{
"cells": [
{
"cell_type": "markdown",
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"source": [
"#### Imports"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"tags": [
"exclude"
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},
"outputs": [
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"data": {
"text/html": [
" \n",
" "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from datetime import timedelta\n",
"import json\n",
"import pprint\n",
"from copy import deepcopy\n",
"\n",
"import cufflinks\n",
"cufflinks.go_offline()\n",
"import numpy as np\n",
"from numpy.polynomial import Polynomial\n",
"import pandas as pd\n",
"from tqdm.notebook import tqdm\n",
"\n",
"from pyrecoy.assets import Heatpump, Eboiler, GasBoiler, HotWaterStorage\n",
"from pyrecoy.colors import *\n",
"from pyrecoy.converters import *\n",
"from pyrecoy.financial import calculate_eb_ode, get_tax_tables, get_tax_rate, get_grid_tariffs_electricity\n",
"from pyrecoy.framework import TimeFramework\n",
"from pyrecoy.casestudy import CaseStudy\n",
"from pyrecoy.plotting import ebitda_bar_chart, npv_bar_chart\n",
"from pyrecoy.reports import CaseReport, ComparisonReport, BusinessCaseReport, SingleFigureComparison\n",
"from pyrecoy.sensitivity import SensitivityAnalysis\n",
"from pyrecoy.prices import get_tennet_data, get_afrr_capacity_fees_nl\n",
"from pyrecoy.forecasts import Mipf\n",
"\n",
"%load_ext autoreload\n",
"%autoreload 2"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": [
"exclude"
]
},
"source": [
"#### Development backlog"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": [
"exclude"
]
},
"source": [
"* aFRR (can improve the optimisation case)\n",
"* Report\n",
"\n",
"--\n",
"* Create strategy on imbalance POS (buy 100% day-ahead, and respond to high prices)\n",
"* Graphs\n",
" * EBITDA vs. baseline (earnings vs baseline)\n",
"* Show COP curves in different cases, just for illustration\n",
"* Energy report --> Check + add gas\n",
"* Fix comparison reports\n",
"* Model verification"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": [
"exclude"
]
},
"source": [
"#### Meeting Notes"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": [
"exclude"
]
},
"source": [
"##### Meeting 25-11-2020"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": [
"exclude"
]
},
"source": [
"* aFRR can help optimisation case\n",
"* SDE++ should be included\n",
"* Tsource sensitivity really gives interesting insights\n",
"* Sensitivities should be verified (especially CO2, Tsink, Tsource, time period)\n",
"* AP TNO: Update/verify COP curve\n",
"* AP TNO: Update CAPEX\n",
"* AP Mark: \n",
" * Create graphs on COP curve with different Tsource, Tsink\n",
" * Generate table and output in .csv (send it to Andrew)\n",
"* Investigate opportunity to lower the COP and negative electricity prices\n",
" * Technically feasible, but not really needed/possible to do it in this project\n",
"* Could be interesting to run this model on a usecase with higher delta T\n",
"* Conclusion: Finalize this model, but not add too much extra complexity, next steps is to go towards industrial partners with the results"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": [
"exclude"
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},
"source": [
"# ENCORE : Heatpump Optimisation Framework\n",
