n",
|
|
" from_storage_vdg_MW = ws.discharging_power_limit\n",
|
|
" tsource_vdg = Tsource_calculation(ws.temperature, from_storage_vdg_MW, tsource_vdg, from_process_massflow_vdg)\n",
|
|
" e_load_vdg, th_load_vdg = hp_vdg.set_heat_output(demand_vdg, tsink_vdg, tsource_vdg)\n",
|
|
" except: \n",
|
|
" from_storage_vdg_MW = 0\n",
|
|
" tsource_vdg = Tsource_calculation(ws.temperature, from_storage_vdg_MW, tsource_vdg, from_process_massflow_vdg)\n",
|
|
" e_load_vdg, th_load_vdg = hp_vdg.set_heat_output(demand_vdg, tsink_vdg, tsource_vdg)\n",
|
|
"\n",
|
|
" from_storage_vdg_MW = ws.discharge(round(from_storage_vdg_MW, 3))\n",
|
|
" else:\n",
|
|
" e_load_vdg, th_load_vdg = (0,0)\n",
|
|
" \n",
|
|
" #print({f'from_storage_vdg_MW='})\n",
|
|
" if demand_ndg != 0:\n",
|
|
" from_process_massflow_ndg = power_to_mass_flow(demand_ndg, tsink_ndg, Tref, Cp)\n",
|
|
" \n",
|
|
" try:\n",
|
|
" from_storage_ndg_MW = min(ws.max_power - from_storage_vdg_MW, ws.discharging_power_limit)\n",
|
|
" tsource_ndg = Tsource_calculation(ws.temperature, from_storage_ndg_MW, tsource_ndg, from_process_massflow_ndg)\n",
|
|
" e_load_ndg, th_load_ndg = hp_ndg.set_heat_output(demand_ndg, tsink_ndg, tsource_ndg)\n",
|
|
" except: \n",
|
|
" from_storage_vdg_MW = 0\n",
|
|
" tsource_ndg = Tsource_calculation(ws.temperature, from_storage_ndg_MW, tsource_ndg, from_process_massflow_ndg)\n",
|
|
" e_load_ndg, th_load_ndg = hp_ndg.set_heat_output(demand_ndg, tsink_ndg, tsource_ndg)\n",
|
|
"\n",
|
|
" from_storage_ndg_MW = ws.discharge(round(from_storage_ndg_MW))\n",
|
|
" else:\n",
|
|
" e_load_ndg, th_load_ndg = (0,0)\n",
|
|
" else:\n",
|
|
" e_load_vdg, th_load_vdg = hp_vdg.set_heat_output(\n",
|
|
" heat_output=demand_vdg,\n",
|
|
" Tsink=tsink_vdg,\n",
|
|
" Tsource=tsource_vdg\n",
|
|
" )\n",
|
|
"\n",
|
|
" e_load_ndg, th_load_ndg = hp_ndg.set_heat_output(\n",
|
|
" heat_output=demand_ndg,\n",
|
|
" Tsink=tsink_ndg,\n",
|
|
" Tsource=tsource_ndg\n",
|
|
" )\n",
|
|
" return e_load_vdg, th_load_vdg, e_load_ndg, th_load_ndg, tsource_vdg, tsource_ndg, to_storage_vdg_MW, from_storage_vdg_MW, to_storage_ndg_MW, from_storage_ndg_MW, ws, hp_vdg, hp_ndg\n",
|
|
"# Neg-take price, Pos-feed price"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 38,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"def hponly_with_storage(case):\n",
|
|
" hp_vdg = case.assets['Heatpump VDG']\n",
|
|
" hp_ndg = case.assets['Heatpump NDG']\n",
|
|
" ws = case.assets['HotWaterStorage']\n",
|
|
" demands_vdg = case.data['MW (VDG)'].to_list()\n",
|
|
" demands_ndg = case.data['MW (NDG)'].to_list()\n",
|
|
" Tsink_vdg = case.data['Tsink (VDG)'].to_list()\n",
|
|
" Tsink_ndg = case.data['Tsink (NDG)'].to_list()\n",
|
|
" Tsource_vdg = case.data['Tsource (VDG)'].to_list()\n",
|
|
" Tsource_ndg = case.data['Tsource (NDG)'].to_list()\n",
|
|
" dam_prices = case.data['DAM'].to_list()\n",
|
|
" pos_prices = case.data['POS'].to_list()\n",
|
|
" neg_prices = case.data['NEG'].to_list()\n",
|
|
"\n",
|
|
" hp_vdg_input = [0] * len(case.data)\n",
|
|
" hp_ndg_input = [0] * len(case.data)\n",
|
|
" hp_vdg_output = [0] * len(case.data)\n",
|
|
" hp_ndg_output = [0] * len(case.data)\n",
|
|
"\n",
|
|
" minutes = len(case.data)\n",
|
|
" storage_levels = [None] * minutes\n",
|
|
" to_storage_list = [0] * minutes\n",
|
|
" from_storage_vdg_list = [0] * minutes\n",
|
|
" to_storage_vdg_list = [0] * minutes\n",
|
|
" from_storage_ndg_list = [0] * minutes\n",
|
|
" to_storage_ndg_list = [0] * minutes\n",
|
|
" \n",
|
|
" new_tsources_vdg = case.data['Tsource (VDG)'].to_list()\n",
|
|
" new_tsources_ndg = case.data['Tsource (NDG)'].to_list()\n",
|
|
" \n",
|
|
" ws.set_chargelevel(ws.min_chargelevel)\n",
|
|
" \n",
|
|
" for m in range(minutes):\n",
|
|
" tsource_vdg = Tsource_vdg[m]\n",
|
|
" tsink_vdg = Tsink_vdg[m]\n",
|
|
" tsource_ndg = Tsource_ndg[m]\n",
|
|
" tsink_ndg = Tsink_ndg[m]\n",
|
|
" demand_vdg = demands_vdg[m]\n",
|
|
" demand_ndg = demands_ndg[m]\n",
|
|
" \n",
|
|
" e_load_vdg, th_load_vdg, e_load_ndg, th_load_ndg, tsource_vdg, tsource_ndg, to_storage_vdg_MW, from_storage_vdg_MW, to_storage_ndg_MW, from_storage_ndg_MW, ws, hp_vdg, hp_ndg = hp_storage_opt_enginge(\n",
|
|
" c, ws, hp_vdg, hp_ndg, pos_prices[m], neg_prices[m], dam_prices[m], demand_vdg, demand_ndg, \n",
|
|
" tsource_vdg, tsink_vdg, tsource_ndg, tsink_ndg\n",
|
|
" )\n",
|
|
" \n",
|
|
" hp_vdg_input[m] = e_load_vdg\n",
|
|
" hp_vdg_output[m] = th_load_vdg\n",
|
|
" hp_ndg_input[m] = e_load_ndg\n",
|
|
" hp_ndg_output[m] = th_load_ndg\n",
|
|
" \n",
|
|
" storage_levels[m] = ws.chargelevel\n",
|
|
" new_tsources_vdg[m] = tsource_vdg\n",
|
|
" new_tsources_ndg[m] = tsource_ndg\n",
|
|
" to_storage_vdg_list[m] = to_storage_vdg_MW\n",
|
|
" from_storage_vdg_list[m] = from_storage_vdg_MW\n",
|
|
" to_storage_ndg_list[m] = to_storage_ndg_MW\n",
|
|
" from_storage_ndg_list[m] = from_storage_ndg_MW\n",
|
|
" \n",
|
|
" case.data['hp_output_MW'] = np.array(hp_vdg_output) + np.array(hp_ndg_output)\n",
|
|
" case.data['hp_input_MW'] = np.array(hp_vdg_input) + np.array(hp_ndg_input)\n",
|
|
" case.data['cop'] = case.data['hp_output_MW'] / -case.data['hp_input_MW']\n",
|
|
" case.data['tsource_vdg'] = new_tsources_vdg\n",
|
|
" case.data['tsource_ndg'] = new_tsources_ndg\n",
|
|
" case.data['to_storage_ndg_MW'] = to_storage_ndg_list\n",
|
|
" case.data['from_storage_ndg_MW'] = from_storage_ndg_list\n",
|
|
" case.data['to_storage_vdg_MW'] = to_storage_vdg_list\n",
|
|
" case.data['from_storage_vdg_MW'] = from_storage_vdg_list\n",
|
|
" case.data['to_storage_MW'] = case.data['to_storage_vdg_MW'] + case.data['to_storage_ndg_MW']\n",
|
|
" case.data['from_storage_MW'] = case.data['from_storage_vdg_MW'] + case.data['from_storage_ndg_MW']\n",
|
|
" case.data['storage_level_MWh'] = storage_levels\n",
|
|
" \n",
|
|
" for col in case.data.columns:\n",
|
|
" if col.endswith('MW'):\n",
|
|
" case.data[col + 'h'] = case.data[col] / 60\n",
|
|
"\n",
|
|
" case.data = case.data.round(3)\n",
|
|
" return case\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 39,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# charge_times = print(sum(s.storage_case_PCM.data['to_storage_MW']!= 0))\n",
|
|
"# discharge_times = print(sum(s.storage_case_PCM.data['from_storage_MW']!= 0))\n",
|
|
"# # 154476 times out of 525600, the storage is used to charge/dischage\n",
|
|
"# # from 39 000 to 110 000 discharge time increases\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 40,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"C:\\Users\\shahla.huseynova\\source\\repos\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\assets.py:263: UserWarning:\n",
|
|
"\n",
|
|
"Chosen heat output is out of range [0.0 - 23.3]. Heat output is being limited to the closest boundary.\n",
|
|
"\n",
|
|
"C:\\Users\\shahla.huseynova\\source\\repos\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\assets.py:263: UserWarning:\n",
|
|
"\n",
|
|
"Chosen heat output is out of range [0.0 - 7.7]. Heat output is being limited to the closest boundary.\n",
|
|
"\n"
|
|
]
|
|
},
|
|
{
|
|
"ename": "ValueError",
|
|
"evalue": "cannot convert float NaN to integer",
|
|
"output_type": "error",
|
|
"traceback": [
|
|
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
|
|
"\u001b[1;31mValueError\u001b[0m Traceback (most recent call last)",
|
|
"Cell \u001b[1;32mIn[40], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m s\u001b[38;5;241m.\u001b[39mstorage_case_PCM \u001b[38;5;241m=\u001b[39m \u001b[43mhponly_with_storage\u001b[49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstorage_case_PCM\u001b[49m\u001b[43m)\u001b[49m\n",
|
|
"Cell \u001b[1;32mIn[38], line 41\u001b[0m, in \u001b[0;36mhponly_with_storage\u001b[1;34m(case)\u001b[0m\n\u001b[0;32m 38\u001b[0m demand_vdg \u001b[38;5;241m=\u001b[39m demands_vdg[m]\n\u001b[0;32m 39\u001b[0m demand_ndg \u001b[38;5;241m=\u001b[39m demands_ndg[m]\n\u001b[1;32m---> 41\u001b[0m e_load_vdg, th_load_vdg, e_load_ndg, th_load_ndg, tsource_vdg, tsource_ndg, to_storage_vdg_MW, from_storage_vdg_MW, to_storage_ndg_MW, from_storage_ndg_MW, ws, hp_vdg, hp_ndg \u001b[38;5;241m=\u001b[39m \u001b[43mhp_storage_opt_enginge\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 42\u001b[0m \u001b[43m \u001b[49m\u001b[43mc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mws\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mhp_vdg\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mhp_ndg\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpos_prices\u001b[49m\u001b[43m[\u001b[49m\u001b[43mm\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mneg_prices\u001b[49m\u001b[43m[\u001b[49m\u001b[43mm\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdam_prices\u001b[49m\u001b[43m[\u001b[49m\u001b[43mm\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdemand_vdg\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdemand_ndg\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[0;32m 43\u001b[0m \u001b[43m \u001b[49m\u001b[43mtsource_vdg\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtsink_vdg\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtsource_ndg\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtsink_ndg\u001b[49m\n\u001b[0;32m 44\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 46\u001b[0m hp_vdg_input[m] \u001b[38;5;241m=\u001b[39m e_load_vdg\n\u001b[0;32m 47\u001b[0m hp_vdg_output[m] \u001b[38;5;241m=\u001b[39m th_load_vdg\n",
|
|
