{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "source": [
    "#### Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-2.32.0.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C:\\Users\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\__init__.py\n"
     ]
    }
   ],
   "source": [
    "from datetime import timedelta, datetime\n",
    "import json\n",
    "import pprint\n",
    "from copy import deepcopy\n",
    "import pytz\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",
    "import sys\n",
    "\n",
    "import os\n",
    " \n",
    "# Path to the folder containing the alternate version of PyRecoy\n",
    "\n",
    "alternate_pyrecoy_path = 'C:\\\\Users\\\\z004yn8c\\\\OneDrive - Siemens AG\\\\Documents\\\\GitHub\\\\Mooi-Kickstart\\\\pyrecoy\\\\pyrecoy'\n",
    " \n",
    "# Add the path to sys.path\n",
    "\n",
    "if alternate_pyrecoy_path not in sys.path:\n",
    "\n",
    "    sys.path.insert(0, alternate_pyrecoy_path)\n",
    " \n",
    "# Now import PyRecoy\n",
    "\n",
    "import pyrecoy2\n",
    "\n",
    "# Check the version or path to confirm\n",
    "\n",
    "print(pyrecoy2.__file__)\n",
    "\n",
    "\n",
    "from pyrecoy2.assets_kickstart import Heatpump, Eboiler, GasBoiler, HotWaterStorage\n",
    "from pyrecoy2.colors import *\n",
    "from pyrecoy2.converters import *\n",
    "from pyrecoy2.financial import calculate_eb_ode, get_tax_tables, get_tax_rate, get_grid_tariffs_electricity\n",
    "from pyrecoy2.framework import TimeFramework\n",
    "from pyrecoy2.casestudy import CaseStudy\n",
    "from pyrecoy2.plotting import ebitda_bar_chart, npv_bar_chart\n",
    "from pyrecoy2.reports import CaseReport, ComparisonReport, BusinessCaseReport, SingleFigureComparison\n",
    "from pyrecoy2.sensitivity import SensitivityAnalysis\n",
    "from pyrecoy2.prices import get_tennet_data, get_afrr_capacity_fees_nl\n",
    "from pyrecoy2.forecasts import Mipf, Forecast\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",
    "* COP seems to have fix values, rather than COP curve"
   ]
  },
  {
   "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"
    ]
   },
   "source": [
    "# Kickstart: Heatpump Optimisation Framework\n",
    "\n",
    "***\n",
    "© Shahla Huseynova  \n",
    "July 2024\n",
    "##### Cases\n",
    "In this model, 4 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 boiler and heatpump run in hybrid mode, and are optimised on costs in real-time\n",
    "* **Heat pump & storage cases**: Heat pump only case is compared with different setup of storage +heat pump cases"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "source": [
    "#### Loading config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "outputs": [],
   "source": [
    "class Config():\n",
    "    start = '2023-01-01'\n",
    "    end = '2023-12-31'\n",
    "    # year = '2019'\n",
    "    # startdate = year + '-01-01'\n",
    "    # enddate = str(year) + '-12-31'\n",
    "    # start = datetime.strptime(startdate, \"%Y-%m-%d\").astimezone(pytz.timezone('Europe/Amsterdam'))\n",
    "    # end = datetime.strptime(enddate, \"%Y-%m-%d\").astimezone(pytz.timezone('Europe/Amsterdam'))\n",
    "    # start = start.astimezone(pytz.UTC)\n",
    "    # end = end.astimezone(pytz.UTC)\n",
    "    \n",
    "    hp_vdg_e_power = 1.5 # MW\n",
    "    # hp_ndg_e_power = 7.7 # MW\n",
    "    hp_min_load = 0\n",
    "    hp_lifetime = 25\n",
    "    hp_capex = 1_152_000 # EUR/MWth\n",
    "    hp_opex = 0.04 # in % of CAPEX\n",
    "    hp_devex = 0.005 # in % of CAPEX\n",
    "    \n",
    "    gb_power = 5 # MW\n",
    "    gb_efficiency = 0.9\n",
    "    \n",
    "    storage_power = 1\n",
    "    # storage_volume = 1000 *3/50\n",
    "    # storage_cap_per_volume = 50 * 1e-3\n",
    "    rated_capacity = 3\n",
    "    storage_lifetime = 25\n",
    "    storage_temperature = 144\n",
    "    # storage_min_level = storage_volume * storage_cap_per_volume * 0.05\n",
    "    storage_min_level = rated_capacity * 0.00\n",
    "    # storage_min_level = rated_capacity\n",
    "    storage_capex_per_MW = 0\n",
    "    storage_capex_per_MWh = 100_000\n",
    "    storage_opex_perc_of_capex = 0.03\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 = '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": 11,
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "outputs": [],
   "source": [
    "class Store():\n",
    "    pass"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "source": [
    "## Model set-up"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define the file paths\n",
    "excel_file_path = r'C:\\Users\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\Mooi-Kickstart\\Kickstart\\V2\\Demand_Data_Smurfit_Preprocessed3.xlsx'\n",
    "output_directory = r'C:\\Users\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\Mooi-Kickstart\\Kickstart\\V2\\data'\n",
    "output_file_name = 'smurfit_demand_preprocessed3.csv'\n",
    "csv_file_path = os.path.join(output_directory, output_file_name)\n",
    "\n",
    "df = pd.read_excel(excel_file_path)\n",
    "# df = df.fillna(0) \n",
    "\n",
    "# # Save the DataFrame to CSV\n",
    "df.to_csv(csv_file_path, index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "outputs": [],
   "source": [
    "def load_demand_data(c, s):\n",
    "    demand = pd.read_csv('data/smurfit_demand_preprocessed3.csv', delimiter=',', decimal='.')\n",
    "    dt_index = pd.date_range(\n",
    "        start=s.time_fw.start,\n",
    "        end=s.time_fw.start + timedelta(days=365), \n",
    "        freq='1T',\n",
    "        tz='Europe/Amsterdam')\n",
    "    dt_index = dt_index[:len(demand)]\n",
    "    demand.index = dt_index\n",
    "    demand['Total demand'] = demand['MW (VDG)']\n",
    "    \n",
    "    demand = demand[c.start:c.end]\n",
    "    return demand"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "s = Store()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "testetss\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\framework.py:41: 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",
      "C:\\Users\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\forecasts.py:62: FutureWarning:\n",
      "\n",
      "'T' is deprecated and will be removed in a future version, please use 'min' instead.\n",
      "\n",
      "C:\\Users\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\forecasts.py:115: FutureWarning:\n",
      "\n",
      "'T' is deprecated and will be removed in a future version, please use 'min' instead.\n",
      "\n",
      "C:\\Users\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\framework.py:54: FutureWarning:\n",
      "\n",
      "'T' is deprecated and will be removed in a future version, please use 'min' instead.\n",
      "\n",
      "C:\\Users\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\framework.py:54: FutureWarning:\n",
      "\n",
      "'T' is deprecated and will be removed in a future version, please use 'min' instead.\n",
      "\n",
      "C:\\Users\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\framework.py:54: FutureWarning:\n",
      "\n",
      "'T' is deprecated and will be removed in a future version, please use 'min' instead.\n",
      "\n",
      "C:\\Users\\z004yn8c\\AppData\\Local\\Temp\\ipykernel_15244\\2484316097.py:3: FutureWarning:\n",
      "\n",
      "'T' is deprecated and will be removed in a future version, please use 'min' instead.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "def setup_model(c):\n",
    "    s = Store()\n",
    "    \n",
    "    s.time_fw = TimeFramework(start=c.start, end=c.end)\n",
    "    # s.minute_ix = s.time_fw.dt_index(freq='1T')\n",
    "    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",
    "    s.baseline = CaseStudy(time_fw=s.time_fw, freq='1T', name='Baseline')\n",
    "    s.hpcase = CaseStudy(time_fw=s.time_fw, freq='1T', name='Heatpump only', data=mipf)\n",
    "    #s.hpcase_sde = CaseStudy(time_fw=s.time_fw, freq='1T', name='Heatpump + SDE', data=mipf)\n",
    "    #s.optcase1 = CaseStudy(time_fw=s.time_fw, freq='1T', name='Optimisation', data=mipf)\n",
    "    s.storage_case_PCM = CaseStudy(time_fw=s.time_fw, freq='1T', name='Heatpump + Storage_PCM', data=mipf)\n",
    "    # s.storage_case_TCM = CaseStudy(time_fw=s.time_fw, freq='1T', name='Heatpump + Storage_TCM', data=mipf)\n",
    "    # s.storage_case_battery = CaseStudy(time_fw=s.time_fw, freq='1T', name='Heatpump + Storage_battery', data=mipf)\n",
    "    s.cases = list(CaseStudy.instances.values())\n",
    "    s.optcases = [s.hpcase, s.storage_case_PCM]\n",
    "    s.sde_cases = []\n",
    "    \n",
    "    s.demand = load_demand_data(c, s)\n",
    "    return s\n",
    "\n",
    "s = setup_model(c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# s.demand.resample('15T').mean()[['Tsource (VDG)', 'Tsink (VDG)']].iplot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>Tsource (VDG)</th>\n",
       "      <th>Tsink (VDG)</th>\n",
       "      <th>MW (VDG)</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>70</td>\n",
       "      <td>144</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-01 00:01:00+01:00</th>\n",
       "      <td>70</td>\n",
       "      <td>144</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-01 00:02:00+01:00</th>\n",
       "      <td>70</td>\n",
       "      <td>144</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-01 00:03:00+01:00</th>\n",
       "      <td>70</td>\n",
       "      <td>144</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-01 00:04:00+01:00</th>\n",
       "      <td>70</td>\n",
       "      <td>144</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-31 23:55:00+01:00</th>\n",
       "      <td>70</td>\n",
       "      <td>144</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-31 23:56:00+01:00</th>\n",
       "      <td>70</td>\n",
       "      <td>144</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-31 23:57:00+01:00</th>\n",
       "      <td>70</td>\n",
       "      <td>144</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-31 23:58:00+01:00</th>\n",
       "      <td>70</td>\n",
       "      <td>144</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-31 23:59:00+01:00</th>\n",
       "      <td>70</td>\n",
       "      <td>144</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>525600 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Tsource (VDG)  Tsink (VDG)  MW (VDG)  Total demand\n",
       "2023-01-01 00:00:00+01:00             70          144         1             1\n",
       "2023-01-01 00:01:00+01:00             70          144         1             1\n",
       "2023-01-01 00:02:00+01:00             70          144         1             1\n",
       "2023-01-01 00:03:00+01:00             70          144         1             1\n",
       "2023-01-01 00:04:00+01:00             70          144         1             1\n",
       "...                                  ...          ...       ...           ...\n",
       "2023-12-31 23:55:00+01:00             70          144         1             1\n",
       "2023-12-31 23:56:00+01:00             70          144         1             1\n",
       "2023-12-31 23:57:00+01:00             70          144         1             1\n",
       "2023-12-31 23:58:00+01:00             70          144         1             1\n",
       "2023-12-31 23:59:00+01:00             70          144         1             1\n",
       "\n",
       "[525600 rows x 4 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.demand"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "source": [
    "## Load in data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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": 21,
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\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\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\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\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\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\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\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\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\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\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\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",
    "    \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",
    "        case.data['DAM_avg'] = case.data.groupby(case.data.index.date)['DAM'].transform('mean')\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",
    "\n",
    "    s.demand['Tsource (VDG)'] += c.tsource_delta\n",
    "    s.demand['Tsink (VDG)'] += 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": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "75.08224016788466"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.hpcase.data['CO2 prices (€/ton)'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>DAM_avg</th>\n",