"\n",
"***\n",
"© Mark Kremer \n",
"July 2020\n",
"##### Cases\n",
"In this model, 3 cases are compared:\n",
"* **Baseline** : All heat is supplied by steam turbine\n",
"* **Heatpump case** : All heat is supplied by heatpump\n",
"* **Hybrid case** : Steam turbine and heatpump run in hybrid mode, and are optimised on costs in real-time"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": [
"exclude"
]
},
"source": [
"#### Loading config"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"tags": [
"exclude"
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},
"outputs": [],
"source": [
"class Config():\n",
" start = '2019-01-01'\n",
" end = '2019-12-31'\n",
" \n",
" hp_vdg_e_power = 23.3 # MW\n",
" hp_ndg_e_power = 7.7 # MW\n",
" hp_min_load = 0\n",
" hp_lifetime = 25\n",
" hp_capex = 200_000 # EUR/MWth\n",
" hp_opex = 0.01 # in % of CAPEX\n",
" hp_devex = 0.005 # in % of CAPEX\n",
" \n",
" gb_power = 35 # MW\n",
" gb_efficiency = 0.9\n",
" \n",
" storage_power = 25\n",
" storage_volume = 1000\n",
" storage_cap_per_volume = 50 * 1e-3\n",
" storage_lifetime = 25\n",
" storage_temperature = 95\n",
" storage_min_level = storage_volume * storage_cap_per_volume * 0.05\n",
" storage_capex_per_MW = 7_000\n",
" storage_capex_per_MWh = 5_000\n",
" storage_opex_perc_of_capex = 0.02\n",
" # storage_initial_level = 5\n",
" threshold = 20\n",
" \n",
" tax_bracket_g = 4 \n",
" tax_bracket_e = 4\n",
" \n",
" include_transport_costs = False\n",
" grid_operator = 'Liander'\n",
" connection_type = 'TS/MS'\n",
" \n",
" discount_rate = 0.1\n",
" project_duration = 12\n",
"\n",
" forecast = 'ForeNeg'\n",
" gas_price_multiplier = 1\n",
" e_price_multiplier = 1\n",
" e_price_volatility_multiplier = 1\n",
" co2_price_multiplier = 1\n",
" tsource_delta = 0\n",
" tsink_delta = 0\n",
" energy_tax_multiplier = 1\n",
" \n",
" # Review the SDE implementation\n",
" sde_base_amount = 81\n",
" longterm_gas_price = 24.00\n",
" longterm_co2_price = 37.90\n",
" sde_switch_price_correction = 40\n",
" \n",
" day_ahead_buying_perc = 0.3\n",
" \n",
" afrr_capacity_fee = 25_000\n",
"\n",
"c = Config()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"tags": [
"exclude"
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},
"outputs": [],
"source": [
"class Store():\n",
" pass"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": [
"exclude"
]
},
"source": [
"## Model set-up"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"tags": [
"exclude"
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},
"outputs": [],
"source": [
"def load_demand_data(c, s):\n",
" demand = pd.read_csv('data/smurfit_demand_preprocessed.csv', delimiter=';', decimal=',')\n",
" dt_index = pd.date_range(\n",
" start=s.time_fw.start,\n",
" end=s.time_fw.start + timedelta(days=365), freq='1T',\n",
" closed='left',\n",
" tz='Europe/Amsterdam')\n",
" demand.index = dt_index\n",
" demand['Total demand'] = demand['MW (VDG)'] + demand['MW (NDG)']\n",
" demand = demand[c.start:c.end]\n",
" return demand"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"s = Store()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"tags": [
"exclude"
]
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"c:\\users\\shahla huseynova\\recoy\\recoy - documents\\03 - libraries\\29 - pyrecoy modelling framework\\v1.2\\pyrecoy\\pyrecoy\\framework.py:40: UserWarning:\n",