"Cell \u001b[1;32mIn[37], line 64\u001b[0m, in \u001b[0;36mhp_storage_opt_enginge\u001b[1;34m(c, ws, hp_vdg, hp_ndg, pos, neg, dam, demand_vdg, demand_ndg, tsource_vdg, tsink_vdg, tsource_ndg, tsink_ndg)\u001b[0m\n\u001b[0;32m 61\u001b[0m tsource_ndg \u001b[38;5;241m=\u001b[39m Tsource_calculation(ws\u001b[38;5;241m.\u001b[39mtemperature, from_storage_ndg_MW, tsource_ndg, from_process_massflow_ndg)\n\u001b[0;32m 62\u001b[0m e_load_ndg, th_load_ndg \u001b[38;5;241m=\u001b[39m hp_ndg\u001b[38;5;241m.\u001b[39mset_heat_output(demand_ndg, tsink_ndg, tsource_ndg)\n\u001b[1;32m---> 64\u001b[0m from_storage_ndg_MW \u001b[38;5;241m=\u001b[39m ws\u001b[38;5;241m.\u001b[39mdischarge(\u001b[38;5;28;43mround\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mfrom_storage_ndg_MW\u001b[49m\u001b[43m)\u001b[49m)\n\u001b[0;32m 65\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m 66\u001b[0m e_load_ndg, th_load_ndg \u001b[38;5;241m=\u001b[39m (\u001b[38;5;241m0\u001b[39m,\u001b[38;5;241m0\u001b[39m)\n",
|
|
"\u001b[1;31mValueError\u001b[0m: cannot convert float NaN to integer"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"s.storage_case_PCM = hponly_with_storage(s.storage_case_PCM)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"s.storage_case_PCM.data.sample(2)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"s.storage_case_PCM.data[['DAM', 'POS', 'NEG', 'hp_output_MW', 'to_storage_MW', 'Total demand']].describe()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"s.storage_case_PCM.data[['DAM', 'POS', 'NEG', 'hp_output_MW', 'to_storage_MW', 'from_storage_MW','Total demand']].sample(20)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"s.hpcase.data.columns"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"s.storage_case_PCM.data.columns"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# hp_selection = s.hpcase.data[['DAM', 'POS', 'NEG', 'hp_input_MW', 'hp_output_MW', 'cop', 'Total demand']]\n",
|
|
"hp_selection = s.hpcase.data[['DAM', 'POS', 'NEG', 'Total demand']]\n",
|
|
"storage_selection = s.storage_case_PCM.data[['hp_input_MW', 'hp_output_MW', 'cop', 'to_storage_MW', 'from_storage_MW']]\n",
|
|
"\n",
|
|
"selection = pd.concat([hp_selection, storage_selection], axis=1)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"selection.sample(20)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"selection.mean()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"########################\n",
|
|
"\n",
|
|
"# This is where we left\n",
|
|
"\n",
|
|
"########################"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"def cost_function(th_load, cop, electricity_cost, alt_heat_price, demand):\n",
|
|
" return (\n",
|
|
" th_load / cop * electricity_cost\n",
|
|
" + (demand - th_load) * alt_heat_price\n",
|
|
" )"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"def hybrid_imb_optimisation(case, decimals, s):\n",
|
|
" gb = case.assets['Gasboiler']\n",
|
|
" hp_vdg = case.assets['Heatpump VDG']\n",
|
|
" hp_ndg = case.assets['Heatpump NDG']\n",
|
|
" demand_vdg = case.data['MW (VDG)'].round(decimals).to_list()\n",
|
|
" demand_ndg = case.data['MW (NDG)'].round(decimals).to_list()\n",
|
|
" Tsink_vdg = case.data['Tsink (VDG)'].round(decimals).to_list()\n",
|
|
" Tsink_ndg = case.data['Tsink (NDG)'].round(decimals).to_list()\n",
|
|
" Tsource_vdg = case.data['Tsource (VDG)'].round(decimals).to_list()\n",
|
|
" Tsource_ndg = case.data['Tsource (NDG)'].round(decimals).to_list()\n",
|
|
" fore_neg = case.data[c.forecast].fillna(999).round(decimals).to_list()\n",
|
|
" gas_prices = case.data['Gas prices (€/MWh)'].round(decimals).to_list()\n",
|
|
" co2_prices = case.data['CO2 prices (€/MWh)'].round(decimals).to_list()\n",
|
|
" eb_ode_g = s.eb_ode_g\n",
|
|
" eb_ode_e = s.eb_ode_e\n",
|
|
" \n",
|
|
" gb_input = [0] * len(case.data)\n",
|
|
" gb_output = [0] * len(case.data)\n",
|
|
"\n",
|
|
" minutes = range(len(case.data))\n",
|
|
" hp_output = [0] * len(case.data)\n",
|
|
" hp_input = [0] * len(case.data)\n",
|
|
"\n",
|
|
" for m in tqdm(minutes):\n",
|
|
" dem_vgd = demand_vdg[m]\n",
|
|
" if dem_vgd != 0:\n",
|
|
" max_load = min(hp_vdg.max_th_power, dem_vgd)\n",
|
|
" min_load = hp_vdg.min_th_power\n",
|
|
" Tsink = Tsink_vdg[m]\n",
|
|
" Tsource = Tsource_vdg[m]\n",
|
|
" cop_max_load = hp_vdg.get_cop(heat_output=max_load, Tsink=Tsink, Tsource=Tsource)\n",
|
|
" cop_min_load = hp_vdg.get_cop(heat_output=min_load, Tsink=Tsink_vdg[m], Tsource=Tsource_vdg[m])\n",
|
|
" \n",
|
|
" cost_full_load = cost_function(\n",
|
|
" th_load=max_load,\n",
|
|
" cop=cop_max_load,\n",
|
|
" electricity_cost=fore_neg[m] + eb_ode_e - c.sde_switch_price_correction,\n",
|
|
" alt_heat_price=gas_prices[m] + co2_prices[m] + eb_ode_g/case.assets['Gasboiler'].efficiency,\n",
|
|
" demand=dem_vgd\n",
|
|
" )\n",
|
|
" \n",
|
|
" cost_min_load = cost_function(\n",
|
|
" th_load=min_load,\n",
|
|
" cop=cop_min_load,\n",
|
|
" electricity_cost=fore_neg[m] + eb_ode_e,\n",
|
|
" alt_heat_price=gas_prices[m] + co2_prices[m] + eb_ode_g/case.assets['Gasboiler'].efficiency,\n",
|
|
" demand=dem_vgd\n",
|
|
" )\n",
|
|
" \n",
|
|
" if cost_full_load < cost_min_load:\n",
|
|
" hp_vdg_input, hp_vdg_output = hp_vdg.set_heat_output(max_load, Tsink, Tsource)\n",
|
|
" else:\n",
|
|
" hp_vdg_input, hp_vdg_output = hp_vdg.set_heat_output(min_load, Tsink, Tsource)\n",
|
|
" else:\n",
|
|
" hp_vdg_input, hp_vdg_output = (0, 0)\n",
|
|
"\n",
|
|
" dem_ngd = demand_ndg[m]\n",
|
|
" if dem_ngd != 0:\n",
|
|
" max_load = min(hp_ndg.max_th_power, dem_ngd)\n",
|
|
" min_load = hp_ndg.min_th_power\n",
|
|
" Tsink = Tsink_ndg[m]\n",
|
|
" Tsource = Tsource_ndg[m]\n",
|
|
" cop_max_load = hp_ndg.get_cop(heat_output=max_load, Tsink=Tsink, Tsource=Tsource)\n",
|
|
" cop_min_load = hp_ndg.get_cop(heat_output=min_load, Tsink=Tsink, Tsource=Tsource)\n",
|
|
" \n",
|
|
" cost_full_load = cost_function(\n",
|
|
" th_load=max_load,\n",
|
|
" cop=cop_max_load,\n",
|
|
" electricity_cost=fore_neg[m] + eb_ode_e,\n",
|
|
" alt_heat_price=gas_prices[m] + co2_prices[m] + eb_ode_g/case.assets['Gasboiler'].efficiency,\n",
|
|
" demand=dem_ngd\n",
|
|
" )\n",
|
|
" \n",
|
|
" cost_min_load = cost_function(\n",
|
|
" th_load=min_load,\n",
|
|
" cop=cop_min_load,\n",
|
|
" electricity_cost=fore_neg[m] + eb_ode_e,\n",
|
|
" alt_heat_price=gas_prices[m] + co2_prices[m] + eb_ode_g/case.assets['Gasboiler'].efficiency,\n",
|
|
" demand=dem_vgd\n",
|
|
" )\n",
|
|
" \n",
|
|
" if cost_full_load <= cost_min_load:\n",
|
|
" hp_ndg_input, hp_ndg_output = hp_ndg.set_heat_output(max_load, Tsink=Tsink, Tsource=Tsource)\n",
|
|
" else:\n",
|
|
" hp_ndg_input, hp_ndg_output = hp_ndg.set_heat_output(min_load, Tsink=Tsink, Tsource=Tsource)\n",
|
|
" else:\n",
|
|
" hp_ndg_input, hp_ndg_output = (0, 0)\n",
|
|
"\n",
|
|
" hp_out = hp_vdg_output + hp_ndg_output\n",
|
|
" hp_output[m] = hp_out\n",
|
|
" hp_input[m] = hp_vdg_input + hp_ndg_input\n",
|
|
" remaining_demand = max(dem_vgd+dem_ngd-hp_out, 0)\n",
|
|
" gb_output[m], gb_input[m] = gb.set_heat_output(remaining_demand)\n",
|
|
"\n",
|
|
" case.data['hp_output_MW'] = np.array(hp_output)\n",
|
|
" case.data['hp_input_MW'] = np.array(hp_input)\n",
|
|
" case.data['gb_output_MW'] = np.array(gb_output)\n",
|
|
" case.data['gb_input_MW'] = np.array(gb_input)\n",
|
|
"\n",
|
|
" for col in case.data.columns:\n",
|
|
" if col.endswith('MW'):\n",
|
|
" case.data[col + 'h'] = case.data[col] / 60\n",
|
|
"\n",
|
|
" case.data = case.data.round(5)\n",
|
|
" return case"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"source": [
|
|
"aFRR\n",
|
|
"* Bid in a volume (X MW) --> Strategy is to only bid in on aFRR down\n",
|
|
"* Remaining demand is filed in by gasboiler\n",
|
|
"* Bid price at switch price?\n",
|
|
"* Assume direct response to 0% for now?\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"def calc_afrr_capacity(case):\n",
|
|
" hp_vdg = case.assets['Heatpump VDG']\n",
|
|
" hp_ndg = case.assets['Heatpump NDG']\n",
|
|
" \n",
|
|
" capacity = 0\n",
|
|
" for hp in [hp_vdg, hp_ndg]:\n",
|
|
" max_th_output = hp.max_th_power\n",
|
|
" cop = hp.get_cop(max_th_output, Tsink=135, Tsource=60)\n",
|
|
" e_power = max_th_output / cop\n",
|
|
" capacity += e_power\n",
|
|
" return capacity"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"def aFRR_optimisation(case, s):\n",
|
|
" s.afrr_case.afrr_capacity = calc_afrr_capacity(s.afrr_case)\n",
|
|
" gb = case.assets['Gasboiler']\n",
|
|
" hp_vdg = case.assets['Heatpump VDG']\n",
|
|
" hp_ndg = case.assets['Heatpump NDG']\n",
|
|
" demand_vdg = case.data['MW (VDG)'].to_list()\n",
|
|
" demand_ndg = case.data['MW (NDG)'].to_list()\n",
|
|
" Tsink_vdg = case.data['Tsink (VDG)'].to_list()\n",
|
|
" Tsink_ndg = case.data['Tsink (NDG)'].to_list()\n",
|
|
" Tsource_vdg = case.data['Tsource (VDG)'].to_list()\n",
|
|
" Tsource_ndg = case.data['Tsource (NDG)'].to_list()\n",
|
|
" afrr_up = case.data['Hoogste_prijs_opregelen'].fillna(-999).to_list()\n",
|
|
" gas_prices = case.data['Gas prices (€/MWh)'].to_list()\n",
|
|
" co2_prices = case.data['CO2 prices (€/MWh)'].to_list()\n",
|
|
" eb_ode_g = s.eb_ode_g\n",
|
|
" eb_ode_e = s.eb_ode_e\n",
|
|
" \n",
|
|
" gb_input = [0] * len(case.data)\n",
|
|
" gb_output = [0] * len(case.data)\n",
|
|
"\n",
|
|
" minutes = range(len(case.data))\n",
|
|
" hp_output = [0] * len(case.data)\n",
|
|
" hp_input = [0] * len(case.data)\n",
|
|
"\n",
|
|
" for m in tqdm(minutes):\n",
|
|
" dem_vgd = demand_vdg[m]\n",
|
|
" if dem_vgd != 0:\n",
|
|
" max_load = min(hp_vdg.max_th_power, dem_vgd)\n",
|
|
" min_load = hp_vdg.min_th_power\n",
|
|
" Tsink = Tsink_vdg[m]\n",