       "      <th>Tsource (VDG)</th>\n",
       "      <th>Tsink (VDG)</th>\n",
       "      <th>MW (VDG)</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",
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       "    <tr>\n",
       "      <th>2023-01-01 00:01:00+01:00</th>\n",
       "      <td>-3.61</td>\n",
       "      <td>-209.40</td>\n",
       "      <td>-209.40</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>63.998</td>\n",
       "      <td>5.23</td>\n",
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       "      <td>18.144167</td>\n",
       "      <td>70</td>\n",
       "      <td>144</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-01 00:02:00+01:00</th>\n",
       "      <td>-3.61</td>\n",
       "      <td>-209.40</td>\n",
       "      <td>-209.40</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>63.998</td>\n",
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       "      <td>1.01</td>\n",
       "      <td>18.144167</td>\n",
       "      <td>70</td>\n",
       "      <td>144</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-01 00:03:00+01:00</th>\n",
       "      <td>-3.61</td>\n",
       "      <td>-209.40</td>\n",
       "      <td>-209.40</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>18.144167</td>\n",
       "      <td>70</td>\n",
       "      <td>144</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>2023-01-01 00:04:00+01:00</th>\n",
       "      <td>-3.61</td>\n",
       "      <td>-209.40</td>\n",
       "      <td>-209.40</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>18.144167</td>\n",
       "      <td>70</td>\n",
       "      <td>144</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>2023-12-31 23:55:00+01:00</th>\n",
       "      <td>3.17</td>\n",
       "      <td>-6.81</td>\n",
       "      <td>-6.81</td>\n",
       "      <td>-7.10</td>\n",
       "      <td>-11.16</td>\n",
       "      <td>29.927</td>\n",
       "      <td>77.25</td>\n",
       "      <td>14.90</td>\n",
       "      <td>14.683333</td>\n",
       "      <td>70</td>\n",
       "      <td>144</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-31 23:56:00+01:00</th>\n",
       "      <td>3.17</td>\n",
       "      <td>-6.81</td>\n",
       "      <td>-6.81</td>\n",
       "      <td>-5.21</td>\n",
       "      <td>-8.12</td>\n",
       "      <td>29.927</td>\n",
       "      <td>77.25</td>\n",
       "      <td>14.90</td>\n",
       "      <td>14.683333</td>\n",
       "      <td>70</td>\n",
       "      <td>144</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-31 23:57:00+01:00</th>\n",
       "      <td>3.17</td>\n",
       "      <td>-6.81</td>\n",
       "      <td>-6.81</td>\n",
       "      <td>-5.61</td>\n",
       "      <td>-7.59</td>\n",
       "      <td>29.927</td>\n",
       "      <td>77.25</td>\n",
       "      <td>14.90</td>\n",
       "      <td>14.683333</td>\n",
       "      <td>70</td>\n",
       "      <td>144</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-31 23:58:00+01:00</th>\n",
       "      <td>3.17</td>\n",
       "      <td>-6.81</td>\n",
       "      <td>-6.81</td>\n",
       "      <td>-5.74</td>\n",
       "      <td>-7.87</td>\n",
       "      <td>29.927</td>\n",
       "      <td>77.25</td>\n",
       "      <td>14.90</td>\n",
       "      <td>14.683333</td>\n",
       "      <td>70</td>\n",
       "      <td>144</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-31 23:59:00+01:00</th>\n",
       "      <td>3.17</td>\n",
       "      <td>-6.81</td>\n",
       "      <td>-6.81</td>\n",
       "      <td>-5.70</td>\n",
       "      <td>-7.27</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.683333</td>\n",
       "      <td>70</td>\n",
       "      <td>144</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>525600 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            DAM     POS     NEG  ForeNeg  ForePos  \\\n",
       "2023-01-01 00:00:00+01:00 -3.61 -209.40 -209.40      NaN      NaN   \n",
       "2023-01-01 00:01:00+01:00 -3.61 -209.40 -209.40      NaN      NaN   \n",
       "2023-01-01 00:02:00+01:00 -3.61 -209.40 -209.40      NaN      NaN   \n",
       "2023-01-01 00:03:00+01:00 -3.61 -209.40 -209.40      NaN      NaN   \n",
       "2023-01-01 00:04:00+01:00 -3.61 -209.40 -209.40      NaN      NaN   \n",
       "...                         ...     ...     ...      ...      ...   \n",
       "2023-12-31 23:55:00+01:00  3.17   -6.81   -6.81    -7.10   -11.16   \n",
       "2023-12-31 23:56:00+01:00  3.17   -6.81   -6.81    -5.21    -8.12   \n",
       "2023-12-31 23:57:00+01:00  3.17   -6.81   -6.81    -5.61    -7.59   \n",
       "2023-12-31 23:58:00+01:00  3.17   -6.81   -6.81    -5.74    -7.87   \n",
       "2023-12-31 23:59:00+01:00  3.17   -6.81   -6.81    -5.70    -7.27   \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",
       "2023-12-31 23:55:00+01:00              29.927               77.25   \n",
       "2023-12-31 23:56:00+01:00              29.927               77.25   \n",
       "2023-12-31 23:57:00+01:00              29.927               77.25   \n",
       "2023-12-31 23:58:00+01:00              29.927               77.25   \n",
       "2023-12-31 23:59:00+01:00                 NaN                 NaN   \n",
       "\n",
       "                           CO2 prices (€/MWh)    DAM_avg  Tsource (VDG)  \\\n",
       "2023-01-01 00:00:00+01:00                1.01  18.144167             70   \n",
       "2023-01-01 00:01:00+01:00                1.01  18.144167             70   \n",
       "2023-01-01 00:02:00+01:00                1.01  18.144167             70   \n",
       "2023-01-01 00:03:00+01:00                1.01  18.144167             70   \n",
       "2023-01-01 00:04:00+01:00                1.01  18.144167             70   \n",
       "...                                       ...        ...            ...   \n",
       "2023-12-31 23:55:00+01:00               14.90  14.683333             70   \n",
       "2023-12-31 23:56:00+01:00               14.90  14.683333             70   \n",
       "2023-12-31 23:57:00+01:00               14.90  14.683333             70   \n",
       "2023-12-31 23:58:00+01:00               14.90  14.683333             70   \n",
       "2023-12-31 23:59:00+01:00                 NaN  14.683333             70   \n",
       "\n",
       "                           Tsink (VDG)  MW (VDG)  Total demand  \n",
       "2023-01-01 00:00:00+01:00          144         1             1  \n",
       "2023-01-01 00:01:00+01:00          144         1             1  \n",
       "2023-01-01 00:02:00+01:00          144         1             1  \n",
       "2023-01-01 00:03:00+01:00          144         1             1  \n",
       "2023-01-01 00:04:00+01:00          144         1             1  \n",
       "...                                ...       ...           ...  \n",
       "2023-12-31 23:55:00+01:00          144         1             1  \n",
       "2023-12-31 23:56:00+01:00          144         1             1  \n",
       "2023-12-31 23:57:00+01:00          144         1             1  \n",
       "2023-12-31 23:58:00+01:00          144         1             1  \n",
       "2023-12-31 23:59:00+01:00          144         1             1  \n",
       "\n",
       "[525600 rows x 13 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.storage_case_PCM.data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "source": [
    "## Assets"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "source": [
    "### COP curve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "outputs": [],
   "source": [
    "def cop_curve_new(Tsink, Tsource):\n",
    "    Tsink += 273\n",
    "    Tsource += 273\n",
    "    Tlift = Tsink - Tsource\n",
    "\n",
    "    c0 = 0.0005426*Tlift**2 - 0.1178*Tlift + 6.962\n",
    "    c1 = 6.7058 \n",
    "    c2 = -1.79\n",
    "    \n",
    "    return Polynomial([c0, c1, c2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$x \\mapsto \\text{19.2496754} + \\text{6.7058}\\,x - \\text{1.79}\\,x^{2}$"
      ],
      "text/plain": [
       "Polynomial([19.2496754,  6.7058   , -1.79     ], domain=[-1,  1], window=[-1,  1], symbol='x')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sourceT = 63 + 273\n",
    "sinkT = 140 + 273\n",
    "cop_curve_new(sourceT, sinkT)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "source": [
    "### Create and assign assets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1152000\n"
     ]
    }
   ],
   "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=2.9\n",
    "    )\n",
    "\n",
    "    heatpump_pcm = Heatpump(\n",
    "        name='Heatpump PCM',\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=2.9\n",
    "    )\n",
    "        \n",
    "    capex_vdg = c.hp_capex * 1\n",
    "    heatpump_vdg.set_financials(capex=capex_vdg, opex=c.hp_opex*capex_vdg, devex=c.hp_devex*capex_vdg, lifetime=25)\n",
    "\n",
    "    print(capex_vdg)\n",
    "    capex_pcm = c.hp_capex * heatpump_vdg.max_th_power\n",
    "    heatpump_pcm.set_financials(capex=capex_pcm, opex=c.hp_opex*capex_pcm, devex=c.hp_devex*capex_pcm, lifetime=25)\n",
    "    # print(capex_pcm)\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",
    "    PCM = HotWaterStorage(\n",
    "        name='PCM_TES',\n",
    "        rated_power=c.storage_power, \n",
    "        # capacity_per_volume=None,\n",
    "        # volume=None, \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 * PCM.max_power + c.storage_capex_per_MWh * PCM.capacity\n",
    "    opex_ws = c.storage_opex_perc_of_capex * capex_ws\n",
    "    PCM.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.storage_case_PCM.add_asset(heatpump_pcm)\n",
    "    s.storage_case_PCM.add_asset(PCM)\n",
    "    # s.storage_case_PCM.add_asset(heatpump_vdg)\n",
    "    return s\n",
    "\n",
    "s = create_and_assign_assets(c, s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "300000"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "capex_ws = c.storage_capex_per_MW * 1 + c.storage_capex_per_MWh * 3\n",
    "capex_ws"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "HotWaterStorage(name=PCM_TES, rated_power=1, capacity=3, temperature=144, min_storagelevel=0.0)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.storage_case_PCM.assets['PCM_TES']"
   ]
  },
  {
   "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)']).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",
    "    demand_vdg = case.data['MW (VDG)'].to_list()\n",
    "    Tsink_vdg = case.data['Tsink (VDG)'].to_list()\n",
    "    Tsource_vdg = case.data['Tsource (VDG)'].to_list()\n",
    "\n",
    "    hp_vdg_input = [0] * len(case.data)\n",
    "    hp_vdg_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",
    "    case.data['hp_output_MW'] = np.array(hp_vdg_output)\n",
    "    case.data['hp_input_MW'] = np.array(hp_vdg_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(5)\n",
    "    return case"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "def hp_storage_opt_enginge(c, PCM, hp_vdg, pos, neg, dam, demand_vdg, tsource_vdg, tsink_vdg):\n",
    "    \n",
    "    from_storage_vdg_MW = 0\n",
    "    to_storage_vdg_MW = 0  \n",
    "    \n",
    "    if neg < dam - c.threshold:\n",
    "        # overproduce\n",
    "        if demand_vdg != 0:\n",
    "            storage_charge_power = PCM.charging_power_limit\n",
    "            # cop = 2.5\n",
    "            if round(PCM.chargelevel,5) == round(PCM.max_chargelevel,5):\n",
    "                storage_charge_power = 0\n",
    "                cop = 2.9\n",
    "            else:\n",
    "                # Adjust charge power if charge level is not at max\n",
    "                storage_charge_power = min(PCM.charging_power_limit, (PCM.max_chargelevel - PCM.chargelevel) * 60)\n",
    "                cop = 2.5\n",
    "\n",
    "            desired_hp_load_vdg = min(demand_vdg + storage_charge_power, 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, cop = cop)\n",
    "\n",
    "            to_storage_vdg_MW = desired_hp_load_vdg - demand_vdg\n",
    "            to_storage_vdg_MW = -PCM.charge(round(to_storage_vdg_MW, 5))\n",
    "            # #Added lately\n",
    "            # extra_charging_power_constraint = ws.max_power - to_storage_vdg_MW\n",
    "            # desired_hp_load_new = min(demand_vdg + min(storage_charge_power, extra_charging_power_constraint) - 0.66, hp_vdg.max_th_power)\n",
    "            # e_load_vdg, th_load_vdg = hp_vdg.set_heat_output(desired_hp_load_new, tsink_vdg, tsource_vdg)\n",
    "\n",
    "        else:\n",
    "            e_load_vdg, th_load_vdg = (0,0)\n",
    "            \n",
    "            \n",
    "\n",
    "    elif pos > dam + c.threshold:\n",
    "        # take from storage\n",
    "        if demand_vdg != 0:\n",
    "            from_storage_vdg_MW = demand_vdg\n",
    "            from_storage_vdg_MW = PCM.discharge(round(from_storage_vdg_MW, 5))\n",