"\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",
"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Warning: Entries missing from dataset 'imbalanceRT_nl.csv'.\n",
"Issue solved: Dataset was reindexed automatically.\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\SHAHLA~1\\AppData\\Local\\Temp/ipykernel_4300/332434720.py:3: FutureWarning:\n",
"\n",
"Argument `closed` is deprecated in favor of `inclusive`.\n",
"\n"
]
}
],
"source": [
"def setup_model(c):\n",
" s = Store()\n",
" \n",
" s.time_fw = TimeFramework(start=c.start, end=c.end)\n",
" s.mipf = Mipf(start=s.time_fw.start, end=s.time_fw.end, tidy=True, include_nextQ=True,\n",
" folder_path = r\"C:\\Users\\Shahla Huseynova\\Recoy\\Recoy - Documents\\03 - Libraries\\12 - Data Management\\Forecast Data\"\n",
" ).data\n",
" \n",
" s.demand = load_demand_data(c, s)\n",
" return s\n",
"\n",
"s = setup_model(c)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"linkText": "Export to plot.ly",
"plotlyServerURL": "https://plot.ly",
"showLink": true
},
"data": [
{
"line": {
"color": "rgba(255, 153, 51, 1.0)",
"dash": "solid",
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"s.demand.resample('15T').mean()[['Tsource (VDG)', 'Tsink (VDG)']].iplot()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"# s.demand.iplot()"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" Tsource (VDG) | \n",
" Tsink (VDG) | \n",
" MW (VDG) | \n",
" Tsource (NDG) | \n",
" Tsink (NDG) | \n",
" MW (NDG) | \n",
" Total demand | \n",
"
\n",
" \n",
" \n",
" \n",
" | count | \n",
" 525600.000000 | \n",
" 525600.000000 | \n",
" 525600.000000 | \n",
" 525600.000000 | \n",
" 525600.000000 | \n",
" 525600.000000 | \n",
" 525600.000000 | \n",
"
\n",
" \n",
" | mean | \n",
" 63.658798 | \n",
" 138.637674 | \n",
" 17.636712 | \n",
" 62.176305 | \n",
" 145.351645 | \n",
" 5.823824 | \n",
" 23.460537 | \n",
"
\n",
" \n",
" | std | \n",
" 6.422773 | \n",
" 14.328580 | \n",
" 5.123252 | \n",
" 10.252555 | \n",
" 14.896056 | \n",
" 1.691697 | \n",
" 6.814125 | \n",
"
\n",
" \n",
" | min | \n",
" 25.310000 | \n",
" 82.480000 | \n",
" 0.000000 | \n",
" 13.540000 | \n",
" 106.330000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
"
\n",
" \n",
" | 25% | \n",
" 64.892000 | \n",
" 126.074000 | \n",
" 17.014000 | \n",
" 63.516000 | \n",
" 131.551500 | \n",
" 5.612000 | \n",
" 22.676000 | \n",
"
\n",
" \n",
" | 50% | \n",
" 64.991000 | \n",
" 142.450000 | \n",
" 19.892000 | \n",
" 64.313000 | \n",
" 148.490000 | \n",
" 6.540000 | \n",
" 26.441000 | \n",
"
\n",
" \n",
" | 75% | \n",
" 65.076000 | \n",
" 151.730000 | \n",
" 20.819000 | \n",
" 65.546000 | \n",
" 158.100000 | \n",
" 6.880000 | \n",
" 27.690000 | \n",
"
\n",
" \n",
" | max | \n",
" 70.070000 | \n",
" 166.020000 | \n",
" 23.250000 | \n",
" 73.470000 | \n",
" 172.050000 | \n",
" 7.650000 | \n",
" 30.900000 | \n",
"
\n",
" \n",
"
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" DAM | \n",
" POS | \n",
" NEG | \n",
" RS | \n",
" ForePos | \n",
" ForeNeg | \n",
" ForePos_nextQ | \n",
" ForeNeg_nextQ | \n",
" Gas prices (€/MWh) | \n",
" CO2 prices (€/ton) | \n",
" CO2 prices (€/MWh) | \n",
" Tsource (VDG) | \n",
" Tsink (VDG) | \n",
" MW (VDG) | \n",
" Tsource (NDG) | \n",
" Tsink (NDG) | \n",
" MW (NDG) | \n",