|
|
" Tsource = Tsource_vdg[m]\n",
|
|
" cop_max_load = hp_vdg.get_cop(heat_output=max_load, Tsink=Tsink, Tsource=Tsource)\n",
|
|
" cop_min_load = hp_vdg.get_cop(heat_output=min_load, Tsink=Tsink_vdg[m], Tsource=Tsource_vdg[m])\n",
|
|
" \n",
|
|
" cost_full_load = cost_function(\n",
|
|
" th_load=max_load,\n",
|
|
" cop=cop_max_load,\n",
|
|
" electricity_cost=afrr_up[m] + eb_ode_e - c.sde_switch_price_correction,\n",
|
|
" alt_heat_price=gas_prices[m] + co2_prices[m] + eb_ode_g/case.assets['Gasboiler'].efficiency,\n",
|
|
" demand=dem_vgd\n",
|
|
" )\n",
|
|
" \n",
|
|
" cost_min_load = cost_function(\n",
|
|
" th_load=min_load,\n",
|
|
" cop=cop_min_load,\n",
|
|
" electricity_cost=afrr_up[m] + eb_ode_e,\n",
|
|
" alt_heat_price=gas_prices[m] + co2_prices[m] + eb_ode_g/case.assets['Gasboiler'].efficiency,\n",
|
|
" demand=dem_vgd\n",
|
|
" )\n",
|
|
" \n",
|
|
" if cost_full_load < cost_min_load:\n",
|
|
" hp_vdg_input, hp_vdg_output = hp_vdg.set_heat_output(max_load, Tsink, Tsource)\n",
|
|
" else:\n",
|
|
" hp_vdg_input, hp_vdg_output = hp_vdg.set_heat_output(min_load, Tsink, Tsource)\n",
|
|
" else:\n",
|
|
" hp_vdg_input, hp_vdg_output = (0, 0)\n",
|
|
"\n",
|
|
" dem_ngd = demand_ndg[m]\n",
|
|
" if dem_ngd != 0:\n",
|
|
" max_load = min(hp_ndg.max_th_power, dem_ngd)\n",
|
|
" min_load = hp_ndg.min_th_power\n",
|
|
" Tsink = Tsink_ndg[m]\n",
|
|
" Tsource = Tsource_ndg[m]\n",
|
|
" cop_max_load = hp_ndg.get_cop(heat_output=max_load, Tsink=Tsink, Tsource=Tsource)\n",
|
|
" cop_min_load = hp_ndg.get_cop(heat_output=min_load, Tsink=Tsink, Tsource=Tsource)\n",
|
|
" \n",
|
|
" cost_full_load = cost_function(\n",
|
|
" th_load=max_load,\n",
|
|
" cop=cop_max_load,\n",
|
|
" electricity_cost=afrr_up[m] + eb_ode_e,\n",
|
|
" alt_heat_price=gas_prices[m] + co2_prices[m] + eb_ode_g/case.assets['Gasboiler'].efficiency,\n",
|
|
" demand=dem_ngd\n",
|
|
" )\n",
|
|
" \n",
|
|
" cost_min_load = cost_function(\n",
|
|
" th_load=min_load,\n",
|
|
" cop=cop_min_load,\n",
|
|
" electricity_cost=afrr_up[m] + eb_ode_e,\n",
|
|
" alt_heat_price=gas_prices[m] + co2_prices[m] + eb_ode_g/case.assets['Gasboiler'].efficiency,\n",
|
|
" demand=dem_vgd\n",
|
|
" )\n",
|
|
" \n",
|
|
" if cost_full_load <= cost_min_load:\n",
|
|
" hp_ndg_input, hp_ndg_output = hp_ndg.set_heat_output(max_load, Tsink=Tsink, Tsource=Tsource)\n",
|
|
" else:\n",
|
|
" hp_ndg_input, hp_ndg_output = hp_ndg.set_heat_output(min_load, Tsink=Tsink, Tsource=Tsource)\n",
|
|
" else:\n",
|
|
" hp_ndg_input, hp_ndg_output = (0, 0)\n",
|
|
"\n",
|
|
" hp_out = hp_vdg_output + hp_ndg_output\n",
|
|
" hp_output[m] = hp_out\n",
|
|
" hp_input[m] = hp_vdg_input + hp_ndg_input\n",
|
|
" remaining_demand = max(dem_vgd+dem_ngd-hp_out, 0)\n",
|
|
" gb_output[m], gb_input[m] = gb.set_heat_output(remaining_demand)\n",
|
|
"\n",
|
|
" case.data['hp_output_MW'] = np.array(hp_output)\n",
|
|
" case.data['hp_input_MW'] = np.array(hp_input)\n",
|
|
" case.data['gb_output_MW'] = np.array(gb_output)\n",
|
|
" case.data['gb_input_MW'] = np.array(gb_input)\n",
|
|
"\n",
|
|
" for col in case.data.columns:\n",
|
|
" if col.endswith('MW'):\n",
|
|
" case.data[col + 'h'] = case.data[col] / 60\n",
|
|
"\n",
|
|
" case.data = case.data.round(5)\n",
|
|
" return case"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"source": [
|
|
"### Run optimisation"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"def run_optimisation(c, s):\n",
|
|
" s.baseline = baseline_sim(s.baseline)\n",
|
|
" s.hpcase = hponly(s.hpcase)\n",
|
|
" s.storage_case_PCM = hponly_with_storage(s.storage_case_PCM)\n",
|
|
"# s.hpcase_sde.assign_algorithm(hponly)\n",
|
|
"# s.hpcase_sde.run()\n",
|
|
" \n",
|
|
"# s.optcase1.assign_algorithm(hybrid_imb_optimisation)\n",
|
|
"# s.optcase1.run(decimals=2, s=s)\n",
|
|
" \n",
|
|
"# s.afrr_case.assign_algorithm(aFRR_optimisation)\n",
|
|
"# s.afrr_case.run(s=s)\n",
|
|
" \n",
|
|
" for case in [s.hpcase, s.storage_case_PCM]: # [s.hpcase, s.hpcase_sde, s.optcase1, s.afrr_case]:\n",
|
|
" case.mean_cop = case.data['hp_output_MW'].sum() / case.data['hp_input_MW'].abs().sum()\n",
|
|
" \n",
|
|
" return s\n",
|
|
"\n",
|
|
"s = run_optimisation(c, s)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"s.hpcase.data['hp_output_MW'].sum() /s.hpcase.data['hp_input_MW'].abs().sum() "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"s.storage_case_PCM.data['hp_output_MW'].sum() /s.storage_case_PCM.data['hp_input_MW'].abs().sum() "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"s.hpcase.data.head()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"vis_data = s.storage_case_PCM.data[[\n",
|
|
" 'storage_level_MWh', \n",
|
|
" #'to_storage_ndg_MW', \n",
|
|
" #'to_storage_vdg_MW', \n",
|
|
" 'to_storage_MW', \n",
|
|
" #'from_storage_ndg_MW', \n",
|
|
" #'from_storage_vdg_MW',\n",
|
|
" 'from_storage_MW'\n",
|
|
"]]\n",
|
|
"\n",
|
|
"cops = pd.concat([s.hpcase.data['cop'], s.storage_case_PCM.data['cop']], axis=1)\n",
|
|
"vis_data = pd.concat([vis_data, cops], axis=1)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"vis_data.loc['2023-01-01', :].iplot(subplots=True, shape=(5,1), dimensions=(1000, 800))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"total_to_storage = s.storage_case_PCM.data['to_storage_MWh'].sum()\n",
|
|
"total_from_storage = s.storage_case_PCM.data['from_storage_MWh'].sum()\n",
|
|
"total_to_storage, total_from_storage"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"s.storage_case_PCM.data.columns"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"hp_output = s.storage_case_PCM.data['hp_output_MW'].round(2)\n",
|
|
"demand_and_to_storage = (s.storage_case_PCM.data['Total demand'] + s.storage_case_PCM.data['to_storage_MW']).round(2)\n",
|
|
"hp_output.equals(demand_and_to_storage)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"pd.concat([hp_output, demand_and_to_storage], axis=1).resample('H').sum().iplot()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"source": [
|
|
"## Financials"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"def calculate_sde_subsidy(c, s, case):\n",
|
|
" hp_capacity = abs(case.assets['Heatpump VDG'].max_th_power) + abs(case.assets['Heatpump NDG'].max_th_power)\n",
|
|
" case.full_load_hours = abs(case.data['hp_output_MWh'].sum() / hp_capacity)\n",
|
|
"\n",
|
|
" subsidized_hours = min(case.full_load_hours, 8000)\n",
|
|
" subsidized_MWh = subsidized_hours * hp_capacity\n",
|
|
"\n",
|
|
" base_amount_per_MWh_th = round(c.sde_base_amount*0.173 + c.longterm_gas_price, 2)\n",
|
|
" base_subsidy_amount = round(base_amount_per_MWh_th * subsidized_MWh, 2)\n",
|
|
" long_term_gas_price_LHV = round(EURperHHV_to_EURperLHV(c.longterm_gas_price), 2)\n",
|
|
" base_amount_gas = (2/3)*long_term_gas_price_LHV*0.9\n",
|
|
" mean_ttf_price_LHV = round(EURperHHV_to_EURperLHV(case.data['Gas prices (€/MWh)'].mean()), 2)\n",
|
|
" correction_amount_gas = max(mean_ttf_price_LHV, base_amount_gas)\n",
|
|
" avoided_gas_consumption = subsidized_MWh/0.9\n",
|
|
" correction_gas = round(correction_amount_gas * avoided_gas_consumption, 2)\n",
|
|
"\n",
|
|
" base_amount_co2 = (2/3)*c.longterm_co2_price\n",
|
|
" avoided_co2_emission = avoided_gas_consumption * 0.226\n",
|
|
" mean_ets_price = round(EURperHHV_to_EURperLHV(case.data['CO2 prices (€/ton)'].mean()), 2)\n",
|
|
" correction_amount_co2 = max(base_amount_co2, mean_ets_price)\n",
|
|
" correction_co2 = round(correction_amount_co2 * avoided_co2_emission, 2)\n",
|
|
"\n",
|
|
" sde_subsidy_corrected = max(base_subsidy_amount - (correction_gas + correction_co2), 0)\n",
|
|
" sde_per_MWh_th = sde_subsidy_corrected / subsidized_MWh\n",
|
|
" sde_per_MWh_e = sde_subsidy_corrected / case.data['hp_input_MWh'].abs().sum()\n",
|
|
"\n",
|
|
" case.sde_results = {\n",
|
|
" 'base_amount': base_subsidy_amount,\n",
|
|
" 'correction_gas': correction_gas,\n",
|
|
" 'correction_co2': correction_co2,\n",
|
|
" 'corrected_amount': sde_subsidy_corrected,\n",
|
|
" 'sde_per_MWh_th': sde_per_MWh_th,\n",
|
|
" 'sde_per_MWh_e': sde_per_MWh_e\n",
|
|
" }\n",
|
|
" return case"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"s.storage_case_PCM.data.columns"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"def collect_cashflows(c, s):\n",
|
|
" s.hpcase.generate_electr_market_results(nom_col='hp_input_MWh', real_col='hp_input_MWh')\n",
|
|
" s.storage_case_PCM.data['nomination_MWh'] = s.hpcase.data['hp_input_MWh']\n",
|
|
" s.storage_case_PCM.generate_electr_market_results(nom_col='nomination_MWh', real_col='hp_input_MWh')\n",
|
|
"\n",
|
|
"# s.hpcase_sde.generate_electr_market_results(nom_col='hp_input_MWh', real_col='hp_input_MWh')\n",
|
|
" \n",
|
|
"# s.optcase1.data['DA Nom'] = s.hpcase.data['hp_input_MWh'] * c.day_ahead_buying_perc\n",
|
|
"# s.optcase1.generate_electr_market_results(nom_col='DA Nom', real_col='hp_input_MWh')\n",
|
|
" \n",
|
|
"# s.afrr_case.data['POS'] = s.afrr_case.data['aFRR_up'].fillna(value=s.afrr_case.data['POS'])\n",
|
|
"# s.afrr_case.data['DA Nom'] = s.hpcase.data['hp_input_MWh']\n",
|
|
"# s.afrr_case.generate_electr_market_results(nom_col='DA Nom', real_col='hp_input_MWh')\n",
|
|
"# s.afrr_case.add_cashflow('aFRR capacity fee (€)', c.afrr_capacity_fee * s.afrr_case.afrr_capacity)\n",
|
|
" \n",
|
|
" for case in [s.baseline]: #, s.optcase1, s.afrr_case]:\n",
|
|
" case.add_gas_costs(gasvolumes_col='gb_input_MWh')\n",
|
|
" case.add_co2_costs(volume_cols='gb_input_MWh', fuel='gas')\n",
|
|
" case.add_eb_ode(commodity='gas', tax_bracket=c.tax_bracket_g)\n",
|
|