    "            # from_storage_vdg_MW = min(ws.max_power - from_storage_vdg_MW, ws.discharging_power_limit)\n",
    "            desired_hp_load_vdg = min(demand_vdg - from_storage_vdg_MW, 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, cop = 2.9)\n",
    "        else:\n",
    "            e_load_vdg, th_load_vdg = (0,0)\n",
    "            \n",
    "        #print({f'from_storage_vdg_MW='})\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",
    "            cop = 2.9\n",
    "        )\n",
    "\n",
    "    return e_load_vdg, th_load_vdg, tsource_vdg, to_storage_vdg_MW, from_storage_vdg_MW, PCM, hp_vdg\n",
    "# Neg-take price, Pos-feed price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "outputs": [],
   "source": [
    "def hponly_with_storage(case):\n",
    "    hp_vdg = case.assets['Heatpump PCM']\n",
    "    PCM = case.assets['PCM_TES']\n",
    "    demands_vdg = case.data['MW (VDG)'].to_list()\n",
    "    Tsink_vdg = case.data['Tsink (VDG)'].to_list()\n",
    "    Tsource_vdg = case.data['Tsource (VDG)'].to_list()\n",
    "    dam_prices = case.data['DAM_avg'].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_vdg_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",
    "\n",
    "    new_tsources_vdg = case.data['Tsource (VDG)'].to_list()\n",
    "\n",
    "    \n",
    "    PCM.set_chargelevel(PCM.min_chargelevel)\n",
    "    \n",
    "    for m in range(minutes):\n",
    "        tsource_vdg = Tsource_vdg[m]\n",
    "        tsink_vdg = Tsink_vdg[m]\n",
    "        demand_vdg = demands_vdg[m]\n",
    "        \n",
    "        e_load_vdg, th_load_vdg, tsource_vdg, to_storage_vdg_MW, from_storage_vdg_MW, PCM, hp_vdg = hp_storage_opt_enginge(\n",
    "            c, PCM, hp_vdg, pos_prices[m], neg_prices[m], dam_prices[m], demand_vdg, tsource_vdg, tsink_vdg\n",
    "        )\n",
    "            \n",
    "        hp_vdg_input[m] = e_load_vdg\n",
    "        hp_vdg_output[m] = th_load_vdg\n",
    "            \n",
    "        storage_levels[m] = PCM.chargelevel\n",
    "        new_tsources_vdg[m] = tsource_vdg\n",
    "        to_storage_vdg_list[m] = to_storage_vdg_MW\n",
    "        from_storage_vdg_list[m] = from_storage_vdg_MW\n",
    "        \n",
    "    case.data['hp_output_MW'] = np.array(hp_vdg_output)\n",
    "    case.data['hp_input_MW'] = np.array(hp_vdg_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['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']\n",
    "    case.data['from_storage_MW'] = case.data['from_storage_vdg_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(5)\n",
    "    return case\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "s.storage_case_PCM = hponly_with_storage(s.storage_case_PCM)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "# s.storage_case_PCM.data['cop'].fillna(2.5, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "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>DAM_avg</th>\n",
       "      <th>Tsource (VDG)</th>\n",
       "      <th>...</th>\n",
       "      <th>from_storage_vdg_MW</th>\n",
       "      <th>to_storage_MW</th>\n",
       "      <th>from_storage_MW</th>\n",
       "      <th>storage_level_MWh</th>\n",
       "      <th>hp_output_MWh</th>\n",
       "      <th>hp_input_MWh</th>\n",
       "      <th>to_storage_vdg_MWh</th>\n",
       "      <th>from_storage_vdg_MWh</th>\n",
       "      <th>to_storage_MWh</th>\n",
       "      <th>from_storage_MWh</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-03-08 11:18:00+01:00</th>\n",
       "      <td>144.18</td>\n",
       "      <td>-444.24</td>\n",
       "      <td>-444.24</td>\n",
       "      <td>160.45</td>\n",
       "      <td>152.49</td>\n",
       "      <td>45.204</td>\n",
       "      <td>92.44</td>\n",
       "      <td>17.83</td>\n",
       "      <td>139.14583</td>\n",
       "      <td>70</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.90833</td>\n",
       "      <td>0.02500</td>\n",
       "      <td>-0.01000</td>\n",
       "      <td>0.00833</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00833</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-10-26 18:29:00+02:00</th>\n",
       "      <td>151.05</td>\n",
       "      <td>95.56</td>\n",
       "      <td>95.56</td>\n",
       "      <td>94.62</td>\n",
       "      <td>94.58</td>\n",
       "      <td>48.888</td>\n",
       "      <td>79.40</td>\n",
       "      <td>15.31</td>\n",
       "      <td>124.03500</td>\n",
       "      <td>70</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.00000</td>\n",
       "      <td>0.01667</td>\n",
       "      <td>-0.00575</td>\n",
       "      <td>-0.00000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.00000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                              DAM     POS     NEG  ForeNeg  ForePos  \\\n",
       "2023-03-08 11:18:00+01:00  144.18 -444.24 -444.24   160.45   152.49   \n",
       "2023-10-26 18:29:00+02:00  151.05   95.56   95.56    94.62    94.58   \n",
       "\n",
       "                           Gas prices (€/MWh)  CO2 prices (€/ton)  \\\n",
       "2023-03-08 11:18:00+01:00              45.204               92.44   \n",
       "2023-10-26 18:29:00+02:00              48.888               79.40   \n",
       "\n",
       "                           CO2 prices (€/MWh)    DAM_avg  Tsource (VDG)  ...  \\\n",
       "2023-03-08 11:18:00+01:00               17.83  139.14583             70  ...   \n",
       "2023-10-26 18:29:00+02:00               15.31  124.03500             70  ...   \n",
       "\n",
       "                           from_storage_vdg_MW  to_storage_MW  \\\n",
       "2023-03-08 11:18:00+01:00                  0.0            0.5   \n",
       "2023-10-26 18:29:00+02:00                  0.0           -0.0   \n",
       "\n",
       "                           from_storage_MW  storage_level_MWh  hp_output_MWh  \\\n",
       "2023-03-08 11:18:00+01:00              0.0            2.90833        0.02500   \n",
       "2023-10-26 18:29:00+02:00              0.0            3.00000        0.01667   \n",
       "\n",
       "                           hp_input_MWh  to_storage_vdg_MWh  \\\n",
       "2023-03-08 11:18:00+01:00      -0.01000             0.00833   \n",
       "2023-10-26 18:29:00+02:00      -0.00575            -0.00000   \n",
       "\n",
       "                           from_storage_vdg_MWh  to_storage_MWh  \\\n",
       "2023-03-08 11:18:00+01:00                   0.0         0.00833   \n",
       "2023-10-26 18:29:00+02:00                   0.0        -0.00000   \n",
       "\n",
       "                           from_storage_MWh  \n",
       "2023-03-08 11:18:00+01:00               0.0  \n",
       "2023-10-26 18:29:00+02:00               0.0  \n",
       "\n",
       "[2 rows x 28 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.storage_case_PCM.data.sample(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1222.5108"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.storage_case_PCM.data['to_storage_MWh'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "s.storage_case_PCM.data.to_csv('storage_data_case1.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "# s.storage_case_PCM.data.to_excel('storage_data_case1.xlsx', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "s.hpcase.data.to_csv('storage_data_hp.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "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>hp_output_MW</th>\n",
       "      <th>to_storage_MW</th>\n",
       "      <th>Total demand</th>\n",
       "      <th>cop</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>525600.000000</td>\n",
       "      <td>525600.000000</td>\n",
       "      <td>525600.000000</td>\n",
       "      <td>525600.000000</td>\n",
       "      <td>525600.000000</td>\n",
       "      <td>525600.0</td>\n",
       "      <td>452694.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>95.817313</td>\n",
       "      <td>93.568163</td>\n",
       "      <td>103.438997</td>\n",
       "      <td>1.000300</td>\n",
       "      <td>0.139612</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.770323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>49.046697</td>\n",
       "      <td>194.977533</td>\n",
       "      <td>195.696551</td>\n",
       "      <td>0.457122</td>\n",
       "      <td>0.224309</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.187229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-500.000000</td>\n",
       "      <td>-1549.470000</td>\n",
       "      <td>-1549.470000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>76.935000</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>57.967500</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>99.215000</td>\n",
       "      <td>84.130000</td>\n",
       "      <td>88.570000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>122.400000</td>\n",
       "      <td>114.020000</td>\n",
       "      <td>119.592500</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>463.770000</td>\n",
       "      <td>2037.740000</td>\n",
       "      <td>2037.740000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.900000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 DAM            POS            NEG   hp_output_MW  \\\n",
       "count  525600.000000  525600.000000  525600.000000  525600.000000   \n",
       "mean       95.817313      93.568163     103.438997       1.000300   \n",
       "std        49.046697     194.977533     195.696551       0.457122   \n",
       "min      -500.000000   -1549.470000   -1549.470000       0.000000   \n",
       "25%        76.935000      47.000000      57.967500       1.000000   \n",
       "50%        99.215000      84.130000      88.570000       1.000000   \n",
       "75%       122.400000     114.020000     119.592500       1.500000   \n",
       "max       463.770000    2037.740000    2037.740000       1.500000   \n",
       "\n",
       "       to_storage_MW  Total demand            cop  \n",
       "count  525600.000000      525600.0  452694.000000  \n",
       "mean        0.139612           1.0       2.770323  \n",
       "std         0.224309           0.0       0.187229  \n",
       "min         0.000000           1.0       2.500000  \n",
       "25%        -0.000000           1.0       2.500000  \n",
       "50%         0.000000           1.0       2.900000  \n",
       "75%         0.500000           1.0       2.900000  \n",
       "max         0.500000           1.0       2.900000  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.storage_case_PCM.data[['DAM', 'POS', 'NEG', 'hp_output_MW', 'to_storage_MW', 'Total demand', 'cop']].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "        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>hp_output_MW</th>\n",
       "      <th>to_storage_MW</th>\n",
       "      <th>from_storage_MW</th>\n",
       "      <th>Total demand</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-07-21 11:08:00+02:00</th>\n",
       "      <td>89.55</td>\n",
       "      <td>2.09</td>\n",
       "      <td>2.09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-05-17 22:04:00+02:00</th>\n",
       "      <td>111.00</td>\n",
       "      <td>98.58</td>\n",
       "      <td>98.58</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-11 14:39:00+02:00</th>\n",
       "      <td>87.86</td>\n",
       "      <td>102.65</td>\n",
       "      <td>102.65</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-06 21:28:00+01:00</th>\n",
       "      <td>115.68</td>\n",
       "      <td>97.26</td>\n",
       "      <td>97.26</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-29 18:56:00+01:00</th>\n",
       "      <td>149.90</td>\n",
       "      <td>70.09</td>\n",
       "      <td>70.09</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-24 02:22:00+01:00</th>\n",
       "      <td>125.80</td>\n",
       "      <td>93.41</td>\n",
       "      <td>93.41</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-04-05 21:32:00+02:00</th>\n",
       "      <td>164.98</td>\n",
       "      <td>109.75</td>\n",
       "      <td>109.75</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-10-17 15:06:00+02:00</th>\n",
       "      <td>97.25</td>\n",
       "      <td>-83.29</td>\n",
       "      <td>-83.29</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-03 22:01:00+01:00</th>\n",
       "      <td>45.53</td>\n",
       "      <td>50.22</td>\n",
       "      <td>50.22</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-19 22:12:00+01:00</th>\n",
       "      <td>75.86</td>\n",
       "      <td>261.50</td>\n",
       "      <td>261.50</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-22 01:35:00+01:00</th>\n",
       "      <td>95.01</td>\n",
       "      <td>98.52</td>\n",
       "      <td>98.52</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-05-20 23:59:00+02:00</th>\n",
       "      <td>73.02</td>\n",
       "      <td>60.86</td>\n",
       "      <td>60.86</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-17 15:23:00+01:00</th>\n",