" Total demand | \n",
"
\n",
" \n",
" \n",
" \n",
" | 2019-01-01 00:00:00+01:00 | \n",
" 68.92 | \n",
" 34.85 | \n",
" 58.01 | \n",
" 2.0 | \n",
" 46.83 | \n",
" 52.70 | \n",
" NaN | \n",
" NaN | \n",
" 22.38 | \n",
" 24.98 | \n",
" 4.82 | \n",
" 64.990 | \n",
" 143.360 | \n",
" 0.0 | \n",
" 20.510 | \n",
" 147.620 | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-01-01 00:01:00+01:00 | \n",
" 68.92 | \n",
" 34.85 | \n",
" 58.01 | \n",
" 2.0 | \n",
" 32.12 | \n",
" 54.45 | \n",
" NaN | \n",
" NaN | \n",
" 22.38 | \n",
" 24.98 | \n",
" 4.82 | \n",
" 64.985 | \n",
" 143.089 | \n",
" 0.0 | \n",
" 20.387 | \n",
" 147.642 | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-01-01 00:02:00+01:00 | \n",
" 68.92 | \n",
" 34.85 | \n",
" 58.01 | \n",
" 2.0 | \n",
" 30.97 | \n",
" 48.64 | \n",
" NaN | \n",
" NaN | \n",
" 22.38 | \n",
" 24.98 | \n",
" 4.82 | \n",
" 64.980 | \n",
" 142.818 | \n",
" 0.0 | \n",
" 20.264 | \n",
" 147.664 | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-01-01 00:03:00+01:00 | \n",
" 68.92 | \n",
" 34.85 | \n",
" 58.01 | \n",
" 2.0 | \n",
" 51.13 | \n",
" 48.35 | \n",
" 57.71 | \n",
" 73.05 | \n",
" 22.38 | \n",
" 24.98 | \n",
" 4.82 | \n",
" 64.975 | \n",
" 142.547 | \n",
" 0.0 | \n",
" 20.141 | \n",
" 147.686 | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-01-01 00:04:00+01:00 | \n",
" 68.92 | \n",
" 34.85 | \n",
" 58.01 | \n",
" 2.0 | \n",
" 48.04 | \n",
" 52.01 | \n",
" 63.60 | \n",
" 79.07 | \n",
" 22.38 | \n",
" 24.98 | \n",
" 4.82 | \n",
" 64.970 | \n",
" 142.276 | \n",
" 0.0 | \n",
" 20.018 | \n",
" 147.708 | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
"
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" DAM | \n",
" POS | \n",
" NEG | \n",
" RS | \n",
" ForePos | \n",
" ForeNeg | \n",
" ForePos_nextQ | \n",
" ForeNeg_nextQ | \n",
" Gas prices (€/MWh) | \n",
" CO2 prices (€/ton) | \n",
" ... | \n",
" from_storage_MW | \n",
" storage_level_MWh | \n",
" hp_output_MWh | \n",
" hp_input_MWh | \n",
" to_storage_ndg_MWh | \n",
" from_storage_ndg_MWh | \n",
" to_storage_vdg_MWh | \n",
" from_storage_vdg_MWh | \n",
" to_storage_MWh | \n",
" from_storage_MWh | \n",
"
\n",
" \n",
" \n",
" \n",
" | 2019-12-15 12:55:00+01:00 | \n",
" 35.45 | \n",
" 50.52 | \n",
" 50.52 | \n",
" 1.0 | \n",
" 56.50 | \n",
" 57.06 | \n",
" 50.76 | \n",
" 68.91 | \n",
" 12.85 | \n",
" 24.02 | \n",
" ... | \n",
" 0.0 | \n",
" 2.5 | \n",
" 0.348 | \n",
" -0.059 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-03-10 08:18:00+01:00 | \n",
" 41.80 | \n",
" 45.74 | \n",
" 45.74 | \n",
" 1.0 | \n",
" 51.21 | \n",
" 44.16 | \n",
" 46.65 | \n",
" 41.56 | \n",
" 16.88 | \n",
" 22.91 | \n",
" ... | \n",
" 0.0 | \n",
" 2.5 | \n",
" 0.457 | \n",
" -0.087 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
"
\n",
"
2 rows × 38 columns
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" DAM | \n",
" POS | \n",
" NEG | \n",
" hp_output_MW | \n",
" to_storage_MW | \n",
" Total demand | \n",
"
\n",
" \n",
" \n",
" \n",
" | count | \n",
" 525600.000000 | \n",
" 525600.000000 | \n",
" 525600.000000 | \n",
" 525600.000000 | \n",
" 525600.000000 | \n",
" 525600.000000 | \n",
"
\n",
" \n",
" | mean | \n",
" 41.195801 | \n",
" 40.391060 | \n",
" 42.554082 | \n",
" 24.354581 | \n",
" 0.894045 | \n",
" 23.460537 | \n",
"
\n",
" \n",
" | std | \n",