" \n",
|
|
" for case in [s.hpcase, s.storage_case_PCM]: #, s.hpcase_sde, s.optcase1, s.afrr_case]:\n",
|
|
" \n",
|
|
" case.add_eb_ode(commodity='electricity', tax_bracket=c.tax_bracket_e, cons_col='hp_input_MWh')\n",
|
|
" case.add_grid_costs(\n",
|
|
" power_MW_col='hp_input_MW',\n",
|
|
" grid_operator=c.grid_operator,\n",
|
|
" year=2020, \n",
|
|
" connection_type=c.connection_type\n",
|
|
" )\n",
|
|
" \n",
|
|
" for case in s.sde_cases:\n",
|
|
" case = calculate_sde_subsidy(c=c, s=s, case=case)\n",
|
|
" case.add_cashflow('SDE++ subsidy (€)', case.sde_results['corrected_amount'])\n",
|
|
" return s\n",
|
|
"\n",
|
|
"s = collect_cashflows(c, s)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"def calculate_financials(c, s):\n",
|
|
" for case in s.cases:\n",
|
|
" case.calculate_ebitda(c.project_duration)\n",
|
|
"\n",
|
|
" for case in [s.hpcase, s.storage_case_PCM]: #, s.hpcase_sde, s.optcase1, s.afrr_case]:\n",
|
|
" case.calculate_business_case(\n",
|
|
" project_duration=c.project_duration, \n",
|
|
" discount_rate=c.discount_rate, \n",
|
|
" baseline=s.baseline\n",
|
|
" )\n",
|
|
" \n",
|
|
" return s\n",
|
|
"\n",
|
|
"s = calculate_financials(c, s)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"source": [
|
|
"## Visualisations"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"fig_demands_over_time = s.demand['Total demand'].resample('H').mean().iplot(\n",
|
|
" title='Smurfit Kappa: Heat demand by Hour in MW', \n",
|
|
" yTitle='MW', \n",
|
|
" colors=recoygreen,\n",
|
|
" asFigure=True,\n",
|
|
" dimensions=(800, 400)\n",
|
|
")\n",
|
|
"fig_demands_over_time"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"demands_fig = s.demand[['Tsource (VDG)', 'Tsink (VDG)', 'Tsource (NDG)', 'Tsink (NDG)']].resample('H').mean().iplot(\n",
|
|
" kind='box',\n",
|
|
" title='Smurfit Kappa: Source and Sink temperatures',\n",
|
|
" color=recoygreen,\n",
|
|
" yTitle='Temperature in degrees C',\n",
|
|
" legend=False,\n",
|
|
" asFigure=True,\n",
|
|
" dimensions=(800, 400)\n",
|
|
")\n",
|
|
"demands_fig"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"s.storage_case_PCM.data.columns"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"temp_comparison = pd.concat([s.storage_case_PCM.data[['tsource_ndg', 'tsource_vdg']], s.storage_case_PCM.data[['Tsource (NDG)', 'Tsource (VDG)']]], axis=1)\n",
|
|
"temp_comparison.columns = ['Tsource (NDG) -after', 'Tsource (VDG) - after', 'Tsource (NDG) - before', 'Tsource (VDG) - before']\n",
|
|
"temp_comparison.resample('15T').mean().iplot()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"s.storage_case_PCM.data[['tsource_ndg', 'tsource_vdg']].idxmin()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# s.storage_case_PCM.data.loc['2019-01-04 07:45:00']"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"case = s.storage_case_PCM\n",
|
|
"hp_vdg = case.assets['Heatpump VDG']\n",
|
|
"hp_ndg = case.assets['Heatpump NDG']\n",
|
|
"ws = case.assets['HotWaterStorage']\n",
|
|
"ws.storage_level = 47.083 + 25\n",
|
|
"pos = 35.650\n",
|
|
"neg = 43.850\n",
|
|
"dam = 68.400\n",
|
|
"demand_vdg = 0\n",
|
|
"demand_ndg = 0\n",
|
|
"tsource_vdg = 29.635\n",
|
|
"tsink_vdg = 134.840\n",
|
|
"tsource_ndg = 21.420\n",
|
|
"tsink_ndg = 118.755\n",
|
|
"\n",
|
|
"hp_storage_opt_enginge(c, ws, hp_vdg, hp_ndg, pos, neg, dam, demand_vdg, demand_ndg, tsource_vdg, tsink_vdg, tsource_ndg, tsink_ndg)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"#e_load_vdg, th_load_vdg, e_load_ndg, th_load_ndg, tsource_vdg, tsource_ndg, to_storage_vdg_MW, from_storage_vdg_MW, to_storage_ndg_MW, from_storage_ndg_MW, ws, hp_vdg, hp_ndg"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"Tsource_VDG_before = s.hpcase.data['Tsource (VDG)'].round(2)\n",
|
|
"Tsource_VDG_after = s.storage_case_PCM.data['Tsource (VDG)'].round(2)\n",
|
|
"Tsource_VDG_before.equals(Tsource_VDG_after)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"Tsource_NDG_before = s.hpcase.data['Tsource (NDG)'].round(2)\n",
|
|
"Tsource_NDG_after = s.storage_case_PCM.data['Tsource (NDG)'].round(2)\n",
|
|
"Tsource_NDG_before.equals(Tsource_NDG_after)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"test_hp = Heatpump(\n",
|
|
" name='Heatpump for Testing',\n",
|
|
" max_th_power=1,\n",
|
|
" min_th_power=0.3,\n",
|
|
" cop_curve=cop_curve\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"# Tsrc_vdg, Tsnk_vdg, Tsrc_ndg, Tsnk_ndg = s.demand[['Tsource (VDG)', 'Tsink (VDG)', 'Tsource (NDG)', 'Tsink (NDG)']].mean().to_list()\n",
|
|
"# mean_gas_price = (s.optcase1.data['Gas prices (€/MWh)'].mean() \n",
|
|
"# + s.eb_ode_g \n",
|
|
"# + s.optcase1.data['CO2 prices (€/MWh)'].mean()\n",
|
|
"# )\n",
|
|
"\n",
|
|
"# max_gas_price = (s.optcase1.data['Gas prices (€/MWh)'].max() \n",
|
|
"# + s.eb_ode_g \n",
|
|
"# + s.optcase1.data['CO2 prices (€/MWh)'].max()\n",
|
|
"# )\n",
|
|
"\n",
|
|
"# min_gas_price = (s.optcase1.data['Gas prices (€/MWh)'].min() \n",
|
|
"# + s.eb_ode_g \n",
|
|
"# + s.optcase1.data['CO2 prices (€/MWh)'].min()\n",
|
|
"# )\n",
|
|
"\n",
|
|
"# Tsrc_vdg_min, Tsnk_vdg_min, Tsrc_ndg_min, Tsnk_ndg_min = s.demand[['Tsource (VDG)', 'Tsink (VDG)', 'Tsource (NDG)', 'Tsink (NDG)']].min().to_list()\n",
|
|
"# Tsrc_vdg_max, Tsnk_vdg_max, Tsrc_ndg_max, Tsnk_ndg_max = s.demand[['Tsource (VDG)', 'Tsink (VDG)', 'Tsource (NDG)', 'Tsink (NDG)']].max().to_list()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import plotly.graph_objs as go\n",
|
|
"def create_load_trace(gas_price, Tsnk, Tsrc, name):\n",
|
|
" loads = []\n",
|
|
" eprices = list(range(1000))\n",
|
|
" for eprice in eprices:\n",
|
|
" _, load = test_hp.set_opt_load(\n",
|
|
" electricity_cost=eprice + s.eb_ode_e,\n",
|
|
" alt_heat_price=gas_price / 0.9,\n",
|
|
" demand=1, \n",
|
|
" Tsink=Tsnk,\n",
|
|
" Tsource=Tsrc\n",
|
|
" )\n",
|
|
" loads.append(load)\n",
|
|
" trace = go.Scatter(x=eprices, y=loads, name=name)\n",
|
|
" return trace"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"# import plotly.graph_objects as go\n",
|
|
"# import numpy as np\n",
|
|
"\n",
|
|
"# fig = go.Figure()\n",
|
|
"\n",
|
|
"# configs = {\n",
|
|
"# 'mean': [mean_gas_price, Tsnk_vdg, Tsrc_vdg],\n",
|
|
"# 'unfav_gas': [min_gas_price, Tsnk_vdg, Tsrc_vdg],\n",
|
|
"# 'fav_gas': [max_gas_price, Tsnk_vdg, Tsrc_vdg],\n",
|
|
"# 'unfav_all': [min_gas_price, Tsnk_vdg_max, Tsrc_vdg_min],\n",
|
|
"# 'fav_all': [max_gas_price, Tsnk_vdg_min, Tsrc_vdg_max],\n",
|
|
"# }\n",
|
|
"\n",
|
|
"# for name, config in configs.items():\n",
|
|
"# trace = create_load_trace(*config, name)\n",
|
|
"# fig.add_trace(trace)\n",
|
|
"\n",
|
|
"# fig.update_layout(title='Switch prices for different configurations')\n",
|
|
"# fig.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"date = s.baseline.data.index[0].strftime('%Y-%m-%d')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"fig_steamboiler = s.baseline.data[['Total demand', 'output_MW_th']].abs().loc[date, :].iplot(\n",
|
|
" subplots=True, \n",
|
|
" title=f'Steamboiler only case on {date}',\n",
|
|
" subplot_titles=['Total demand', 'Steam boiler output (MW)'],\n",
|
|
" legend=False,\n",
|
|
" dimensions=(800, 400),\n",
|
|
" colors=[recoydarkblue, recoygreen], \n",
|
|
" asFigure=True,\n",
|
|
" shape = (2, 1)\n",
|
|
")\n",
|
|
"fig_steamboiler"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"fig_heatpump = s.hpcase.data[['Total demand', 'hp_output_MW']].abs().loc[date, :].iplot(\n",
|
|
" subplots=True, \n",
|
|
" title=f'Heatpump only case on {date}', \n",
|
|
" subplot_titles=['Total demand', 'Heatpump output (MW)'],\n",
|
|
" legend=False,\n",
|
|
" dimensions=(800, 400),\n",
|
|
" colors=[recoydarkblue, recoygreen], \n",
|
|
" asFigure=True,\n",
|
|
" shape = (2, 1)\n",
|
|
")\n",
|
|
"fig_heatpump"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"# fig_optcase = s.optcase1.data[['hp_output_MW', 'gb_output_MW', 'NEG']].loc[date, :].iplot(\n",
|
|
"# subplots=True, \n",
|
|
"# title=f'Hybrid case on {date}',\n",
|
|
"# subplot_titles=['Heatpump output (MW)', 'Steam boiler output (MW)', 'Imbalance price (€/MWh)'],\n",
|
|
"# legend=False,\n",
|
|
"# dimensions=(800, 600),\n",
|
|
"# colors=[recoydarkblue, recoygreen, recoyred],\n",
|
|
"# asFigure=True,\n",
|
|
"# shape=(3,1)\n",
|
|
"# )\n",
|
|
"# fig_optcase"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"# date = '2019-09-04'\n",
|
|
"\n",
|
|
"# fig_optcase2 = s.optcase1.data[['hp_output_MW', 'gb_output_MW', 'NEG']].loc[date, :].iplot(\n",
|
|
"# subplots=True, \n",
|
|
"# title=f'Hybrid case on {date}',\n",
|
|
"# subplot_titles=['Heatpump output (MW)', 'Steam boiler output (MW)', 'Imbalance price (€/MWh)'],\n",
|
|
"# legend=False,\n",
|
|
"# dimensions=(800, 600),\n",
|
|
"# colors=[recoydarkblue, recoygreen, recoyred],\n",
|
|
"# asFigure=True,\n",
|
|
"# shape=(3,1)\n",
|
|
"# )\n",
|
|
"# fig_optcase2"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"report = ComparisonReport(\n",
|
|
" cases=s.optcases, \n",
|
|
" kind='electr_market_results',\n",
|
|
")\n",
|
|
"report.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"casereport = ComparisonReport(cases = s.cases, kind='ebitda_calc', baseline=s.baseline, comparison='relative')\n",
|
|
"casereport.show(presentation_format=True)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"BusinessCaseReport(s.hpcase).show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"#price chart\n",
|
|
"from copy import deepcopy\n",
|
|
"\n",
|
|
"data = deepcopy(s.baseline.data)\n",
|
|
"data = data[data.columns[:2]]\n",