       "      <td>147.72</td>\n",
       "      <td>144.24</td>\n",
       "      <td>144.24</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-06 14:19:00+02:00</th>\n",
       "      <td>-4.75</td>\n",
       "      <td>-23.52</td>\n",
       "      <td>-23.52</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-05-11 02:09:00+02:00</th>\n",
       "      <td>96.00</td>\n",
       "      <td>95.12</td>\n",
       "      <td>95.12</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-25 16:06:00+01:00</th>\n",
       "      <td>93.90</td>\n",
       "      <td>-57.08</td>\n",
       "      <td>-57.08</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-17 15:54:00+01:00</th>\n",
       "      <td>129.76</td>\n",
       "      <td>182.40</td>\n",
       "      <td>182.40</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-22 21:24:00+01:00</th>\n",
       "      <td>102.82</td>\n",
       "      <td>142.20</td>\n",
       "      <td>142.20</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-21 15:39:00+02:00</th>\n",
       "      <td>87.30</td>\n",
       "      <td>77.82</td>\n",
       "      <td>77.82</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-22 04:49:00+02:00</th>\n",
       "      <td>99.61</td>\n",
       "      <td>-117.94</td>\n",
       "      <td>-117.94</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              DAM     POS     NEG  hp_output_MW  \\\n",
       "2023-07-21 11:08:00+02:00   89.55    2.09    2.09           1.0   \n",
       "2023-05-17 22:04:00+02:00  111.00   98.58   98.58           0.0   \n",
       "2023-09-11 14:39:00+02:00   87.86  102.65  102.65           1.0   \n",
       "2023-12-06 21:28:00+01:00  115.68   97.26   97.26           1.5   \n",
       "2023-01-29 18:56:00+01:00  149.90   70.09   70.09           1.5   \n",
       "2023-02-24 02:22:00+01:00  125.80   93.41   93.41           1.5   \n",
       "2023-04-05 21:32:00+02:00  164.98  109.75  109.75           1.5   \n",
       "2023-10-17 15:06:00+02:00   97.25  -83.29  -83.29           1.0   \n",
       "2023-11-03 22:01:00+01:00   45.53   50.22   50.22           1.0   \n",
       "2023-12-19 22:12:00+01:00   75.86  261.50  261.50           1.0   \n",
       "2023-11-22 01:35:00+01:00   95.01   98.52   98.52           1.0   \n",
       "2023-05-20 23:59:00+02:00   73.02   60.86   60.86           1.0   \n",
       "2023-01-17 15:23:00+01:00  147.72  144.24  144.24           1.0   \n",
       "2023-08-06 14:19:00+02:00   -4.75  -23.52  -23.52           1.5   \n",
       "2023-05-11 02:09:00+02:00   96.00   95.12   95.12           1.0   \n",
       "2023-02-25 16:06:00+01:00   93.90  -57.08  -57.08           1.5   \n",
       "2023-11-17 15:54:00+01:00  129.76  182.40  182.40           0.0   \n",
       "2023-11-22 21:24:00+01:00  102.82  142.20  142.20           0.0   \n",
       "2023-08-21 15:39:00+02:00   87.30   77.82   77.82           1.5   \n",
       "2023-09-22 04:49:00+02:00   99.61 -117.94 -117.94           1.0   \n",
       "\n",
       "                           to_storage_MW  from_storage_MW  Total demand  \n",
       "2023-07-21 11:08:00+02:00           -0.0              0.0             1  \n",
       "2023-05-17 22:04:00+02:00            0.0              1.0             1  \n",
       "2023-09-11 14:39:00+02:00           -0.0              0.0             1  \n",
       "2023-12-06 21:28:00+01:00            0.5              0.0             1  \n",
       "2023-01-29 18:56:00+01:00            0.5              0.0             1  \n",
       "2023-02-24 02:22:00+01:00            0.5              0.0             1  \n",
       "2023-04-05 21:32:00+02:00            0.5              0.0             1  \n",
       "2023-10-17 15:06:00+02:00           -0.0              0.0             1  \n",
       "2023-11-03 22:01:00+01:00            0.0              0.0             1  \n",
       "2023-12-19 22:12:00+01:00            0.0              0.0             1  \n",
       "2023-11-22 01:35:00+01:00            0.0              0.0             1  \n",
       "2023-05-20 23:59:00+02:00            0.0              0.0             1  \n",
       "2023-01-17 15:23:00+01:00            0.0              0.0             1  \n",
       "2023-08-06 14:19:00+02:00            0.5              0.0             1  \n",
       "2023-05-11 02:09:00+02:00            0.0              0.0             1  \n",
       "2023-02-25 16:06:00+01:00            0.5              0.0             1  \n",
       "2023-11-17 15:54:00+01:00            0.0              1.0             1  \n",
       "2023-11-22 21:24:00+01:00            0.0              1.0             1  \n",
       "2023-08-21 15:39:00+02:00            0.5              0.0             1  \n",
       "2023-09-22 04:49:00+02:00           -0.0              0.0             1  "
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "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": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['DAM', 'POS', 'NEG', 'ForeNeg', 'ForePos', 'Gas prices (€/MWh)',\n",
       "       'CO2 prices (€/ton)', 'CO2 prices (€/MWh)', 'DAM_avg', 'Tsource (VDG)',\n",
       "       'Tsink (VDG)', 'MW (VDG)', 'Total demand'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.hpcase.data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['DAM', 'POS', 'NEG', 'ForeNeg', 'ForePos', 'Gas prices (€/MWh)',\n",
       "       'CO2 prices (€/ton)', 'CO2 prices (€/MWh)', 'DAM_avg', 'Tsource (VDG)',\n",
       "       'Tsink (VDG)', 'MW (VDG)', 'Total demand', 'hp_output_MW',\n",
       "       'hp_input_MW', 'cop', 'tsource_vdg', 'to_storage_vdg_MW',\n",
       "       'from_storage_vdg_MW', 'to_storage_MW', 'from_storage_MW',\n",
       "       'storage_level_MWh', 'hp_output_MWh', 'hp_input_MWh',\n",
       "       'to_storage_vdg_MWh', 'from_storage_vdg_MWh', 'to_storage_MWh',\n",
       "       'from_storage_MWh'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.storage_case_PCM.data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "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": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</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>Total demand</th>\n",
       "      <th>hp_input_MW</th>\n",
       "      <th>hp_output_MW</th>\n",
       "      <th>cop</th>\n",
       "      <th>to_storage_MW</th>\n",
       "      <th>from_storage_MW</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-02-20 02:13:00+01:00</th>\n",
       "      <td>48.86</td>\n",
       "      <td>38.40</td>\n",
       "      <td>38.40</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.60000</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-18 15:09:00+02:00</th>\n",
       "      <td>88.37</td>\n",
       "      <td>-201.63</td>\n",
       "      <td>81.91</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.60000</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-26 15:21:00+02:00</th>\n",
       "      <td>79.82</td>\n",
       "      <td>32.42</td>\n",
       "      <td>32.42</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.60000</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-07-08 15:38:00+02:00</th>\n",
       "      <td>40.00</td>\n",
       "      <td>119.68</td>\n",
       "      <td>119.68</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.00000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-05-02 14:52:00+02:00</th>\n",
       "      <td>86.32</td>\n",
       "      <td>-13.68</td>\n",
       "      <td>-13.68</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.60000</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-10-15 17:20:00+02:00</th>\n",
       "      <td>111.60</td>\n",
       "      <td>86.69</td>\n",
       "      <td>86.69</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.00000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-05-18 15:07:00+02:00</th>\n",
       "      <td>43.08</td>\n",
       "      <td>19.02</td>\n",
       "      <td>19.02</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.34483</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-07 05:27:00+01:00</th>\n",
       "      <td>83.41</td>\n",
       "      <td>77.16</td>\n",
       "      <td>77.16</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.60000</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-06-23 13:05:00+02:00</th>\n",
       "      <td>86.71</td>\n",
       "      <td>96.50</td>\n",
       "      <td>96.50</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.34483</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-06-17 18:14:00+02:00</th>\n",
       "      <td>115.31</td>\n",
       "      <td>84.08</td>\n",
       "      <td>84.08</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.60000</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-06-27 02:11:00+02:00</th>\n",
       "      <td>93.03</td>\n",
       "      <td>76.60</td>\n",
       "      <td>76.60</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.34483</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-12 19:27:00+01:00</th>\n",
       "      <td>130.00</td>\n",
       "      <td>144.24</td>\n",
       "      <td>144.24</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.34483</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-07 03:15:00+01:00</th>\n",
       "      <td>99.90</td>\n",
       "      <td>74.79</td>\n",
       "      <td>74.79</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.34483</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-10 06:44:00+02:00</th>\n",
       "      <td>99.90</td>\n",
       "      <td>88.98</td>\n",
       "      <td>88.98</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.34483</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-17 05:58:00+01:00</th>\n",
       "      <td>103.20</td>\n",
       "      <td>89.88</td>\n",
       "      <td>89.88</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.34483</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-06-23 22:38:00+02:00</th>\n",
       "      <td>130.54</td>\n",
       "      <td>87.57</td>\n",
       "      <td>87.57</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.34483</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-08 10:21:00+01:00</th>\n",
       "      <td>118.78</td>\n",
       "      <td>187.08</td>\n",
       "      <td>187.08</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.00000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-06-15 18:24:00+02:00</th>\n",
       "      <td>125.39</td>\n",
       "      <td>97.00</td>\n",
       "      <td>97.00</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.34483</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-06-19 05:31:00+02:00</th>\n",
       "      <td>95.87</td>\n",
       "      <td>39.84</td>\n",
       "      <td>39.84</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.60000</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-07-18 12:15:00+02:00</th>\n",
       "      <td>75.00</td>\n",
       "      <td>67.22</td>\n",
       "      <td>67.22</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.60000</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              DAM     POS     NEG  Total demand  hp_input_MW  \\\n",
       "2023-02-20 02:13:00+01:00   48.86   38.40   38.40             1     -0.60000   \n",
       "2023-08-18 15:09:00+02:00   88.37 -201.63   81.91             1     -0.60000   \n",
       "2023-08-26 15:21:00+02:00   79.82   32.42   32.42             1     -0.60000   \n",
       "2023-07-08 15:38:00+02:00   40.00  119.68  119.68             1     -0.00000   \n",
       "2023-05-02 14:52:00+02:00   86.32  -13.68  -13.68             1     -0.60000   \n",
       "2023-10-15 17:20:00+02:00  111.60   86.69   86.69             1     -0.00000   \n",
       "2023-05-18 15:07:00+02:00   43.08   19.02   19.02             1     -0.34483   \n",
       "2023-11-07 05:27:00+01:00   83.41   77.16   77.16             1     -0.60000   \n",
       "2023-06-23 13:05:00+02:00   86.71   96.50   96.50             1     -0.34483   \n",
       "2023-06-17 18:14:00+02:00  115.31   84.08   84.08             1     -0.60000   \n",
       "2023-06-27 02:11:00+02:00   93.03   76.60   76.60             1     -0.34483   \n",
       "2023-01-12 19:27:00+01:00  130.00  144.24  144.24             1     -0.34483   \n",
       "2023-03-07 03:15:00+01:00   99.90   74.79   74.79             1     -0.34483   \n",
       "2023-08-10 06:44:00+02:00   99.90   88.98   88.98             1     -0.34483   \n",
       "2023-11-17 05:58:00+01:00  103.20   89.88   89.88             1     -0.34483   \n",
       "2023-06-23 22:38:00+02:00  130.54   87.57   87.57             1     -0.34483   \n",
       "2023-12-08 10:21:00+01:00  118.78  187.08  187.08             1     -0.00000   \n",
       "2023-06-15 18:24:00+02:00  125.39   97.00   97.00             1     -0.34483   \n",
       "2023-06-19 05:31:00+02:00   95.87   39.84   39.84             1     -0.60000   \n",
       "2023-07-18 12:15:00+02:00   75.00   67.22   67.22             1     -0.60000   \n",