" 11.278173 | \n",
" 51.226931 | \n",
" 52.003252 | \n",
" 7.151966 | \n",
" 2.633376 | \n",
" 6.814125 | \n",
"
\n",
" \n",
" | min | \n",
" -9.020000 | \n",
" -487.650000 | \n",
" -487.650000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
"
\n",
" \n",
" | 25% | \n",
" 34.100000 | \n",
" 24.470000 | \n",
" 25.530000 | \n",
" 22.760000 | \n",
" 0.000000 | \n",
" 22.676000 | \n",
"
\n",
" \n",
" | 50% | \n",
" 39.700000 | \n",
" 31.110000 | \n",
" 32.160000 | \n",
" 26.980000 | \n",
" 0.000000 | \n",
" 26.441000 | \n",
"
\n",
" \n",
" | 75% | \n",
" 47.392500 | \n",
" 40.900000 | \n",
" 42.540000 | \n",
" 28.010000 | \n",
" 0.000000 | \n",
" 27.690000 | \n",
"
\n",
" \n",
" | max | \n",
" 121.460000 | \n",
" 936.120000 | \n",
" 936.120000 | \n",
" 31.000000 | \n",
" 25.000000 | \n",
" 30.900000 | \n",
"
\n",
" \n",
"
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" DAM | \n",
" POS | \n",
" NEG | \n",
" hp_output_MW | \n",
" to_storage_MW | \n",
" from_storage_MW | \n",
" Total demand | \n",
"
\n",
" \n",
" \n",
" \n",
" | 2019-01-01 00:00:00+01:00 | \n",
" 68.92 | \n",
" 34.85 | \n",
" 58.01 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-01-01 00:01:00+01:00 | \n",
" 68.92 | \n",
" 34.85 | \n",
" 58.01 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-01-01 00:02:00+01:00 | \n",
" 68.92 | \n",
" 34.85 | \n",
" 58.01 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-01-01 00:03:00+01:00 | \n",
" 68.92 | \n",
" 34.85 | \n",
" 58.01 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-01-01 00:04:00+01:00 | \n",
" 68.92 | \n",
" 34.85 | \n",
" 58.01 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
"
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" DAM | \n",
" POS | \n",
" NEG | \n",
" Total demand | \n",
" hp_input_MW | \n",
" hp_output_MW | \n",
" cop | \n",
" to_storage_MW | \n",
" from_storage_MW | \n",
"
\n",
" \n",
" \n",
" \n",
" | 2019-06-08 20:25:00+02:00 | \n",
" 34.90 | \n",
" 25.85 | \n",
" 25.85 | \n",
" 27.550 | \n",
" -5.211 | \n",
" 27.550 | \n",
" 5.287 | \n",
" 0.000 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-03-17 10:45:00+01:00 | \n",
" 37.80 | \n",
" -66.52 | \n",
" -66.52 | \n",
" 27.700 | \n",
" -5.423 | \n",
" 31.000 | \n",
" 5.717 | \n",
" 3.300 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-05-19 05:00:00+02:00 | \n",
" 33.91 | \n",
" 45.42 | \n",
" 45.42 | \n",
" 20.770 | \n",
" -3.558 | \n",
" 20.770 | \n",
" 5.837 | \n",
" 0.000 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-11-27 08:27:00+01:00 | \n",
" 50.54 | \n",
" -83.03 | \n",
" -83.03 | \n",
" 27.581 | \n",
" -5.538 | \n",
" 31.000 | \n",
" 5.598 | \n",
" 3.419 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-11-30 03:43:00+01:00 | \n",
" 35.39 | \n",
" 44.78 | \n",
" 44.78 | \n",
" 22.868 | \n",
" -4.164 | \n",
" 22.868 | \n",
" 5.492 | \n",
" 0.000 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-08-26 15:27:00+02:00 | \n",
" 38.39 | \n",
" 73.12 | \n",
" 73.12 | \n",
" 29.626 | \n",
" -5.397 | \n",
" 29.626 | \n",
" 5.489 | \n",
" 0.000 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-07-17 18:07:00+02:00 | \n",
" 52.00 | \n",
" 35.23 | \n",
" 35.23 | \n",
" 20.807 | \n",
" -3.612 | \n",
" 20.807 | \n",
" 5.760 | \n",
" 0.000 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-09-27 08:05:00+02:00 | \n",