|
|
"data[data.columns[1]] = MWh_gas_to_tonnes_CO2(data[data.columns[1]])\n",
|
|
"data = data.rename(columns={\"CO2 prices (€/ton)\": \"CO2 prices (€/MWh)\"})\n",
|
|
"\n",
|
|
"data.resample('D').mean().iplot(dimensions=(800, 300), title='Gasprices vs. CO2 prices', colors=recoycolors)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"# #price chart\n",
|
|
"# from copy import deepcopy\n",
|
|
"\n",
|
|
"# s.optcase1.data['DAM'].resample('D').mean().iplot(dimensions=(800, 300), title='Electricity Prices', colors=recoycolors)\n",
|
|
"\n",
|
|
"# _source_output = s.optcase1.data[['hp_output_MWh', 'gb_output_MWh']].resample('M').sum()\n",
|
|
"# _total_output = _source_output.sum(axis=1)\n",
|
|
"# _data = _source_output.divide(_total_output, axis=0).rename(\n",
|
|
"# columns={'hp_output_MWh':'Heat pump', 'gb_output_MWh':'Gasboiler'}\n",
|
|
"# ) * 100\n",
|
|
"\n",
|
|
"# production_fig = _data.iplot(\n",
|
|
"# kind='bar',\n",
|
|
"# barmode='stack',\n",
|
|
"# colors=[recoydarkblue, recoygreen],\n",
|
|
"# title='Hybrid case: Heat production per Month by Source in % share',\n",
|
|
"# yTitle='Share of production in %',\n",
|
|
"# dimensions=(600, 400),\n",
|
|
"# asFigure=True\n",
|
|
"# )\n",
|
|
"\n",
|
|
"# production_fig = production_fig.update_layout(legend_traceorder=\"reversed\")\n",
|
|
"# production_fig"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"report = ComparisonReport(s.cases, kind='capex').report\n",
|
|
"report = report[report.index.str.contains('CAPEX')].T\n",
|
|
"capex_fig = report.iplot(\n",
|
|
" kind='bar', \n",
|
|
" barmode='relative',\n",
|
|
" colors=recoycolors,\n",
|
|
" title='CAPEX by Casestudy',\n",
|
|
" yTitle='CAPEX in €',\n",
|
|
" dimensions=(600, 400),\n",
|
|
" asFigure=True,\n",
|
|
")\n",
|
|
"\n",
|
|
"capex_fig = capex_fig.update_layout(legend_traceorder=\"reversed\")\n",
|
|
"capex_fig"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"cashflow_report = ComparisonReport(cases = s.cases, kind='cashflows')\n",
|
|
"\n",
|
|
"fig = cashflow_report.report.T.iplot(\n",
|
|
" kind='bar',\n",
|
|
" barmode='relative',\n",
|
|
" colors=recoycolors,\n",
|
|
" title='OPEX breakdown',\n",
|
|
" asFigure=True,\n",
|
|
" yTitle='€',\n",
|
|
" dimensions=(800, 600)\n",
|
|
")\n",
|
|
"\n",
|
|
"ebitda_report = ComparisonReport(cases=s.cases, kind='ebitda_calc')\n",
|
|
"scat = go.Scatter(\n",
|
|
" mode='markers',\n",
|
|
" y=ebitda_report.report.loc['EBITDA (€)', :].values, \n",
|
|
" x=ebitda_report.report.columns, \n",
|
|
" line=go.scatter.Line(color=recoydarkgrey),\n",
|
|
" marker=dict(\n",
|
|
" color=recoydarkgrey,\n",
|
|
" size=20,\n",
|
|
" line=dict(\n",
|
|
" color=recoydarkgrey,\n",
|
|
" width=3\n",
|
|
" ),\n",
|
|
" symbol='line-ew'\n",
|
|
" ),\n",
|
|
" name='EBITDA (€)'\n",
|
|
")\n",
|
|
"fig.add_trace(scat)\n",
|
|
"fig"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# ebitda_report.show(comparison='relative')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"_series = SingleFigureComparison(s.cases, 'ebitda', label='EBITDA').report\n",
|
|
"ebitda_graph = _series.iplot(\n",
|
|
" kind='bar',\n",
|
|
" title='Yearly EBITDA by Casestudy in €',\n",
|
|
" colors=recoygreen,\n",
|
|
" dimensions=(600, 400), \n",
|
|
" yTitle='EBITDA in €',\n",
|
|
" asFigure=True,\n",
|
|
" yrange=[_series.min() * 1.2, max(_series.max() * 2, 0)]\n",
|
|
")\n",
|
|
"\n",
|
|
"ebitda_graph.update_traces(\n",
|
|
" text=_series.values/1000_000, \n",
|
|
" textposition='outside', \n",
|
|
" texttemplate=\"%{text:.1f}M €\", \n",
|
|
")\n",
|
|
"\n",
|
|
"ebitda_graph"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"_series = SingleFigureComparison(s.optcases, 'npv', label='NPV').report\n",
|
|
"\n",
|
|
"npv_graph = _series.iplot(\n",
|
|
" kind='bar',\n",
|
|
" title='NPV by Casestudy in €',\n",
|
|
" colors=recoygreen,\n",
|
|
" dimensions=(600, 400), \n",
|
|
" yTitle='NPV in €',\n",
|
|
" asFigure=True,\n",
|
|
" yrange=[0, _series.max() * 1.1]\n",
|
|
")\n",
|
|
"\n",
|
|
"npv_graph.update_traces(\n",
|
|
" text=_series.values/1000_000, \n",
|
|
" textposition='outside', \n",
|
|
" texttemplate=\"%{text:.1f}M €\", \n",
|
|
")\n",
|
|
"\n",
|
|
"npv_graph"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"irr_report = (SingleFigureComparison(s.optcases, 'irr', label='IRR').report * 100)\n",
|
|
"irr_fig = irr_report.iplot(\n",
|
|
" kind='bar',\n",
|
|
" title='IRR by Casestudy in %',\n",
|
|
" colors=recoygreen,\n",
|
|
" dimensions=(600, 400),\n",
|
|
" yTitle='IRR in %',\n",
|
|
" asFigure=True,\n",
|
|
" yrange=[0, irr_report.max() * 1.2]\n",
|
|
")\n",
|
|
"\n",
|
|
"irr_fig.update_traces(\n",
|
|
" text=irr_report.values, \n",
|
|
" textposition='outside', \n",
|
|
" texttemplate=\"%{text:.0f} %\", \n",
|
|
")\n",
|
|
"\n",
|
|
"irr_fig"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"_series = (SingleFigureComparison(s.optcases, 'spp', label='Simple Payback Time').report)\n",
|
|
"spt_fig = _series.iplot(\n",
|
|
" kind='bar',\n",
|
|
" title='Simple Payback Time by Casestudy in Years',\n",
|
|
" colors=recoygreen,\n",
|
|
" dimensions=(600, 400),\n",
|
|
" yTitle='Years',\n",
|
|
" asFigure=True,\n",
|
|
" yrange=[0, _series.max() * 1.2]\n",
|
|
")\n",
|
|
"\n",
|
|
"spt_fig.update_traces(\n",
|
|
" text=_series.values, \n",
|
|
" textposition='outside', \n",
|
|
" texttemplate=\"%{text:.1f} years\", \n",
|
|
")\n",
|
|
"\n",
|
|
"spt_fig "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"mean_cops = (SingleFigureComparison(s.optcases, 'mean_cop', label='COP').report)\n",
|
|
"cop_fig = mean_cops.iplot(\n",
|
|
" kind='bar',\n",
|
|
" title='Mean COP by Casestudy',\n",
|
|
" colors=recoygreen,\n",
|
|
" dimensions=(600, 400),\n",
|
|
" yTitle='COP',\n",
|
|
" asFigure=True,\n",
|
|
" yrange=[0, mean_cops.max() * 1.2]\n",
|
|
")\n",
|
|
"\n",
|
|
"cop_fig.update_traces(\n",
|
|
" text=mean_cops.values, \n",
|
|
" textposition='outside', \n",
|
|
" texttemplate=\"%{text:.1f}\", \n",
|
|
")\n",
|
|
"\n",
|
|
"cop_fig "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"source": [
|
|
"## Sensitivity analysis"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"source": [
|
|
"We have agreed that for the sensitivity analysis we will vary the following key assumptions in the flex-model:\n",
|
|
"1. Market prices of gas and electricity. We will use the actual prices for 2019, the actual prices for 2020.\n",
|
|
"2. aFRR prices +/- 30%\n",
|
|
"3. CAPEX\n",
|
|
"4. CO2 price\n",
|
|
"5. Tsource +/- 10 degrees Celsius\n",
|
|
"6. Tsink\n",
|
|
" * Roam off the peak / lower pressure\n",
|
|
" * Stabalize / running average per hour/ 2 hours\n",
|
|
"7. __A scenario with a constraint on grid capacity and a scenario without grid capacity as a constraint__\n",
|
|
"8. Energy Tax and ODE +/- 30%"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"def setup():\n",
|
|
" _c = Config()\n",
|
|
" s = setup_model(c=_c)\n",
|
|
" return s\n",
|
|
"\n",
|
|
"def routine(c, s):\n",
|
|
" s = load_data(c=c, s=s)\n",
|
|
" s = create_and_assign_assets(c=c, s=s)\n",
|
|
" #s = preprocessing(c=c, s=s)\n",
|
|
" s = run_optimisation(c=c, s=s)\n",
|
|
" #s = postprocessing(c=c, s=s)\n",
|
|
" s = collect_cashflows(c=c, s=s)\n",
|
|
" s = calculate_financials(c=c, s=s)\n",
|
|
" return s"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"%time _s = setup()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"%time result = routine(c, _s)\n",
|
|
"npv = result.hpcase.npv\n",
|
|
"npv"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# sensitivity:Storage temperature\n",
|
|
"values = range(80, 120, 10)\n",
|
|
"param = 'storage_temperature'\n",
|
|
"kpis = ['npv','irr','spp', 'mean_cop']\n",
|
|
"\n",
|
|
"sens = SensitivityAnalysis(c, _s, routine, param, values, kpis)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('npv', case_names=[case.name for case in s.cases][1:])\n",
|
|
"output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='volume(m3)',\n",
|
|
" yTitle='NPV in €',\n",
|
|
" yrange=[output.min().min()*1.1, 0],\n",
|
|
" title='Sensitivity: Storage volume',\n",
|
|
" colors=recoycolors,\n",
|
|
" dimensions=(600, 400),\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"### Sensitivity: Water storage volume"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"(_s.demand['MW (VDG)'] + _s.demand['MW (NDG)']).to_list()[:3]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"%time _s = setup()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"values = range(100, 500, 100)\n",
|
|
"param = 'storage_volume'\n",
|
|
"kpis = ['npv','irr','spp']\n",
|
|
"\n",
|
|
"sens = SensitivityAnalysis(c, _s, routine, param, values, kpis)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"[case.name for case in s.cases][1:]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('npv', case_names=[case.name for case in s.cases][1:])\n",
|
|
"output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='volume(m3)',\n",
|
|
" yTitle='NPV in €',\n",
|
|
" yrange=[output.min().min()*1.1, 0],\n",
|
|
" title='Sensitivity: Storage volume',\n",
|
|
" colors=recoycolors,\n",
|
|
" dimensions=(600, 400),\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('irr', case_names=[case.name for case in s.cases][1:])\n",
|
|
"output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='volume(m3)',\n",
|
|
" yTitle='irr in %',\n",
|
|
" yrange=[output.min().min()*1.1, 0],\n",
|
|
" title='Sensitivity: IRR',\n",
|
|
" colors=recoycolors,\n",
|
|