       "\n",
       "                           hp_output_MW  cop  to_storage_MW  from_storage_MW  \n",
       "2023-02-20 02:13:00+01:00           1.5  2.5            0.5              0.0  \n",
       "2023-08-18 15:09:00+02:00           1.5  2.5            0.5              0.0  \n",
       "2023-08-26 15:21:00+02:00           1.5  2.5            0.5              0.0  \n",
       "2023-07-08 15:38:00+02:00           0.0  NaN            0.0              1.0  \n",
       "2023-05-02 14:52:00+02:00           1.5  2.5            0.5              0.0  \n",
       "2023-10-15 17:20:00+02:00           0.0  NaN            0.0              1.0  \n",
       "2023-05-18 15:07:00+02:00           1.0  2.9           -0.0              0.0  \n",
       "2023-11-07 05:27:00+01:00           1.5  2.5            0.5              0.0  \n",
       "2023-06-23 13:05:00+02:00           1.0  2.9            0.0              0.0  \n",
       "2023-06-17 18:14:00+02:00           1.5  2.5            0.5              0.0  \n",
       "2023-06-27 02:11:00+02:00           1.0  2.9           -0.0              0.0  \n",
       "2023-01-12 19:27:00+01:00           1.0  2.9            0.0              0.0  \n",
       "2023-03-07 03:15:00+01:00           1.0  2.9           -0.0              0.0  \n",
       "2023-08-10 06:44:00+02:00           1.0  2.9            0.0              0.0  \n",
       "2023-11-17 05:58:00+01:00           1.0  2.9           -0.0              0.0  \n",
       "2023-06-23 22:38:00+02:00           1.0  2.9            0.0              0.0  \n",
       "2023-12-08 10:21:00+01:00           0.0  NaN            0.0              1.0  \n",
       "2023-06-15 18:24:00+02:00           1.0  2.9            0.0              0.0  \n",
       "2023-06-19 05:31:00+02:00           1.5  2.5            0.5              0.0  \n",
       "2023-07-18 12:15:00+02:00           1.5  2.5            0.5              0.0  "
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "selection.sample(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "72906"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "none_count = selection['cop'].isnull().sum()\n",
    "none_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DAM                 95.817313\n",
       "POS                 93.568163\n",
       "NEG                103.438997\n",
       "Total demand         1.000000\n",
       "hp_input_MW         -0.368040\n",
       "hp_output_MW         1.000300\n",
       "cop                  2.770323\n",
       "to_storage_MW        0.139612\n",
       "from_storage_MW      0.139312\n",
       "dtype: float64"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "selection.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "########################\n",
    "\n",
    "# This is where we left\n",
    "\n",
    "########################"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "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": 56,
   "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",
    "    demand_vdg = case.data['MW (VDG)'].round(decimals).to_list()\n",
    "    Tsink_vdg = case.data['Tsink (VDG)'].round(decimals).to_list()\n",
    "    Tsource_vdg = case.data['Tsource (VDG)'].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",
    "\n",
    "        hp_out = hp_vdg_output\n",
    "        hp_output[m] = hp_out\n",
    "        hp_input[m] = hp_vdg_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": 58,
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "outputs": [],
   "source": [
    "def calc_afrr_capacity(case):\n",
    "    hp_vdg = case.assets['Heatpump VDG']\n",
    "    \n",
    "    capacity = 0\n",
    "    for hp in hp_vdg:\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": "markdown",
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "source": [
    "### Run optimisation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "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": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.899979700142095"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.hpcase.data['hp_output_MW'].sum() /s.hpcase.data['hp_input_MW'].abs().sum() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-181242.64800000025"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.hpcase.data['hp_input_MW'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.34483"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.hpcase.data['hp_input_MW'].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-193442.08086"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.storage_case_PCM.data['hp_input_MW'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.6"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.storage_case_PCM.data['hp_input_MW'].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.717906557159644"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "s.storage_case_PCM.data['hp_output_MW'].sum() /s.storage_case_PCM.data['hp_input_MW'].abs().sum() "
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  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
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       "<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>DAM_avg</th>\n",
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       "                            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)   DAM_avg  Tsource (VDG)  \\\n",
       "2023-01-01 00:00:00+01:00                1.01  18.14417             70   \n",
       "2023-01-01 00:01:00+01:00                1.01  18.14417             70   \n",
       "2023-01-01 00:02:00+01:00                1.01  18.14417             70   \n",
       "2023-01-01 00:03:00+01:00                1.01  18.14417             70   \n",
       "2023-01-01 00:04:00+01:00                1.01  18.14417             70   \n",
       "\n",
       "                           Tsink (VDG)  MW (VDG)  Total demand  hp_output_MW  \\\n",
       "2023-01-01 00:00:00+01:00          144         1             1             1   \n",
       "2023-01-01 00:01:00+01:00          144         1             1             1   \n",
       "2023-01-01 00:02:00+01:00          144         1             1             1   \n",
       "2023-01-01 00:03:00+01:00          144         1             1             1   \n",
       "2023-01-01 00:04:00+01:00          144         1             1             1   \n",
       "\n",
       "                           hp_input_MW  cop  hp_output_MWh  hp_input_MWh  \n",
       "2023-01-01 00:00:00+01:00     -0.34483  2.9        0.01667      -0.00575  \n",
       "2023-01-01 00:01:00+01:00     -0.34483  2.9        0.01667      -0.00575  \n",
       "2023-01-01 00:02:00+01:00     -0.34483  2.9        0.01667      -0.00575  \n",
       "2023-01-01 00:03:00+01:00     -0.34483  2.9        0.01667      -0.00575  \n",
       "2023-01-01 00:04:00+01:00     -0.34483  2.9        0.01667      -0.00575  "
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.hpcase.data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "72906"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.storage_case_PCM.data['cop'].isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "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",
    "    'hp_input_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": 70,
   "metadata": {},
   "outputs": [
    {
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      "\n",
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         "title": {
          "font": {
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       "                           storage_level_MWh  to_storage_MW  from_storage_MW  \\\n",
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   "source": [
    "vis_data['cycles'].resample('1M').sum().iplot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1222.5108, 1220.6174099999998)"
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     "execution_count": 76,
     "metadata": {},
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   ],
   "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": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['DAM', 'POS', 'NEG', 'ForeNeg', 'ForePos', 'Gas prices (€/MWh)',\n",
       "       'CO2 prices (€/ton)', 'CO2 prices (€/MWh)', 'DAM_avg', 'Tsource (VDG)',\n",
       "       'Tsink (VDG)', 'MW (VDG)', 'Total demand', 'hp_output_MW',\n",
       "       'hp_input_MW', 'cop', 'tsource_vdg', 'to_storage_vdg_MW',\n",
       "       'from_storage_vdg_MW', 'to_storage_MW', 'from_storage_MW',\n",
       "       'storage_level_MWh', 'hp_output_MWh', 'hp_input_MWh',\n",
       "       'to_storage_vdg_MWh', 'from_storage_vdg_MWh', 'to_storage_MWh',\n",
       "       'from_storage_MWh'],\n",
       "      dtype='object')"
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     "execution_count": 77,
     "metadata": {},
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   "execution_count": 78,
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     "execution_count": 78,
     "metadata": {},
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    "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)"
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  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
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      "\n",
      "'H' is deprecated and will be removed in a future version, please use 'h' instead.\n",
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     "metadata": {},
     "output_type": "display_data"
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   ],
   "source": [
    "pd.concat([hp_output, demand_and_to_storage], axis=1).resample('H').sum().iplot()"
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  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "exclude"
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   },
   "source": [
    "## Financials"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['DAM', 'POS', 'NEG', 'ForeNeg', 'ForePos', 'Gas prices (€/MWh)',\n",
       "       'CO2 prices (€/ton)', 'CO2 prices (€/MWh)', 'DAM_avg', 'Tsource (VDG)',\n",
       "       'Tsink (VDG)', 'MW (VDG)', 'Total demand', 'hp_output_MW',\n",
       "       'hp_input_MW', 'cop', 'tsource_vdg', 'to_storage_vdg_MW',\n",
       "       'from_storage_vdg_MW', 'to_storage_MW', 'from_storage_MW',\n",
       "       'storage_level_MWh', 'hp_output_MWh', 'hp_input_MWh',\n",
       "       'to_storage_vdg_MWh', 'from_storage_vdg_MWh', 'to_storage_MWh',\n",
       "       'from_storage_MWh'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.storage_case_PCM.data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "meer dan 1 miljoen t/m 10 miljoen m3 0 0.02348 0.0\n",
      "meer dan 10 miljoen m3 zakelijk 996428.7030402296 0.01261 12564.97\n",
      "50.001 t/m 10 miljoen kWh 0 0.01353 0.0\n",
      "meer dan 10 miljoen kWh zakelijk 3022199.9999999977 0.00055 1662.21\n",
      "344.83000000000004\n",
      "344.83000000000004\n",
      "-22\n",
      "-31\n",
      "{'Variable': -0.0, 'kW contract': -7531.07, 'kW max': -10717.3}\n",
      "50.001 t/m 10 miljoen kWh 0 0.01353 0.0\n",
      "meer dan 10 miljoen kWh zakelijk 3224898.9600000004 0.00055 1773.69\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\casestudy.py:369: FutureWarning:\n",
      "\n",
      "'T' is deprecated and will be removed in a future version, please use 'min' instead.\n",
      "\n",
      "C:\\Users\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\casestudy.py:372: FutureWarning:\n",
      "\n",
      "'M' is deprecated and will be removed in a future version, please use 'ME' instead.\n",
      "\n",
      "C:\\Users\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\casestudy.py:369: FutureWarning:\n",
      "\n",
      "'T' is deprecated and will be removed in a future version, please use 'min' instead.\n",
      "\n",
      "C:\\Users\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\casestudy.py:372: FutureWarning:\n",
      "\n",
      "'M' is deprecated and will be removed in a future version, please use 'ME' instead.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "600.0\n",
      "600.0\n",
      "-22\n",
      "-31\n",
      "{'Variable': -0.0, 'kW contract': -13103.98, 'kW max': -18647.96}\n"
     ]
    }
   ],
   "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",
    "    \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=2023, \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": 83,
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\financial.py:544: FutureWarning:\n",
      "\n",
      "Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n",
      "\n",
      "C:\\Users\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\financial.py:545: FutureWarning:\n",
      "\n",
      "Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n",
      "\n",
      "C:\\Users\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\financial.py:546: FutureWarning:\n",
      "\n",
      "Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n",