" 50.31 | \n",
" 27.02 | \n",
" 27.02 | \n",
" 27.850 | \n",
" -5.378 | \n",
" 31.000 | \n",
" 5.765 | \n",
" 3.150 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-07-28 01:03:00+02:00 | \n",
" 30.02 | \n",
" 189.12 | \n",
" 189.12 | \n",
" 0.000 | \n",
" 0.000 | \n",
" 0.000 | \n",
" NaN | \n",
" 0.000 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-11-07 10:52:00+01:00 | \n",
" 47.54 | \n",
" 29.74 | \n",
" 29.74 | \n",
" 22.934 | \n",
" -4.018 | \n",
" 22.934 | \n",
" 5.708 | \n",
" 0.000 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-05-29 01:54:00+02:00 | \n",
" 33.07 | \n",
" 28.72 | \n",
" 28.72 | \n",
" 29.432 | \n",
" -5.351 | \n",
" 29.432 | \n",
" 5.500 | \n",
" 0.000 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-06-12 16:22:00+02:00 | \n",
" 34.90 | \n",
" 27.79 | \n",
" 27.79 | \n",
" 20.102 | \n",
" -3.764 | \n",
" 20.102 | \n",
" 5.340 | \n",
" 0.000 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-10-11 14:02:00+02:00 | \n",
" 31.55 | \n",
" 21.06 | \n",
" 26.98 | \n",
" 28.280 | \n",
" -5.198 | \n",
" 28.280 | \n",
" 5.441 | \n",
" 0.000 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-11-25 02:05:00+01:00 | \n",
" 36.02 | \n",
" 54.21 | \n",
" 54.21 | \n",
" 0.000 | \n",
" -0.000 | \n",
" 0.000 | \n",
" NaN | \n",
" 0.000 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-12-12 01:10:00+01:00 | \n",
" 35.83 | \n",
" 27.37 | \n",
" 32.72 | \n",
" 0.000 | \n",
" -0.000 | \n",
" 0.000 | \n",
" NaN | \n",
" 0.000 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-08-02 18:06:00+02:00 | \n",
" 45.95 | \n",
" 29.53 | \n",
" 29.53 | \n",
" 20.678 | \n",
" -3.653 | \n",
" 20.678 | \n",
" 5.661 | \n",
" 0.000 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-06-08 17:51:00+02:00 | \n",
" 26.30 | \n",
" 26.85 | \n",
" 26.85 | \n",
" 27.539 | \n",
" -5.239 | \n",
" 27.539 | \n",
" 5.257 | \n",
" 0.000 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-07-14 15:09:00+02:00 | \n",
" 32.04 | \n",
" 33.48 | \n",
" 33.48 | \n",
" 27.945 | \n",
" -5.054 | \n",
" 27.945 | \n",
" 5.529 | \n",
" 0.000 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-01-10 02:55:00+01:00 | \n",
" 48.63 | \n",
" 45.72 | \n",
" 45.72 | \n",
" 26.850 | \n",
" -4.905 | \n",
" 26.850 | \n",
" 5.474 | \n",
" 0.000 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-06-13 20:12:00+02:00 | \n",
" 72.87 | \n",
" 24.18 | \n",
" 24.18 | \n",
" 28.364 | \n",
" -5.452 | \n",
" 31.000 | \n",
" 5.686 | \n",
" 2.636 | \n",
" 0.0 | \n",
"
\n",
" \n",
"
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" DAM | \n",
" POS | \n",
" NEG | \n",
" RS | \n",
" ForePos | \n",
" ForeNeg | \n",
" ForePos_nextQ | \n",
" ForeNeg_nextQ | \n",
" Gas prices (€/MWh) | \n",
" CO2 prices (€/ton) | \n",
" ... | \n",
" MW (VDG) | \n",
" Tsource (NDG) | \n",
" Tsink (NDG) | \n",
" MW (NDG) | \n",
" Total demand | \n",
" hp_output_MW | \n",
" hp_input_MW | \n",
" cop | \n",
" hp_output_MWh | \n",
" hp_input_MWh | \n",
"
\n",
" \n",
" \n",
" \n",
" | 2019-01-01 00:00:00+01:00 | \n",
" 68.92 | \n",
" 34.85 | \n",
" 58.01 | \n",
" 2.0 | \n",
" 46.83 | \n",
" 52.70 | \n",
" NaN | \n",
" NaN | \n",
" 22.38 | \n",
" 24.98 | \n",
" ... | \n",
" 0.0 | \n",
" 20.510 | \n",
" 147.620 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" NaN | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-01-01 00:01:00+01:00 | \n",