" dimensions=(600, 400),\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('spp', case_names=[case.name for case in s.cases][1:])\n",
|
|
"output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='volume(m3)',\n",
|
|
" yTitle='years',\n",
|
|
" yrange=[output.min().min()*1.2, 0],\n",
|
|
" title='Sensitivity: payback time',\n",
|
|
" colors=recoycolors,\n",
|
|
" dimensions=(600, 400),\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('mean_cop', case_names=[case.name for case in s.cases][1:])\n",
|
|
"output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='volume(m3)',\n",
|
|
" yTitle='COP',\n",
|
|
" yrange=[output.min().min()*1.1, 0],\n",
|
|
" title='Sensitivity: COP',\n",
|
|
" colors=recoycolors,\n",
|
|
" dimensions=(600, 400),\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"### Sensitivity: CAPEX per MW storage"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"values = range(4_000, 10_000, 2_000)\n",
|
|
"param = 'storage_capex_per_MW'\n",
|
|
"kpis = ['npv', 'irr', 'spp', 'mean_cop']\n",
|
|
"\n",
|
|
"sens = SensitivityAnalysis(c, _s, routine, param, values, kpis)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('npv', case_names=[case.name for case in s.cases][1:])\n",
|
|
"output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='CAPEX',\n",
|
|
" yTitle='NPV in Euro',\n",
|
|
" yrange=[output.min().min()*1.1, 0],\n",
|
|
" title='Sensitivity: NPV in euro',\n",
|
|
" colors=recoycolors,\n",
|
|
" dimensions=(600, 400),\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('spp', case_names=[case.name for case in s.cases][1:])\n",
|
|
"output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='CAPEX/MW',\n",
|
|
" yTitle='years',\n",
|
|
" yrange=[output.min().min()*1.2, 0],\n",
|
|
" title='Sensitivity: payback time',\n",
|
|
" colors=recoycolors,\n",
|
|
" dimensions=(600, 400),\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"### Sensitivity: CAPEX per MWh storage"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"values = range(1_000, 5_000, 1000)\n",
|
|
"param = 'storage_capex_per_MWh'\n",
|
|
"kpis = ['npv', 'spp', 'mean_cop']\n",
|
|
"\n",
|
|
"sens = SensitivityAnalysis(c, _s, routine, param, values, kpis)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('npv', case_names=[case.name for case in s.cases][1:])\n",
|
|
"output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='CAPEX/MWh',\n",
|
|
" yTitle='NPV',\n",
|
|
" yrange=[output.min().min()*1.2, 0],\n",
|
|
" title='Sensitivity: NPV in Euro',\n",
|
|
" colors=recoycolors,\n",
|
|
" dimensions=(600, 400),\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('spp', case_names=[case.name for case in s.cases][1:])\n",
|
|
"output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='CAPEX/MWh',\n",
|
|
" yTitle='years',\n",
|
|
" yrange=[output.min().min()*1.2, 0],\n",
|
|
" title='Sensitivity: Payback time',\n",
|
|
" colors=recoycolors,\n",
|
|
" dimensions=(600, 400),\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"### Sensitivity: threshold price"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"values = range(10, 60, 10)\n",
|
|
"param = 'threshold'\n",
|
|
"kpis = ['npv', 'spp', 'mean_cop']\n",
|
|
"\n",
|
|
"sens = SensitivityAnalysis(c, _s, routine, param, values, kpis)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('npv', case_names=[case.name for case in s.cases][1:])\n",
|
|
"output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='threshold',\n",
|
|
" yTitle='NPV',\n",
|
|
" yrange=[output.min().min()*1.2, 0],\n",
|
|
" title='Sensitivity: NPV in Euro',\n",
|
|
" colors=recoycolors,\n",
|
|
" dimensions=(600, 400),\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('spp', case_names=[case.name for case in s.cases][1:])\n",
|
|
"output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='threshold',\n",
|
|
" yTitle='years',\n",
|
|
" yrange=[output.min().min()*1.2, 0],\n",
|
|
" title='Sensitivity: SPP in years',\n",
|
|
" colors=recoycolors,\n",
|
|
" dimensions=(600, 400),\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('mean_cop', case_names=[case.name for case in s.cases][1:])\n",
|
|
"output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='threshold',\n",
|
|
" yTitle='COP',\n",
|
|
" yrange=[output.min().min()*1.2, 0],\n",
|
|
" title='Sensitivity: SOP',\n",
|
|
" colors=recoycolors,\n",
|
|
" dimensions=(600, 400),\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"source": [
|
|
"### Sensitivity: Heat Pump CAPEX"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"_s = setup()\n",
|
|
"configs = {}\n",
|
|
"values = [0.7, 1, 1.3, 2]\n",
|
|
"for value in values:\n",
|
|
" _c = Config()\n",
|
|
" _c.hp_capex *= value\n",
|
|
" configs[value*100] = _c"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"%%time\n",
|
|
"sens = SensitivityAnalysis(_s, routine, configs)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('spp', case_names=['Heatpump only', 'Heatpump + SDE', 'Optimisation', 'Optimisation + aFRR'])\n",
|
|
"\n",
|
|
"sens_capex = output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='CAPEX factor (%)',\n",
|
|
" yTitle='Payback Period in years',\n",
|
|
" yrange=[0, output.max().max()*1.1],\n",
|
|
" title='Sensitivity: Heat Pump CAPEX (€)',\n",
|
|
" colors=[recoygreen, recoyyellow, recoydarkblue, recoyred],\n",
|
|
" dimensions=(600, 400),\n",
|
|
" asFigure=True\n",
|
|
")\n",
|
|
"sens_capex"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"source": [
|
|
"### Sensitivity: CO2 prices"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"_s = setup()\n",
|
|
"configs = {}\n",
|
|
"mean = 24.86\n",
|
|
"co2_prices = [10, 25, 50, 100]\n",
|
|
"\n",
|
|
"for price in co2_prices:\n",
|
|
" _c = Config()\n",
|
|
" multiplier = price / mean\n",
|
|
" _c.co2_price_multiplier = multiplier\n",
|
|
" configs[price] = _c"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"%%time\n",
|
|
"sens = SensitivityAnalysis(_s, routine, configs)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('ebitda', case_names=['Baseline', 'Heatpump + SDE', 'Heatpump only', 'Optimisation', 'Optimisation + aFRR'])\n",
|
|
"output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='Mean CO2 price in €',\n",
|
|
" yTitle='EBITDA in €',\n",
|
|
" yrange=[output.min().min() * 1.1, 0],\n",
|
|
" title='Sensitivity: CO2 prices > EBITDA',\n",
|
|
" colors=[recoypurple, recoygreen, recoyyellow, recoydarkblue, recoyred],\n",
|
|
" dimensions=(600, 400),\n",
|
|
" asFigure=True\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('spp', case_names=['Heatpump only', 'Heatpump + SDE', 'Optimisation', 'Optimisation + aFRR'])\n",
|
|
"sens_co2_spp = output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='Mean CO2 price in €',\n",
|
|
" yTitle='Payback Period in Years',\n",
|
|
" yrange=[0, output.max().max()*1.1],\n",
|
|
" title='Sensitivity: CO2 prices',\n",
|
|
" colors=[recoygreen, recoyyellow, recoydarkblue, recoyred],\n",
|
|
" dimensions=(600, 400),\n",
|
|
" asFigure=True\n",
|
|
")\n",
|
|
"sens_co2_spp"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('npv', case_names=['Heatpump only', 'Heatpump + SDE', 'Optimisation', 'Optimisation + aFRR'])\n",
|
|
"output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='Mean CO2 price in €',\n",
|
|
" yTitle='NPV in €',\n",
|
|
" yrange=[output.min().min() * 10, output.max().max()*1.1],\n",
|
|
" title='Sensitivity: CO2 prices > NPV',\n",
|
|
" colors=[recoygreen, recoyyellow, recoydarkblue, recoyred],\n",
|
|
" dimensions=(600, 400)\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"source": [
|
|
"### Sensitivity: Gas prices"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"_s = setup()\n",
|
|
"configs = {}\n",
|
|
"values = [0.7, 1, 1.3]\n",
|
|
"for value in values:\n",
|
|
" _c = Config()\n",
|
|
" _c.gas_price_multiplier = value\n",
|
|
" configs[value * 100] = _c"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"%%time\n",
|
|
"sens = SensitivityAnalysis(_s, routine, configs)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('npv', case_names=['Heatpump only', 'Heatpump + SDE', 'Optimisation', 'Optimisation + aFRR'])\n",
|
|
"output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='Gas price factor (%)',\n",
|
|
" yTitle='NPV in €',\n",
|
|
" yrange=[output.min().min()*1.5, output.max().max()*1.1],\n",
|
|
" title='Sensitivity: Gas prices',\n",
|
|
" colors=[recoygreen, recoyyellow, recoydarkblue, recoyred],\n",
|
|
" dimensions=(600, 400)\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"source": [
|
|
"### Sensitivity: Day Ahead buying amount"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"_s = setup()\n",
|
|
"configs = {}\n",
|
|
"values = [0, 0.5, 1]\n",
|
|
"for value in values:\n",
|
|
" _c = Config()\n",
|
|
" _c.day_ahead_buying_perc = value\n",
|
|
" configs[value * 100] = _c"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"sens = SensitivityAnalysis(_s, routine, configs)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('npv', case_names=['Heatpump only', 'Heatpump + SDE', 'Optimisation', 'Optimisation + aFRR'])\n",
|
|
"output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='Volume in %',\n",
|
|
" yTitle='NPV in €',\n",
|
|
" yrange=[0, output.max().max()*1.1],\n",
|
|
" title='Sensitivity: Volume bought on Day-Ahead market in %',\n",
|
|
" colors=[recoygreen, recoyyellow, recoydarkblue, recoyred],\n",
|
|
" dimensions=(600, 400)\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"source": [
|
|
"### Sensitivity: Electricity prices"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"_s = setup()\n",
|
|