      "\n",
      "C:\\Users\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\financial.py:544: FutureWarning:\n",
      "\n",
      "Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n",
      "\n",
      "C:\\Users\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\financial.py:545: FutureWarning:\n",
      "\n",
      "Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n",
      "\n",
      "C:\\Users\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\financial.py:546: FutureWarning:\n",
      "\n",
      "Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n",
      "\n"
     ]
    }
   ],
   "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": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "146760\n",
      "73389\n"
     ]
    }
   ],
   "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))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-193442.08086000002\n",
      "-181242.64800000002\n"
     ]
    }
   ],
   "source": [
    "charge_times_pcm = print(sum(s.storage_case_PCM.data['hp_input_MW']))\n",
    "charge_times_hp = print(sum(s.hpcase.data['hp_input_MW']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "source": [
    "## Visualisations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\z004yn8c\\AppData\\Local\\Temp\\ipykernel_15244\\1396106630.py:1: FutureWarning:\n",
      "\n",
      "'H' is deprecated and will be removed in a future version, please use 'h' instead.\n",
      "\n",
      "C:\\Users\\z004yn8c\\AppData\\Local\\anaconda3\\Lib\\site-packages\\cufflinks\\plotlytools.py:117: FutureWarning:\n",
      "\n",
      "DatetimeIndex.format is deprecated and will be removed in a future version. Convert using index.astype(str) or index.map(formatter) instead.\n",
      "\n"
     ]
    },
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
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          "color": "rgba(70, 165, 121, 1.0)",
          "dash": "solid",
          "shape": "linear",
          "width": 1.3
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         "mode": "lines",
         "name": "Total demand",
         "text": "",
         "type": "scatter",
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        "width": 800,
        "xaxis": {
         "autorange": true,
         "gridcolor": "#E1E5ED",
         "range": [
          "2023-01-01",
          "2023-12-31 23:00"
         ],
         "showgrid": true,
         "tickfont": {
          "color": "#4D5663"
         },
         "title": {
          "font": {
           "color": "#4D5663"
          },
          "text": ""
         },
         "type": "date",
         "zerolinecolor": "#E1E5ED"
        },
        "yaxis": {
         "autorange": true,
         "gridcolor": "#E1E5ED",
         "range": [
          0,
          2
         ],
         "showgrid": true,
         "tickfont": {
          "color": "#4D5663"
         },
         "title": {
          "font": {
           "color": "#4D5663"
          },
          "text": "MW"
         },
         "type": "linear",
         "zerolinecolor": "#E1E5ED"
        }
       }
      },
      "image/png": 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    "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",
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      "C:\\Users\\z004yn8c\\AppData\\Local\\Temp\\ipykernel_15244\\1493830805.py:1: FutureWarning:\n",
      "\n",
      "'H' is deprecated and will be removed in a future version, please use 'h' instead.\n",
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        "title": {
         "font": {
          "color": "#4D5663"
         },
         "text": "Smurfit Kappa: Source and Sink temperatures"
        },
        "width": 800,
        "xaxis": {
         "autorange": true,
         "gridcolor": "#E1E5ED",
         "range": [
          -0.5,
          1.5
         ],
         "showgrid": true,
         "tickfont": {
          "color": "#4D5663"
         },
         "title": {
          "font": {
           "color": "#4D5663"
          },
          "text": ""
         },
         "type": "category",
         "zerolinecolor": "#E1E5ED"
        },
        "yaxis": {
         "autorange": true,
         "gridcolor": "#E1E5ED",
         "range": [
          65.88888888888889,
          148.11111111111111
         ],
         "showgrid": true,
         "tickfont": {
          "color": "#4D5663"
         },
         "title": {
          "font": {
           "color": "#4D5663"
          },
          "text": "Temperature in degrees C"
         },
         "type": "linear",
         "zerolinecolor": "#E1E5ED"
        }
       }
      },
      "image/png": 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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "demands_fig = s.demand[['Tsource (VDG)', 'Tsink (VDG)']].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": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['DAM', 'POS', 'NEG', 'ForeNeg', 'ForePos', 'Gas prices (€/MWh)',\n",
       "       'CO2 prices (€/ton)', 'CO2 prices (€/MWh)', 'DAM_avg', 'Tsource (VDG)',\n",
       "       'Tsink (VDG)', 'MW (VDG)', 'Total demand', 'hp_output_MW',\n",
       "       'hp_input_MW', 'cop', 'tsource_vdg', 'to_storage_vdg_MW',\n",
       "       'from_storage_vdg_MW', 'to_storage_MW', 'from_storage_MW',\n",
       "       'storage_level_MWh', 'hp_output_MWh', 'hp_input_MWh',\n",
       "       'to_storage_vdg_MWh', 'from_storage_vdg_MWh', 'to_storage_MWh',\n",
       "       'from_storage_MWh', 'nomination_MWh', 'Prod. vol.', 'Cons. vol.',\n",
       "       'Imb. vol.', 'Day-Ahead Result', 'POS Result', 'NEG Result',\n",
       "       'Imbalance Result', 'Combined Result'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.storage_case_PCM.data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "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": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2023-01-01 00:00:00+0100', tz='Europe/Amsterdam')"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.storage_case_PCM.data['tsource_vdg'].idxmin()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "# s.storage_case_PCM.data.loc['2019-01-04 07:45:00']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0,\n",
       " 0,\n",
       " 29.635,\n",
       " 0,\n",
       " 0,\n",
       " HotWaterStorage(name=PCM_TES, rated_power=1, capacity=3, temperature=144, min_storagelevel=0.0),\n",
       " Heatpump(name='Heatpump PCM', max_thermal_power=1.5, cop_curve=2.9, min_th_power=0.0))"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "case = s.storage_case_PCM\n",
    "hp_vdg = case.assets['Heatpump PCM']\n",
    "PCM = case.assets['PCM_TES']\n",
    "PCM.storage_level = 47.083 + 25\n",
    "pos = 35.650\n",
    "neg = 43.850\n",
    "dam = 68.400\n",
    "demand_vdg = 0\n",
    "tsource_vdg = 29.635\n",
    "tsink_vdg = 134.840\n",
    "\n",
    "hp_storage_opt_enginge(c, PCM, hp_vdg, pos, neg, dam, demand_vdg, tsource_vdg, tsink_vdg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "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": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "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": 96,
   "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=2.5\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "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": 98,
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "outputs": [],
   "source": [
    "date = s.baseline.data.index[0].strftime('%Y-%m-%d')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\z004yn8c\\AppData\\Local\\anaconda3\\Lib\\site-packages\\cufflinks\\plotlytools.py:117: FutureWarning:\n",
      "\n",
      "DatetimeIndex.format is deprecated and will be removed in a future version. Convert using index.astype(str) or index.map(formatter) instead.\n",
      "\n"
     ]
    },
    {
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    "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",
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     "text": [
      "C:\\Users\\z004yn8c\\AppData\\Local\\anaconda3\\Lib\\site-packages\\cufflinks\\plotlytools.py:117: FutureWarning:\n",
      "\n",
      "DatetimeIndex.format is deprecated and will be removed in a future version. Convert using index.astype(str) or index.map(formatter) instead.\n",
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   "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",
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   "metadata": {
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     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\reports.py:46: FutureWarning:\n",
      "\n",
      "DataFrame.applymap has been deprecated. Use DataFrame.map instead.\n",
      "\n"
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Heatpump only</th>\n",
       "      <th>Heatpump + Storage_PCM</th>\n",
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       "      <th>Total net volume (MWh)</th>\n",
       "      <td>-3,022</td>\n",
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       "      <th>Total exported to grid (MWh)</th>\n",
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       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total consumed from grid (MWh)</th>\n",
       "      <td>3,022</td>\n",
       "      <td>3,225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total nominated volume (MWh)</th>\n",
       "      <td>-3,022</td>\n",
       "      <td>-3,022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Absolute imbalance volume (MWh)</th>\n",
       "      <td>-</td>\n",
       "      <td>1,045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mean selling price (€/MWh)</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mean buying price (€/MWh)</th>\n",
       "      <td>96</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total day-ahead result (€)</th>\n",
       "      <td>-289,579</td>\n",
       "      <td>-289,579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total POS result (€)</th>\n",
       "      <td>-</td>\n",
       "      <td>114,467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total NEG result (€)</th>\n",
       "      <td>-</td>\n",
       "      <td>-9,137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total imbalance result (€)</th>\n",
       "      <td>-</td>\n",
       "      <td>105,330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total combined result (€)</th>\n",
       "      <td>-289,579</td>\n",
       "      <td>-184,249</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                Heatpump only Heatpump + Storage_PCM\n",
       "Total net volume (MWh)                 -3,022                 -3,225\n",
       "Total exported to grid (MWh)                -                      -\n",
       "Total consumed from grid (MWh)          3,022                  3,225\n",
       "Total nominated volume (MWh)           -3,022                 -3,022\n",
       "Absolute imbalance volume (MWh)             -                  1,045\n",
       "Mean selling price (€/MWh)                  -                      -\n",
       "Mean buying price (€/MWh)                  96                     57\n",
       "Total day-ahead result (€)           -289,579               -289,579\n",
       "Total POS result (€)                        -                114,467\n",
       "Total NEG result (€)                        -                 -9,137\n",
       "Total imbalance result (€)                  -                105,330\n",
       "Total combined result (€)            -289,579               -184,249"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "report = ComparisonReport(\n",
    "    cases=s.optcases, \n",
    "    kind='electr_market_results',\n",
    ")\n",
    "report.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\reports.py:46: FutureWarning:\n",
      "\n",
      "DataFrame.applymap has been deprecated. Use DataFrame.map instead.\n",
      "\n"
     ]
    },
    {
     "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>Heatpump only</th>\n",
       "      <th>Heatpump + Storage_PCM</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Gasboiler OPEX (€)</th>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gas consumption costs (€)</th>\n",
       "      <td>393,966</td>\n",
       "      <td>393,966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CO2 emission costs (€)</th>\n",
       "      <td>140,949</td>\n",
       "      <td>140,949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gas taxes (€)</th>\n",
       "      <td>33,689</td>\n",
       "      <td>33,689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Heatpump VDG OPEX (€)</th>\n",
       "      <td>-46,080</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Result on electricity market (€)</th>\n",
       "      <td>-289,579</td>\n",
       "      <td>-184,249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Electricity taxes (€)</th>\n",