" 68.92 | \n",
" 34.85 | \n",
" 58.01 | \n",
" 2.0 | \n",
" 32.12 | \n",
" 54.45 | \n",
" NaN | \n",
" NaN | \n",
" 22.38 | \n",
" 24.98 | \n",
" ... | \n",
" 0.0 | \n",
" 20.387 | \n",
" 147.642 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" NaN | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-01-01 00:02:00+01:00 | \n",
" 68.92 | \n",
" 34.85 | \n",
" 58.01 | \n",
" 2.0 | \n",
" 30.97 | \n",
" 48.64 | \n",
" NaN | \n",
" NaN | \n",
" 22.38 | \n",
" 24.98 | \n",
" ... | \n",
" 0.0 | \n",
" 20.264 | \n",
" 147.664 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" NaN | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-01-01 00:03:00+01:00 | \n",
" 68.92 | \n",
" 34.85 | \n",
" 58.01 | \n",
" 2.0 | \n",
" 51.13 | \n",
" 48.35 | \n",
" 57.71 | \n",
" 73.05 | \n",
" 22.38 | \n",
" 24.98 | \n",
" ... | \n",
" 0.0 | \n",
" 20.141 | \n",
" 147.686 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" NaN | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-01-01 00:04:00+01:00 | \n",
" 68.92 | \n",
" 34.85 | \n",
" 58.01 | \n",
" 2.0 | \n",
" 48.04 | \n",
" 52.01 | \n",
" 63.60 | \n",
" 79.07 | \n",
" 22.38 | \n",
" 24.98 | \n",
" ... | \n",
" 0.0 | \n",
" 20.018 | \n",
" 147.708 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" NaN | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
"
\n",
"
5 rows × 23 columns
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" Heatpump only | \n",
" Heatpump + Storage | \n",
"
\n",
" \n",
" \n",
" \n",
" | Total net volume (MWh) | \n",
" -37,696 | \n",
" -38,190 | \n",
"
\n",
" \n",
" | Total exported to grid (MWh) | \n",
" - | \n",
" - | \n",
"
\n",
" \n",
" | Total consumed from grid (MWh) | \n",
" 37,696 | \n",
" 38,190 | \n",
"
\n",
" \n",
" | Total nominated volume (MWh) | \n",
" -37,696 | \n",
" -37,696 | \n",
"
\n",
" \n",
" | Absolute imbalance volume (MWh) | \n",
" - | \n",
" 801 | \n",
"
\n",
" \n",
" | Mean selling price (€/MWh) | \n",
" - | \n",
" - | \n",
"
\n",
" \n",
" | Mean buying price (€/MWh) | \n",
" 41 | \n",
" 40 | \n",
"
\n",
" \n",
" | Total day-ahead result (€) | \n",
" -1,553,699 | \n",
" -1,553,699 | \n",
"
\n",
" \n",
" | Total POS result (€) | \n",
" - | \n",
" 22,954 | \n",
"
\n",
" \n",
" | Total NEG result (€) | \n",
" - | \n",
" -5,580 | \n",
"
\n",
" \n",
" | Total imbalance result (€) | \n",
" - | \n",
" 17,374 | \n",
"
\n",
" \n",
" | Total combined result (€) | \n",
" -1,553,699 | \n",
" -1,536,325 | \n",
"
\n",
" \n",
"
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" Heatpump only | \n",
" Heatpump + Storage | \n",
"
\n",
" \n",
" \n",
" \n",
" | Gasboiler OPEX (€) | \n",
" - | \n",
" - | \n",
"
\n",
" \n",
" | Gas consumption costs (€) | \n",
" 3,089,622 | \n",
" 3,089,622 | \n",
"
\n",
" \n",
" | CO2 emission costs (€) | \n",
" 1,095,004 | \n",
" 1,095,004 | \n",
"
\n",
" \n",
" | Gas taxes (€) | \n",
" 790,305 | \n",
" 790,305 | \n",
"
\n",
" \n",
" | Heatpump VDG OPEX (€) | \n",
" -46,600 | \n",
" -46,600 | \n",
"
\n",
" \n",
" | Heatpump NDG OPEX (€) | \n",
" -15,400 | \n",
" -15,400 | \n",
"
\n",
" \n",
" | Result on electricity market (€) | \n",
" -1,553,699 | \n",
" -1,536,325 | \n",
"
\n",
" \n",
" | Electricity taxes (€) | \n",
" -35,811 | \n",
" -36,280 | \n",
"
\n",