"configs = {}\n",
|
|
"values = [0.7, 1, 1.3]\n",
|
|
"for value in values:\n",
|
|
" _c = Config()\n",
|
|
" _c.e_price_multiplier = value\n",
|
|
" configs[value * 100] = _c"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"sens = SensitivityAnalysis(_s, routine, configs)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('spp', case_names=['Heatpump only', 'Heatpump + SDE', 'Optimisation', 'Optimisation + aFRR'])\n",
|
|
"sens_eprices = output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='Electricity price factor in %',\n",
|
|
" yTitle='Payback Period in years',\n",
|
|
" yrange=[0, output.max().max()*1.1],\n",
|
|
" title='Sensitivity: Electricity prices',\n",
|
|
" colors=[recoygreen, recoyyellow, recoydarkblue, recoyred],\n",
|
|
" dimensions=(600, 400),\n",
|
|
" asFigure=True\n",
|
|
")\n",
|
|
"sens_eprices"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"source": [
|
|
"### Sensitivity: Electricity price volatility"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"_s = setup()\n",
|
|
"configs = {}\n",
|
|
"values = [0.7, 1, 1.3]\n",
|
|
"for value in values:\n",
|
|
" _c = Config()\n",
|
|
" _c.e_price_volatility_multiplier = value\n",
|
|
" configs[value] = _c"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"sens = SensitivityAnalysis(_s, routine, configs)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('spp', case_names=['Heatpump only', 'Heatpump + SDE', 'Optimisation', 'Optimisation + aFRR'])\n",
|
|
"sens_evol = output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='Volatility factor',\n",
|
|
" yTitle='Payback period in years',\n",
|
|
" yrange=[0, output.max().max()*1.1],\n",
|
|
" title='Sensitivity: E-price volatility',\n",
|
|
" colors=[recoygreen, recoyyellow, recoydarkblue, recoyred],\n",
|
|
" dimensions=(600, 400),\n",
|
|
" asFigure=True\n",
|
|
")\n",
|
|
"sens_evol"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"source": [
|
|
"### Sensitivity: aFRR capacity fee"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"_s = setup()\n",
|
|
"configs = {}\n",
|
|
"values = [10_000, 25_000, 50_000]\n",
|
|
"for value in values:\n",
|
|
" _c = Config()\n",
|
|
" _c.afrr_capacity_fee = value\n",
|
|
" configs[value] = _c"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"sens = SensitivityAnalysis(_s, routine, configs)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('spp', case_names=['Heatpump only', 'Heatpump + SDE', 'Optimisation', 'Optimisation + aFRR'])\n",
|
|
"sens_affr_fee = output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='aFRR capacity fee in €/MW',\n",
|
|
" yTitle='Payback Period in years',\n",
|
|
" yrange=[0, output.max().max()*1.1],\n",
|
|
" title='Sensitivity: aFRR capacity fee',\n",
|
|
" colors=[recoygreen, recoyyellow, recoydarkblue, recoyred],\n",
|
|
" dimensions=(600, 400),\n",
|
|
" asFigure=True\n",
|
|
")\n",
|
|
"sens_affr_fee"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"source": [
|
|
"### Sensitivity: Energy tax"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"_s = setup()\n",
|
|
"configs = {}\n",
|
|
"values = [0.7, 1, 1.3]\n",
|
|
"for value in values:\n",
|
|
" _c = Config()\n",
|
|
" _c.energy_tax_multiplier = value\n",
|
|
" configs[value] = _c"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"sens = SensitivityAnalysis(_s, routine, configs)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('npv', case_names=['Heatpump only', 'Heatpump + SDE', 'Optimisation', 'Optimisation + aFRR'])\n",
|
|
"output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='Factor',\n",
|
|
" yTitle='NPV in €',\n",
|
|
" yrange=[0, output.max().max()*1.1],\n",
|
|
" title='Sensitivity: Energy taxes',\n",
|
|
" colors=[recoygreen, recoyyellow, recoydarkblue, recoyred],\n",
|
|
" dimensions=(600, 400)\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"source": [
|
|
"### Sensitivity: Tsource"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"_s = setup()\n",
|
|
"configs = {}\n",
|
|
"values = [-25, -10, 0, 10, 25]\n",
|
|
"for value in values:\n",
|
|
" _c = Config()\n",
|
|
" _c.tsource_delta = value\n",
|
|
" configs[value] = _c"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"sens = SensitivityAnalysis(_s, routine, configs)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('spp', case_names=['Heatpump only', 'Heatpump + SDE', 'Optimisation', 'Optimisation + aFRR'])\n",
|
|
"output.loc[-25, 'Heatpump only'] = np.nan\n",
|
|
"sens_tsource = output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='Tsource delta',\n",
|
|
" yTitle='Payback Period in years',\n",
|
|
" yrange=[0, output.max().max()*1.1],\n",
|
|
" title='Sensitivity: Tsource',\n",
|
|
" colors=[recoygreen, recoyyellow, recoydarkblue, recoyred],\n",
|
|
" dimensions=(600, 400),\n",
|
|
" asFigure=True\n",
|
|
")\n",
|
|
"sens_tsource"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('mean_cop', case_names=['Heatpump only', 'Heatpump + SDE', 'Optimisation', 'Optimisation + aFRR'])\n",
|
|
"output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='Tsource delta',\n",
|
|
" yTitle='COP',\n",
|
|
" yrange=[0, output.max().max()*1.1],\n",
|
|
" title='Sensitivity: Tsource > Mean COP',\n",
|
|
" colors=[recoygreen, recoyyellow, recoydarkblue, recoyred],\n",
|
|
" dimensions=(600, 400)\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"source": [
|
|
"### Sensitivity: Tsink"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"_s = setup()\n",
|
|
"configs = {}\n",
|
|
"values = [-25, -10, 0, 10, 25]\n",
|
|
"for value in values:\n",
|
|
" _c = Config()\n",
|
|
" _c.tsink_delta = value\n",
|
|
" configs[value] = _c"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"sens = SensitivityAnalysis(_s, routine, configs)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('spp', case_names=['Heatpump only', 'Heatpump + SDE', 'Optimisation', 'Optimisation + aFRR'])\n",
|
|
"sens_tsink = output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='Tsink delta',\n",
|
|
" yTitle='Payback Period in Years',\n",
|
|
" yrange=[0, output.max().max()*1.1],\n",
|
|
" title='Sensitivity: Tsink',\n",
|
|
" colors=[recoygreen, recoyyellow, recoydarkblue, recoyred],\n",
|
|
" dimensions=(600, 400),\n",
|
|
" asFigure=True\n",
|
|
")\n",
|
|
"sens_tsink"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"output = sens.single_kpi_overview('mean_cop', case_names=['Heatpump only', 'Heatpump + SDE', 'Optimisation', 'Optimisation + aFRR'])\n",
|
|
"sens_tsink_cop = output.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='Tsink delta',\n",
|
|
" yTitle='COP',\n",
|
|
" yrange=[0, output.max().max()*1.1],\n",
|
|
" title='Sensitivity: Tsink > Mean COP',\n",
|
|
" colors=[recoygreen, recoyyellow, recoydarkblue, recoyred],\n",
|
|
" dimensions=(600, 400),\n",
|
|
" asFigure=True\n",
|
|
")\n",
|
|
"sens_tsink_cop"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"source": [
|
|
"### Sensitivity: Time period"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"def routine2(c, s):\n",
|
|
" s = setup_model(c=c)\n",
|
|
" s = load_data(c=c, s=s)\n",
|
|
" s = create_and_assign_assets(c=c, s=s)\n",
|
|
" s = run_optimisation(c=c, s=s)\n",
|
|
" s = collect_cashflows(c=c, s=s)\n",
|
|
" s = calculate_financials(c=c, s=s)\n",
|
|
" return s"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"configs = {}\n",
|
|
"start_values = ['2018-01-01', '2019-01-01', '2019-11-01']\n",
|
|
"\n",
|
|
"for value in start_values:\n",
|
|
" _c = Config()\n",
|
|
" _c.start = value\n",
|
|
" _c.end = (pd.to_datetime(value) + timedelta(days=364)).strftime('%Y-%m-%d')\n",
|
|
" configs[value] = _c"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"%%time\n",
|
|
"sens = SensitivityAnalysis(_s, routine2, configs)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"result = sens.single_kpi_overview('npv', case_names=['Heatpump only', 'Heatpump + SDE', 'Optimisation', 'Optimisation + aFRR'])\n",
|
|
"result.iplot(\n",
|
|
" mode='lines+markers',\n",
|
|
" symbol='circle-dot',\n",
|
|
" size=10,\n",
|
|
" xTitle='Start date',\n",
|
|
" yTitle='NPV in €',\n",
|
|
" yrange=[0, result.max().max()*1.1],\n",
|
|
" title='Sensitivity: Modelled time period',\n",
|
|
" colors=[recoygreen, recoyyellow, recoydarkblue, recoyred],\n",
|
|
" dimensions=(600, 400)\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"source": [
|
|
"## Report"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"tags": [
|
|
"exclude"
|
|
]
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"renderer = 'svg'"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"# __Presentation Flexible Heatpumps__\n",
|
|
"\n",
|
|
"ENCORE meeting: 17-12-2020\n",
|
|
"Mark Kremer\n",
|
|
"\n",
|
|
" \n",
|
|
" \n",
|
|
" \n",
|
|
"\n",
|
|
"\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"## __Central question:__\n",
|
|
"#### *Can Smurfit Kappi shorten the Payback Period of an investment in a Heatpump by operating it in a flexible manner?*"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"#### __Flexible operations on imbalance market__\n",
|
|
"\n",
|
|
"Benefiting from fluctuations in electricity market prices by ramping the asset up- and down (increasing and decreasing the electricity consumption)."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"fig_example_1 = s.hpcase.data[['DAM']].iloc[:60*24].iplot(\n",
|
|
" title='Day-Ahead prices on arbitrary day in €/MWh',\n",
|
|
" yrange=[-100, 200],\n",
|
|
" colors=recoygreen, \n",
|
|
" yTitle='Price in €/MWh',\n",
|
|
" xTitle='Time of Day',\n",
|
|
" dimensions=(800, 400),\n",