       "      <td>-2,871</td>\n",
       "      <td>-3,064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Grid transport costs (€)</th>\n",
       "      <td>-18,248</td>\n",
       "      <td>-31,752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Heatpump PCM OPEX (€)</th>\n",
       "      <td>-</td>\n",
       "      <td>-69,120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PCM_TES OPEX (€)</th>\n",
       "      <td>-</td>\n",
       "      <td>-9,000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EBITDA (€)</th>\n",
       "      <td>211,826</td>\n",
       "      <td>271,420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Depreciation (€)</th>\n",
       "      <td>-46,080</td>\n",
       "      <td>-81,120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EBITDA + depr (€)</th>\n",
       "      <td>165,746</td>\n",
       "      <td>190,300</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 Heatpump only Heatpump + Storage_PCM\n",
       "Gasboiler OPEX (€)                           -                      -\n",
       "Gas consumption costs (€)              393,966                393,966\n",
       "CO2 emission costs (€)                 140,949                140,949\n",
       "Gas taxes (€)                           33,689                 33,689\n",
       "Heatpump VDG OPEX (€)                  -46,080                      -\n",
       "Result on electricity market (€)      -289,579               -184,249\n",
       "Electricity taxes (€)                   -2,871                 -3,064\n",
       "Grid transport costs (€)               -18,248                -31,752\n",
       "Heatpump PCM OPEX (€)                        -                -69,120\n",
       "PCM_TES OPEX (€)                             -                 -9,000\n",
       "EBITDA (€)                             211,826                271,420\n",
       "Depreciation (€)                       -46,080                -81,120\n",
       "EBITDA + depr (€)                      165,746                190,300"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "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": 103,
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\z004yn8c\\OneDrive - Siemens AG\\Documents\\GitHub\\Mooi-Kickstart\\pyrecoy\\pyrecoy\\pyrecoy2\\styling.py:42: FutureWarning:\n",
      "\n",
      "DataFrame.applymap has been deprecated. Use DataFrame.map instead.\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year 0</th>\n",
       "      <th>Year 1</th>\n",
       "      <th>Year 2</th>\n",
       "      <th>Year 3</th>\n",
       "      <th>Year 4</th>\n",
       "      <th>Year 5</th>\n",
       "      <th>Year 6</th>\n",
       "      <th>Year 7</th>\n",
       "      <th>Year 8</th>\n",
       "      <th>Year 9</th>\n",
       "      <th>Year 10</th>\n",
       "      <th>Year 11</th>\n",
       "      <th>Year 12</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CAPEX (€)</th>\n",
       "      <td>-1,157,760</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Regular Earnings (€)</th>\n",
       "      <td></td>\n",
       "      <td>211,827</td>\n",
       "      <td>211,827</td>\n",
       "      <td>211,827</td>\n",
       "      <td>211,827</td>\n",
       "      <td>211,827</td>\n",
       "      <td>211,827</td>\n",
       "      <td>211,827</td>\n",
       "      <td>211,827</td>\n",
       "      <td>211,827</td>\n",
       "      <td>211,827</td>\n",
       "      <td>211,827</td>\n",
       "      <td>211,827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Irregular Cashflows (€)</th>\n",
       "      <td></td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EBITDA (€)</th>\n",
       "      <td></td>\n",
       "      <td>211,827</td>\n",
       "      <td>211,827</td>\n",
       "      <td>211,827</td>\n",
       "      <td>211,827</td>\n",
       "      <td>211,827</td>\n",
       "      <td>211,827</td>\n",
       "      <td>211,827</td>\n",
       "      <td>211,827</td>\n",
       "      <td>211,827</td>\n",
       "      <td>211,827</td>\n",
       "      <td>211,827</td>\n",
       "      <td>211,827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Depreciations (€) -/-</th>\n",
       "      <td></td>\n",
       "      <td>-46,080</td>\n",
       "      <td>-46,080</td>\n",
       "      <td>-46,080</td>\n",
       "      <td>-46,080</td>\n",
       "      <td>-46,080</td>\n",
       "      <td>-46,080</td>\n",
       "      <td>-46,080</td>\n",
       "      <td>-46,080</td>\n",
       "      <td>-46,080</td>\n",
       "      <td>-46,080</td>\n",
       "      <td>-46,080</td>\n",
       "      <td>-46,080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EBIT (€)</th>\n",
       "      <td></td>\n",
       "      <td>165,747</td>\n",
       "      <td>165,747</td>\n",
       "      <td>165,747</td>\n",
       "      <td>165,747</td>\n",
       "      <td>165,747</td>\n",
       "      <td>165,747</td>\n",
       "      <td>165,747</td>\n",
       "      <td>165,747</td>\n",
       "      <td>165,747</td>\n",
       "      <td>165,747</td>\n",
       "      <td>165,747</td>\n",
       "      <td>165,747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Income tax (Vpb.) (€)</th>\n",
       "      <td></td>\n",
       "      <td>-24,862</td>\n",
       "      <td>-24,862</td>\n",
       "      <td>-24,862</td>\n",
       "      <td>-24,862</td>\n",
       "      <td>-24,862</td>\n",
       "      <td>-24,862</td>\n",
       "      <td>-24,862</td>\n",
       "      <td>-24,862</td>\n",
       "      <td>-24,862</td>\n",
       "      <td>-24,862</td>\n",
       "      <td>-24,862</td>\n",
       "      <td>-24,862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NOPLAT (€)</th>\n",
       "      <td></td>\n",
       "      <td>140,885</td>\n",
       "      <td>140,885</td>\n",
       "      <td>140,885</td>\n",
       "      <td>140,885</td>\n",
       "      <td>140,885</td>\n",
       "      <td>140,885</td>\n",
       "      <td>140,885</td>\n",
       "      <td>140,885</td>\n",
       "      <td>140,885</td>\n",
       "      <td>140,885</td>\n",
       "      <td>140,885</td>\n",
       "      <td>140,885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Depreciations (€) +/+</th>\n",
       "      <td></td>\n",
       "      <td>46,080</td>\n",
       "      <td>46,080</td>\n",
       "      <td>46,080</td>\n",
       "      <td>46,080</td>\n",
       "      <td>46,080</td>\n",
       "      <td>46,080</td>\n",
       "      <td>46,080</td>\n",
       "      <td>46,080</td>\n",
       "      <td>46,080</td>\n",
       "      <td>46,080</td>\n",
       "      <td>46,080</td>\n",
       "      <td>46,080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Free Cash Flow (€)</th>\n",
       "      <td>-1,157,760</td>\n",
       "      <td>186,965</td>\n",
       "      <td>186,965</td>\n",
       "      <td>186,965</td>\n",
       "      <td>186,965</td>\n",
       "      <td>186,965</td>\n",
       "      <td>186,965</td>\n",
       "      <td>186,965</td>\n",
       "      <td>186,965</td>\n",
       "      <td>186,965</td>\n",
       "      <td>186,965</td>\n",
       "      <td>186,965</td>\n",
       "      <td>186,965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Simple Payback Period</th>\n",
       "      <td>6.192400442044605 years</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IRR (%)</th>\n",
       "      <td>12%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WACC (%)</th>\n",
       "      <td>10%</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NPV of explicit period (€)</th>\n",
       "      <td>105,600</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Discounted residual value (€)</th>\n",
       "      <td>192,708</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NPV (€)</th>\n",
       "      <td>105,600</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                Year 0   Year 1   Year 2  \\\n",
       "CAPEX (€)                                   -1,157,760                     \n",
       "Regular Earnings (€)                                    211,827  211,827   \n",
       "Irregular Cashflows (€)                                       -        -   \n",
       "EBITDA (€)                                              211,827  211,827   \n",
       "Depreciations (€) -/-                                   -46,080  -46,080   \n",
       "EBIT (€)                                                165,747  165,747   \n",
       "Income tax (Vpb.) (€)                                   -24,862  -24,862   \n",
       "NOPLAT (€)                                              140,885  140,885   \n",
       "Depreciations (€) +/+                                    46,080   46,080   \n",
       "Free Cash Flow (€)                          -1,157,760  186,965  186,965   \n",
       "Simple Payback Period          6.192400442044605 years                     \n",
       "IRR (%)                                            12%                     \n",
       "WACC (%)                                           10%                     \n",
       "NPV of explicit period (€)                     105,600                     \n",
       "Discounted residual value (€)                  192,708                     \n",
       "NPV (€)                                        105,600                     \n",
       "\n",
       "                                Year 3   Year 4   Year 5   Year 6   Year 7  \\\n",
       "CAPEX (€)                                                                    \n",
       "Regular Earnings (€)           211,827  211,827  211,827  211,827  211,827   \n",
       "Irregular Cashflows (€)              -        -        -        -        -   \n",
       "EBITDA (€)                     211,827  211,827  211,827  211,827  211,827   \n",
       "Depreciations (€) -/-          -46,080  -46,080  -46,080  -46,080  -46,080   \n",
       "EBIT (€)                       165,747  165,747  165,747  165,747  165,747   \n",
       "Income tax (Vpb.) (€)          -24,862  -24,862  -24,862  -24,862  -24,862   \n",
       "NOPLAT (€)                     140,885  140,885  140,885  140,885  140,885   \n",
       "Depreciations (€) +/+           46,080   46,080   46,080   46,080   46,080   \n",
       "Free Cash Flow (€)             186,965  186,965  186,965  186,965  186,965   \n",
       "Simple Payback Period                                                        \n",
       "IRR (%)                                                                      \n",
       "WACC (%)                                                                     \n",
       "NPV of explicit period (€)                                                   \n",
       "Discounted residual value (€)                                                \n",
       "NPV (€)                                                                      \n",
       "\n",
       "                                Year 8   Year 9  Year 10  Year 11  Year 12  \n",
       "CAPEX (€)                                                                   \n",
       "Regular Earnings (€)           211,827  211,827  211,827  211,827  211,827  \n",
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       "EBITDA (€)                     211,827  211,827  211,827  211,827  211,827  \n",
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       "EBIT (€)                       165,747  165,747  165,747  165,747  165,747  \n",
       "Income tax (Vpb.) (€)          -24,862  -24,862  -24,862  -24,862  -24,862  \n",
       "NOPLAT (€)                     140,885  140,885  140,885  140,885  140,885  \n",
       "Depreciations (€) +/+           46,080   46,080   46,080   46,080   46,080  \n",
       "Free Cash Flow (€)             186,965  186,965  186,965  186,965  186,965  \n",
       "Simple Payback Period                                                       \n",
       "IRR (%)                                                                     \n",
       "WACC (%)                                                                    \n",
       "NPV of explicit period (€)                                                  \n",
       "Discounted residual value (€)                                               \n",
       "NPV (€)                                                                     "
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       "                                                Year 0   Year 1   Year 2  \\\n",
       "CAPEX (€)                                   -2,036,640                     \n",
       "Regular Earnings (€)                                    271,420  271,420   \n",
       "Irregular Cashflows (€)                                       -        -   \n",
       "EBITDA (€)                                              271,420  271,420   \n",
       "Depreciations (€) -/-                                   -81,120  -81,120   \n",
       "EBIT (€)                                                190,300  190,300   \n",