" \n",
" | Grid transport costs (€) | \n",
" -273,944 | \n",
" -275,718 | \n",
"
\n",
" \n",
" | HotWaterStorage OPEX (€) | \n",
" - | \n",
" -8,500 | \n",
"
\n",
" \n",
" | EBITDA (€) | \n",
" 3,049,476 | \n",
" 3,056,107 | \n",
"
\n",
" \n",
"
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" Year 0 | \n",
" Year 1 | \n",
" Year 2 | \n",
" Year 3 | \n",
" Year 4 | \n",
" Year 5 | \n",
" Year 6 | \n",
" Year 7 | \n",
" Year 8 | \n",
" Year 9 | \n",
" Year 10 | \n",
" Year 11 | \n",
" Year 12 | \n",
"
\n",
" \n",
" \n",
" \n",
" | CAPEX (€) | \n",
" -6,231,000 | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
"
\n",
" \n",
" | Regular Earnings (€) | \n",
" | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
"
\n",
" \n",
" | Irregular Cashflows (€) | \n",
" | \n",
" - | \n",
" - | \n",
" - | \n",
" - | \n",
" - | \n",
" - | \n",
" - | \n",
" - | \n",
" - | \n",
" - | \n",
" - | \n",
" - | \n",
"
\n",
" \n",
" | EBITDA (€) | \n",
" | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
"
\n",
" \n",
" | Depreciations (€) -/- | \n",
" | \n",
" -248,000 | \n",
" -248,000 | \n",
" -248,000 | \n",
" -248,000 | \n",
" -248,000 | \n",
" -248,000 | \n",
" -248,000 | \n",
" -248,000 | \n",
" -248,000 | \n",
" -248,000 | \n",
" -248,000 | \n",
" -248,000 | \n",
"
\n",
" \n",
" | EBIT (€) | \n",
" | \n",
" 2,801,481 | \n",
" 2,801,481 | \n",
" 2,801,481 | \n",
" 2,801,481 | \n",
" 2,801,481 | \n",
" 2,801,481 | \n",
" 2,801,481 | \n",
" 2,801,481 | \n",
" 2,801,481 | \n",
" 2,801,481 | \n",
" 2,801,481 | \n",
" 2,801,481 | \n",
"
\n",
" \n",
" | Income tax (Vpb.) (€) | \n",
" | \n",
" -687,120 | \n",
" -687,120 | \n",
" -687,120 | \n",
" -687,120 | \n",
" -687,120 | \n",
" -687,120 | \n",
" -687,120 | \n",
" -687,120 | \n",
" -687,120 | \n",
" -687,120 | \n",
" -687,120 | \n",
" -687,120 | \n",
"
\n",
" \n",
" | NOPLAT (€) | \n",
" | \n",
" 2,114,361 | \n",
" 2,114,361 | \n",
" 2,114,361 | \n",
" 2,114,361 | \n",
" 2,114,361 | \n",
" 2,114,361 | \n",
" 2,114,361 | \n",
" 2,114,361 | \n",
" 2,114,361 | \n",
" 2,114,361 | \n",
" 2,114,361 | \n",
" 2,114,361 | \n",
"
\n",
" \n",
" | Depreciations (€) +/+ | \n",
" | \n",
" 248,000 | \n",
" 248,000 | \n",
" 248,000 | \n",
" 248,000 | \n",
" 248,000 | \n",
" 248,000 | \n",
" 248,000 | \n",
" 248,000 | \n",
" 248,000 | \n",
" 248,000 | \n",
" 248,000 | \n",
" 248,000 | \n",
"
\n",
" \n",
" | Free Cash Flow (€) | \n",
" -6,231,000 | \n",
" 2,362,361 | \n",
" 2,362,361 | \n",
" 2,362,361 | \n",
" 2,362,361 | \n",
" 2,362,361 | \n",
" 2,362,361 | \n",
" 2,362,361 | \n",
" 2,362,361 | \n",
" 2,362,361 | \n",
" 2,362,361 | \n",
" 2,362,361 | \n",
" 2,362,361 | \n",
"
\n",
" \n",
" | Simple Payback Period | \n",
" 2.6 years | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
"
\n",
" \n",
" | IRR (%) | \n",
" 37% | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
"
\n",
" \n",
" | WACC (%) | \n",
" 10% | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
"
\n",
" \n",
" | NPV of explicit period (€) | \n",
" 8,968,545 | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
"
\n",
" \n",
" | Discounted residual value (€) | \n",
" 1,037,143 | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
"
\n",
" \n",
" | NPV (€) | \n",
" 10,005,689 | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
"
\n",
" \n",
"
\n",
"