|
|
" asFigure=True\n",
|
|
")\n",
|
|
"\n",
|
|
"fig_example_1.show(renderer=renderer)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"Imbalance prices are very volatile, with prices below -100 and above 200 €/MWh on a daily basis."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"fig_example_2 = s.hpcase.data[['DAM', 'POS']].rename(columns={'POS':'IMB'}).iloc[:60*24].iplot(\n",
|
|
" title='Imbalance Prices on arbitrary day in €/MWh',\n",
|
|
" colors=[recoygreen, recoydarkblue], \n",
|
|
" yTitle='Price in €/MWh',\n",
|
|
" xTitle='Time of Day',\n",
|
|
" dimensions=(800, 400),\n",
|
|
" asFigure=True\n",
|
|
")\n",
|
|
"\n",
|
|
"fig_example_2.show(renderer=renderer)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"It is possible to benefit from these fluctiations, if you have __flexibility__\n",
|
|
"* Storage options\n",
|
|
"* Hybrid installations (e.g. with gas-powered assets)\n",
|
|
"\n",
|
|
"In this case we are looking at a __hybrid set-up of a Steamboiler and a Heatpump__"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"#### __Simulations & mathematical modelling__"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"* To answer the central question, we have build a simulation model\n",
|
|
"* The model simulates the operations of a hybrid set-up of a Heatpump and a Steamboiler over the timespan of 1 years (on a 1 minute basis)\n",
|
|
"* The goal of the model is to minimize the operating costs, in order to reach the shortest Payback Period\n",
|
|
"* We are taking into account all major investment and operating costs, including:\n",
|
|
" * Asset CAPEX\n",
|
|
" * Commodity costs for gas and electricity\n",
|
|
" * Energy taxes\n",
|
|
" * Grid transport costs\n",
|
|
" * SDE++ subsidies\n",
|
|
" * Maintenance costs\n",
|
|
" * CO2 allowances\n",
|
|
"* The output of the model is a Payback Period for an investment in an heatpump, in different scenario's"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"#### __Casestudies__\n",
|
|
"5 main scenario's"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"\n",
|
|
"1. Steamboiler only (baseline, baseload)\n",
|
|
"2. Heatpump only (stand-alone, baseload, without SDE++)\n",
|
|
"3. Heatpump + SDE\n",
|
|
"4. Heatpump + SDE + Steam boiler (hybrid set-up) on Imbalance market\n",
|
|
"5. Heatpump + SDE + Steam boiler (hybrid set-up) on aFRR (secondary reserve market)\n",
|
|
"\n",
|
|
"Besides that, we modelled 11 sensitivities:\n",
|
|
"* Heatpump CAPEX\n",
|
|
"* Gas & CO2 prices\n",
|
|
"* Electricity prices & volatility\n",
|
|
"* Energy taxes\n",
|
|
"* Bidding strategies\n",
|
|
"* Source temperatures (affecting COP)\n",
|
|
"* Sink temperatures (affecting COP)\n",
|
|
"* Time period (2018, 2019, 2020)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"#### __Smurfit Kappa case__"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"The model is based on the context of Smurfit Kappa (paper factory)\n",
|
|
"* Currently a Steamboiler is providing the 20-30 MW of average heat demand for drying processes\n",
|
|
"* We add a 31 MW heatpump (to make sure it can cover entire demand)\n",
|
|
"* The steam demand must be fulfilled at all times, by either the heatpump or the gasboiler\n",
|
|
"* The heatpump and steam boiler can both respond very quickly (within minutes) within a flexible range (30%-100% for heatpump)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"fig_demands_over_time.show(renderer=renderer)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"* Source temperatures of around 65 degrees C\n",
|
|
"* Sink temperatures of 125-170 degrees C \n",
|
|
"* Average Temperature lift of about 85 degrees C"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"demands_fig.show(renderer=renderer)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"#### __Heat pump__"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"COP roughly between 4 and 1.5, depending on load, Tsource and Tsink"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"def cop_curve(Tsink, Tsource):\n",
|
|
" Tsink += 273\n",
|
|
" Tsource += 273\n",
|
|
"\n",
|
|
" c1 = 0.267 * Tsink / (Tsink - Tsource)\n",
|
|
" c2 = 0.333 * Tsink / (Tsink - Tsource)\n",
|
|
" \n",
|
|
" return Polynomial([c2, c1])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sourceT = 63\n",
|
|
"sinkT = 140\n",
|
|
"cop_curve(sourceT, sinkT)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"fig_cop_curve.show(renderer=renderer)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"#### __Optimisation__"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"* At each moment in time, we calculate the cheapest option to produce the required heat. \n",
|
|
"* Taking into account the COP fluctuations, due to changing Tsource and Tsink\n",
|
|
"* Taking into account fluctuating market prices (electricity, gas, CO2)\n",
|
|
"* We are predicting real-time electricity prices using our forecasting models"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"__Some example days:__"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"Steamboiler only is following demand pattern"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"fig_steamboiler.show(renderer=renderer)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"Similar pattern for heatpump only case"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"fig_heatpump.show(renderer=renderer)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"Hybrid set-up is responding to price fluctuactions, steam boiler taking over at high prices"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"fig_optcase.show(renderer=renderer)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"fig_optcase2.show(renderer=renderer)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"#### __Business case__"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"CAPEX of around 6 M€ (200.000 €/MW), which need to be earned back by savings in operating costs"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"capex_fig.show(renderer=renderer)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"* Savings in EBITDA compared to the baseline are about 1.5 mln € without subsidy, and up to 4.5 mln € including subsidy\n",
|
|
"* The optimisation on aFRR allows for a 30-40% improvement in EBITDA"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"ebitda_graph.show(renderer=renderer)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"Resulting in a Payback Period of 5.4 years without subsidy, and 1.8 years with subsidy"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"spt_fig.show(renderer=renderer)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"The added value of the optimisation is limited (in absolute terms), which is explained by the high COP of the heatpump"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"production_fig.show(renderer=renderer)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"* The heatpump is filling in 95-98 % of the demand. \n",
|
|
"* Because of its high COP, it is almost always cheaper to run than the steam boiler\n",
|
|
"* Switch price is on average around 90€/MWh (excluding subsidies)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"#### __Sensitivities__"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"If CAPEX is 200%, subsidy is needed to keep a good Payback Time"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sens_capex.show(renderer=renderer)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"Subsidies are protecting the business case againsts low CO2 prices"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sens_co2_spp.show(renderer=renderer)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"* The businesscase is quite sensitive to Tsource and Tsink differences, because they directly impact the COP\n",
|
|
"* The Smurtfit Kappa case, with a temperature lifte of about 85 degrees C on average, looks favorable. \n",
|
|
"* When the temperature lift is higher, the COP will decrease and the business case will degrade"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sens_tsource.show(renderer=renderer)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sens_tsink.show(renderer=renderer)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sens_tsink_cop.show(renderer=renderer)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"sens_eprices.show(renderer=renderer)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"#### __Conclusions__"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"* The business case for a Heat Pump seems favourable\n",
|
|
"* Flexible operation, using aFRR, can improve the operational results by 30-40%\n",
|
|
"* However, this only results in a marginal improvement of the business case\n",
|
|
"* SDE++ has a very favourable effect on the business case, but is not critical\n",
|
|
"* The business case is notably sensitive to the temperature lift required, and is therefore strongly dependent on the specific use case."
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"interpreter": {
|
|
"hash": "fea6e7ab4c0ed1d184e153838ac4b2d24a0985a5f17e99f4f437a114b66796b8"
|
|
},
|
|
"kernelspec": {
|
|
"display_name": "Python 3 (ipykernel)",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.10.9"
|
|
},
|
|
"toc-autonumbering": false,
|
|
"toc-showmarkdowntxt": false,
|
|
"widgets": {
|
|
"application/vnd.jupyter.widget-state+json": {
|
|
"state": {},
|
|
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|
|
"version_minor": 0
|
|
}
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 4
|
|
}
|