       "Income tax (Vpb.) (€)                                   -28,545  -28,545   \n",
       "NOPLAT (€)                                              161,755  161,755   \n",
       "Depreciations (€) +/+                                    81,120   81,120   \n",
       "Free Cash Flow (€)                          -2,036,640  242,875  242,875   \n",
       "Simple Payback Period          8.385534435261583 years                     \n",
       "IRR (%)                                             6%                     \n",
       "WACC (%)                                           10%                     \n",
       "NPV of explicit period (€)                    -347,056                     \n",
       "Discounted residual value (€)                  338,768                     \n",
       "NPV (€)                                       -347,056                     \n",
       "\n",
       "                                Year 3   Year 4   Year 5   Year 6   Year 7  \\\n",
       "CAPEX (€)                                                                    \n",
       "Regular Earnings (€)           271,420  271,420  271,420  271,420  271,420   \n",
       "Irregular Cashflows (€)              -        -        -        -        -   \n",
       "EBITDA (€)                     271,420  271,420  271,420  271,420  271,420   \n",
       "Depreciations (€) -/-          -81,120  -81,120  -81,120  -81,120  -81,120   \n",
       "EBIT (€)                       190,300  190,300  190,300  190,300  190,300   \n",
       "Income tax (Vpb.) (€)          -28,545  -28,545  -28,545  -28,545  -28,545   \n",
       "NOPLAT (€)                     161,755  161,755  161,755  161,755  161,755   \n",
       "Depreciations (€) +/+           81,120   81,120   81,120   81,120   81,120   \n",
       "Free Cash Flow (€)             242,875  242,875  242,875  242,875  242,875   \n",
       "Simple Payback Period                                                        \n",
       "IRR (%)                                                                      \n",
       "WACC (%)                                                                     \n",
       "NPV of explicit period (€)                                                   \n",
       "Discounted residual value (€)                                                \n",
       "NPV (€)                                                                      \n",
       "\n",
       "                                Year 8   Year 9  Year 10  Year 11  Year 12  \n",
       "CAPEX (€)                                                                   \n",
       "Regular Earnings (€)           271,420  271,420  271,420  271,420  271,420  \n",
       "Irregular Cashflows (€)              -        -        -        -        -  \n",
       "EBITDA (€)                     271,420  271,420  271,420  271,420  271,420  \n",
       "Depreciations (€) -/-          -81,120  -81,120  -81,120  -81,120  -81,120  \n",
       "EBIT (€)                       190,300  190,300  190,300  190,300  190,300  \n",
       "Income tax (Vpb.) (€)          -28,545  -28,545  -28,545  -28,545  -28,545  \n",
       "NOPLAT (€)                     161,755  161,755  161,755  161,755  161,755  \n",
       "Depreciations (€) +/+           81,120   81,120   81,120   81,120   81,120  \n",
       "Free Cash Flow (€)             242,875  242,875  242,875  242,875  242,875  \n",
       "Simple Payback Period                                                       \n",
       "IRR (%)                                                                     \n",
       "WACC (%)                                                                    \n",
       "NPV of explicit period (€)                                                  \n",
       "Discounted residual value (€)                                               \n",
       "NPV (€)                                                                     "
      ]
     },
     "execution_count": 104,
     "metadata": {},
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   "source": [
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VZnZCAQpQgAIUoAAFKEABClCAAhSgAAUoQAEKUIACagQYWqtR4jkUoAAFKEABClCAAhSgAAUoQAEKUIACFKAABShgFQGG1lZhZicUoAAFKEABClCAAhSgAAUoQAEKUIACFKAABSigRoChtRolnkMBClCAAhSgAAUoQAEKUIACFKAABShAAQpQgAJWEWBobRVmdkIBClCAAhSgAAUoQAEKUIACFKAABShAAQpQgAJqBBhaq1HiORSgAAUoQAEKUIACFKAABShAAQpQgAIUoAAFKGAVAYbWVmFmJxSgAAUoQAEKUIACFKAABShAAQpQgAIUoAAFKKBGgKG1GiWeQwEKUIACFKAABShAAQpQgAIUoAAFKEABClCAAlYRYGhtFWZ2QgEKUIACFKAABShAAQpQgAIUoAAFKEABClCAAmoEGFqrUeI5FKAABShAAQpQgAIUoAAFKEABClCAAhSgAAUoYBUBhtZWYWYnFKAABShAAQpQgAIUoAAFKEABClCAAhSgAAUooEaAobUaJZ5DAQpQgAIUoAAFKEABClCAAhSgAAUoQAEKUIACVhFgaG0VZnZCAQpQgAIUoAAFKEABClCAAhSgAAUoQAEKUIACagQYWqtR4jkUoAAFKEABClCAAhSgAAUoQAEKUIACFKAABShgFQGG1lZhZicUoAAFKEABClCAAhSgAAUoQAEKUIACFKAABSigRoChtRolnkMBClCAAhSgAAUoQAEKUIACFKAABShAAQpQgAJWEWBobRVmdkIBClCAAhSgAAUoQAEKUIACFKAABShAAQpQgAJqBBhaq1HiORSgAAUoQAEKUIACFKAABShAAQpQgAIUoAAFKGAVAYbWVmFmJxSgAAUoQAEKUIACFKAABShAAQpQgAIUoAAFKKBGgKG1GiWeQwEKUIACFKAABShAAQpQgAIUoAAFKEABClCAAlYRYGhtFWZ2QgEKUIACFKAABShAAQpQgAIUoAAFKEABClCAAmoEGFqrUeI5FKAABShAAQpQgAIUoAAFKEABClCAAhSgAAUoYBUBhtZWYWYnFKAABShAAQpQgAIUoAAFKEABClCAAhSgAAUooEaAobUaJZ5DAQpQgAIUoAAFKEABClCAAhSgAAUoQAEKUIACVhFgaG0VZnZCAQpQgAIUoAAFKEABClCAAhSgAAUoQAEKUIACagQYWqtR4jkUoAAFKEABClCAAhSgAAUoQAEKUIACFKAABShgFQGG1lZhZicUoAAFKEABClCAAhSgAAUoQAEKUIACFKAABSigRoChtRolnkMBClCAAhSgAAUoQAEKUIACFKAABShAAQpQgAJWEWBobRVmdkIBClCAAhSgAAUoQAEKUIACFKAABShAAQpQgAJqBBhaq1HiORSgAAUoQAEKUIACFKAABShAAQpQgAIUoAAFKGAVAYbWVmFmJxSgAAUoQAEKUIACFKAABShAAQpQgAIUoAAFKKBGgKG1GiWeQwEKUIACFKAABShAAQpQgAIUoAAFKEABClCAAlYRYGhtFWZ2QgEKUIACFKAABShAAQpQgAIUoAAFKEABClCAAmoEGFqrUeI5FKAABShAAQpQgAIUoAAFKEABClCAAhSgAAUoYBUBhtZWYWYnFKAABShAAQpQgAIUoAAFKEABClCAAhSgAAUooEaAobUaJZ5DAQpQgAIUoAAFKEABClCAAhSgAAUoQAEKUIACVhFgaG0VZnZCAQpQgAIUoAAFKEABClCAAhSgAAUoQAEKUIACagQYWqtR4jkUoAAFKEABClCAAhSgAAUoQAEKUIACFKAABShgFQGG1lZhZicUoAAFKEABClCAAhSgAAUoQAEKUIACFKAABSigRoChtRolnkMBCugEXgYEwjOuK6JHj04VCji9wOs3gYgT2xUxfuDPg9M/DARAwLtguLvEQMyYMahBAQroCQR9+IQvn78gtrsLXSjg9AIfPnzCx89fEJc/D07/LBCAAhSggCkBhtamhPh9ClAghABDaz4QFPguwNCaTwMFvgswtObTQAHjAgyt+WRQ4LsAQ2s+DRSgAAUooFaAobVaKZ5HAQpIAYbWfBAowNCazwAFjAkwtOZzQQGG1nwGKGBKgKG1KSF+nwIUoAAFFAGG1nwWKEABswQYWpvFxZMdXIArrR18gnl7ZgkwtDaLiyc7kQBXWjvRZPNWTQowtDZJxBMoQAEKUOB/Agyt+ShQgAJmCTC0NouLJzu4AENrB59g3p5ZAgytzeLiyU4kwNDaiSabt2pSgKG1SSKeQAEKUIACDK1t/wzcuf8QQR8+4I80qW0/GI6AAioFGFqrhOJpTiHA0Nopppk3qVKAobVKKJ7mdAIMrZ1uynnD4QgwtObjQQEKUIACagW40lqtVBScV6BqQ7x8HYBLu9dGQetskgJRI8DQOmpc2ap9CjC0ts9546ijRoChddS4slX7F2Bobf9zyDuwnABDa8tZsiUKUIACji7A0NpGM3zwxGnU8Osie988fzKyZfzDRiNhtxQwT4ChtXlePNuxBRhaO/b88u7ME2BobZ4Xz3YeAYbWzjPXvFPTAgytTRvxDApQgAIU+CbA0NpGT0LTbv0RGBiEyzduo45PWXRr1chGI2G3FDBPgKG1eV4827EFGFo79vzy7swTYGhtnhfPdh4BhtbOM9e8U9MCDK1NG/EMClCAAhRgaG2zZ+DZi5fIXLIaFk8chj1HTuD46fPYtWyWzcYTmY4PnDiFl68CEPD2Pd68e4umtarCzdUlMk3yWo0LMLTW+ARxeFYVYGhtVW52pnEBhtYanyAOz2YCDK1tRs+ONSjA0FqDk8IhUYACOoGbt+9i3OTZ6NimKX79JaVVZIKCgjF87BTZV/dOreHm5qqqX3HdhOlzUM2nXJSN1ZTHpOlzce3GHQzs3QnxvbxUjduck7jS2hytcM71f/Yc/k//RbaM6Uy2OGbmAqzcvAPH1i/BoX/OoHrLzji9dQW8Eyc0ea2WTqjbrjv2HD4RYkgb5k5CzszptTRMjsXCAgytLQzK5uxagKG1XU8fB29hAYbWFgZlcw4jwNDaYaaSN2IBAYbWFkBkExRwEIE167dixdqNIe6mY5vmyJ0ji83u0FRIGxUDEw6P/P3RtmVjXfNKkH3txi35tYQJEoQKhsVYV63fjPYtmyAoOAh9B49FgvieIYJvcc7QUZOQInlS+fWtO/bi3MXLunOUfjJn+ANVfMrIvsQ1M+cuRvfOreUiVVMhvgiuk3l76663pBFDawtpVmjUBifPX8apLcuR9MdE4bYqVln7+dZAS98a8rxf85dHn/bN0aB6RQuNJuqbqdPmL9y4ew/rZk9EsiSJZYcZildG6wa14OdbM+oHwB5sJsDQ2mb07FiDAgytNTgpHJLNBBha24yeHWtcgKG1xieIw7OqAENrq3KzMwpoUiCslcUvX73ChKlz0b5V4yhZtatFDHHPw8dMQfPG9XSrpcXXRACdNk0qXZAtvrZ15z7UrVFZdxsi7BaHCJuVdt4HBqN+nWq64F8EyvcfPoK7m7sMqh/5P9EF0mJltBJqZ82cXteXaFcJtsX5pkLrqJw3htYWeGp3Hz6Oeu16IG7s2GjhWx2dm9UPs9VNu/ajbd9hOLt9JTzixpXnNe8+EO8DA7Fk4nCj14nvxXZ3t8BILdOEWGF99eYdrJ09AT8lTaJrtFHnPogWLTrmjh5gmY7YiiYFGFprclo4KBsJMLS2ETy71aQAQ2tNTgsHpQEBhtYamAQOQTMCDK01MxUcCAVsJnD85FksWrbaZEkJEbgePnZSjtPdzQ09u7bVBbuGq7TDWqGtBLBu7q44e+6SbEs5V1lV/WfubNi0dZdczdzYtwbmLFweojyIfl/6K57FfYybPFO2abgSOryx68OLNrZs3x1idbSxldeGk2VYGkQJrYsWyoezFy/L1dcicBYrsZMn9caNm3dkH2JFtn5ILvq/cPEKHjx6rHuzQH/ltKGRGEe+PDlCrAoXXxPX5MqRzeKr5BlaW+DHtFitZsiQNjWS/pgYq7fsxIlNy0K06tu+J94FBsqv3b73ECUK5MHoPl1056zZtgutew3FrUNb4G5Qu+b1mzeo2Lg9hv7VDvlzZrXAaCPXRO/Rk7Fl9wEZWP+czDtEY1MXLsf0xStwfsfqyHXCqzUtwNBa09PDwVlZgKG1lcHZnaYFGFpreno4OBsKMLS2IT671pwAQ2vNTQkH5AQCt+89wJPnL6x+p6l/ToEfEyYI1a8IOMWhXw7D8CTDlcXimucvXoW5WvjmrTsoXaJIqL6UwFkJqvUDc1H6QpTO0F9lbFgeRFy/58ARXcB+/tIVGaC/ePkaM+Ys0gXp+kGzYRAt/l8cxsqe6K+WFufoB+Hi/w3DeuUG9UuDiBrY+iu2t+7YIwPkR4/8kSyZt/y3fkkQ/VBa/HemDH/g6D+nZG3sZN5JZH3tsqWKyfEarsRWVoH71q4a4n7UBO0ReQAZWkdETe+addv3wK/nYBzfuBRfv35Fnop18ffUUSiUO7s8a8LcJZg4bym6tWgIT4948IgbBzkypUfC+J66Vl6/eYt0RXwwf+xglCqUV/d1scK6avPOOHflGlKmSIqj6xZHcrSRuzwwKFhuIDm8RwdULVs8VGMnzlyET9N2MrRP4f1j5Drj1ZoVYGit2anhwGwgwNDaBujsUrMCDK01OzUcmI0FGFrbeALYvaYEGFprajo4GCcR6Dp4LBav3WT1ux3ZsyN8q1YI1a9hDeSwVjLrX6gfNt+4dS9EYBzejemXulDCXVF6Q4Suov6zYekL/dBaCXD16z0rfRkG7/p1oPcdOBYi6A5vfIYrlJXSKUpoHNa1hob6obW4ZsbcRUiQIL5ccW1Yx1oJmJs2qIPZC5aibs3KEGMWR6aM6UKVD9E3Cmt8Yn5OnDwd7hsREXkAGVpHRE3vmj8r+6JAjqwY2auT/KrYVNHL0wMzh/fF46f/Il9lX/Rp3xKNa1YKt6fKzTrglxTJMKZvV3meCIir+3XG/Uf+WD1jLKq37IKGNX3QsYmvrp1lomj9pu26/3d3dcWSScZLjETyNuXli9duxqDxM3Bt/wajzQV/+IhUeUtj+rA+8CkZ+h0uS4yBbdhegKG17eeAI9COAENr7cwFR2J7AYbWtp8DjkCbAgyttTkvHJVtBBha28advTq3gL2stDYsG2K46li/BIeaoFvMumForR+6qg2tjQXI+uU/lKdLf3z630+bJnWI8h/6T6NhaG14zzUqVwi1wWFYdbCVsh+Gq6UNDZSAvWql8th78LAMts9fuipDZ7FCW79cieHKc4bWdvZniXf2ojizbSWSJPr2kQdl5fWVvevw17DxuHPvEXYsnWHyrmYsXilXZDeq7oP4Xp7YsucAzl+5gQ3zJuL31Kmwcec+tO07HPtXzZNlOeb+vRa9Rk1C5nRp4ebmgv8+f8bJc5dwcPV8/JryJ5P9ReQEUQalUJ4c6NuhRZiXl63fCtky/YHBXdpEpAteYwcCDK3tYJI4RKsJMLS2GjU7sgMBhtZ2MEkcok0EGFrbhJ2dalSAobVGJ4bDooAVBcKqaR3eaurw6mCHV24kKldaJ/P2DhUoGzIqIa+x1dpKqC7+LTZTVA5TpTaM1cE2FmTrt6dfHkQ5N1PGP+Du6qbbyFFsgpkiWVKZSSrjYWhtxR+MqOhq37GTKJwnR4imfy/sgzzZMmL7/iPYtniaDJZNHaJEyJa9h3Dp2g2cv3Idt+49xMLxQ5Ej0x+6S8Uq7pgxYuDPHJkxdNJsdGvVKMTK6wzFK+OvVk3gW6W8qe7M/v7pC1dQrmFrHF2/BCmTh6xlrd+YqHl9+vxlbFk41ew+eIF9CDC0to954iitI8DQ2jrO7MU+BBha28c8cZTWF2BobX1z9qhdAYbW2p0bjowC1hJQglzRn9gcUJTtEIdhaK2/WaN+bWlRHkQcSo1oc0Jr/RBbbFQYXnmQX39JKVdq69e03rZzL35NnSpUTWsxniUr1qJMicI4cfIC77GRAAAgAElEQVSsPEdcbyq0DiuAFiVM0qZJpSu3oV/j27A0iOjbnNBanK+sBFdqfSvjvHbjlm6jSnGe2tCaGzFa66fHAv2IFdBiJXT9ahUwokdHC7T4rQnxkY58VRrI/x7evQMaVK8You0mXfvBzdUFkwf1tFifSkPt+w3H039fyHrd4R3rd+xFyx6DcOfINri6xLL4ONig7QUYWtt+DjgC7QgwtNbOXHAkthdgaG37OeAItCnA0Fqb88JR2UaAobVt3NkrBbQooF/iQ4xPv7yGfogqvpciuTeCgj7KDRGVDRQDg4LkbYVXfiO8PgwDWdGWsa/pl/rQH6NhKY98eXLIkDmsrxubg7DCZsP7V/oVbYgV0e1bNUZ8Ly9dk+aG1sJl07Zduo0kRUOGAb0xD2PlQUTfxsZkiWeONa3/p6j/UOk/hMrErVi70eQPgzIhdx/6Y9Wm7WhWtyo84sa1xDzp2hg5dR7S/prSaM3oWUtXY9bSVXIjRP3jzMUruHDtJh48eoL7/v7Ilj4dWtSrrnpcYhV4llLVMW1ob5Qpkj/c6x49eYYc5Wphw9xJyJk5veo+eKL9CDC0tp+54kijXoChddQbswf7EWBobT9zxZFaV4ChtXW92Zu2BRhaa3t+ODoKOJqAYXkQLd6fqXIg+mOOqg0PI+NibOV3ZNrTv5ahtcFHEPTfqRBQhnVzwvvYgaUmJaLtnLtyDaXr+eH01hXwTpxQ14woVxIrVgykTJEMP0SPjmOnz2NU786oV7mcqq5EGD55/jKc27FK1fki4PbzrWFWMK6qYZ6kCQGG1pqYBg5CIwIMrTUyERyGJgQYWmtiGjgIDQowtNbgpHBINhNgaG0zenZMAacUsIfQOqxyKcYmLKrKcET04RDjuXbjjlwBb5inRrRNhtZ6AuEtoRenGb5jEF7xd0tMSGTbSJ2/LMb06YJKpYrKprbtO4xGnfvgyt718Iz3bdX33OXr0GvkRMwe2R/lihUM1eXUhcsxbtYivAsM1H2vS4sG6Nz8W2kSU0ezvwbgy5cvmDNqgKlT+X07FGBobYeTxiFHmQBD6yijZcN2KMDQ2g4njUO2igBDa6swsxM7EWBobScTxWFSgAIU0ICA06+0FvVqho6aBKUWjpgTpQ6NsYLphvVtvnz5qoFp/D6EWq27IVWKpBjWvYP8ol/PgQgM+ogF4waHGGfPEROwYNUG/D1lFArkyia/d+TUWfQYPgEvXwdgQMdWSPPLz/D0iAuPuHEQL04c1fc5c8kqTF30N85uU7cyW3XDJk588+6dWeO0VL/O1k7A2yDEi+2CaNGjO9uta/5+o0f/ii9foml+nI40wDfvghDb3UV+ioUHBZxd4G3gB7jF+gExYsRwdgrePwVCCAR//ISvn7/CzY37vdjq0eBrJFvJh+7348dP+PT5K2Lz50E7k8KRWF0genT+zmZ1dHZolwJOH1ob7tQpVl6LXTqLFsyLMiWLYPjYKShbqphuV1LD0PplwHtNTfz0xcuxbe9BrJszGe+DgpC/Ul0M/qs9yhUtFGqcLf7qh0P/nA7x9TKFC6B3h5bwjBcvwvd1/vI11G7TBTuXzUXSHxNFuB1zLjx94TLa9xuC0X26I3fWjCEuPXf5Gs5euiLvyTNeHHh4xJO1xsV/e3l44O7DR3jw+AnuP/JHiYJ5kThBfHO6drpzP3/5CvGXLP+a1d7Ux4zxAz7991l7A3PgEYk3LqNFi4Zo/IFw4FnmrakV4M+DWime52wCX78CX/EV0fmXhc2mnq+RbEYfqmP+PGhnLjgS2wnE94htu87ZMwXsSICh9cmz2LJ9N7p3ag03N1c5dUrNmw5+TTB+2hxkzvAHqviUkd8ztpOoluZbrJau2ryTLAey69AxdB08Bhd3rUVsd7dQwxTlP85fua77epzY7sj0+28WuR3v7EXlpo2TBvYw2rdFOvlfI6Lmdt8xU5AogZdcaX1ozQJd82/fv0ehao3g/+y5qi6rlyuJiQO7qzrXWU9ieRBnnXnetzEBlgfhc0GB7wIsD8KngQLGBVgehE8GBb4LsDwInwYKUIACFFAr4PShtQihZ85djO6dW+uKhuvv3GlvNa2DP3xEqrylsXD8EMxbvg4e8eJi2tDeap8Hi52348ARtOo5FMm9E2PhhKH4KWkSi7WtNCTutVWvIdi69yAGdW6NKmWL408fX7RrUget69eSp7XpMxQHjp/CkXWLEMfdXTeGp89fyDIoAW/e4cvXL/Lrt+49RLchY7Ft8TRkTpfW4uN1lAYZWjvKTPI+LCHA0NoSimzDUQQYWjvKTPI+LC3A0NrSomzPngUYWtvz7HHsFKAABawr4PShtVK3OmECL7Rt2RhKeRDf2lVlSRDDjRdFiC0Oca5Wj3INW+O3VD/j7w3bZHhdosCfNhnqzbv34duhJ14HvMW8MYOQJ1smi46jabf+EGVBZgzvh5yZ08u2569cj4Hjp+PIusU4f+UaGnTsjcUTh6FYvtyq+q7foRdeBQRg47zJqs53xpMYWjvjrPOewxJgaM1ngwLfBRha82mggHEBhtZ8MijwXYChNZ8GClCAAhRQK+D0obWAUoLq5y9eSLcalSvoyoGI/xcrr1es3Si/lzZN6hClRNRCW/O8geNnYNqi5bJUxrX9G6zZdai+RHmOFn8NxN6j/2BY9/ZoWN1H9XhE+ZIXrwLwKuANkiRKiCSJEuiuHTRhBhat3oTti6ch1U/JQ7RZvHYzxPf0wMVrN2VYPWlQD9V93n3ojz996mLGsL6oWLKw6uuc6USG1s4027xXUwIMrU0J8fvOJMDQ2plmm/dqjgBDa3O0eK6jCzC0dvQZ5v1RgAIUsJwAQ2vLWWqmJVGaQ6wwrle5HEb17qyJcY2YOhfj5yyGb5XyGNmrE56/fI0TZy/gwtUbeP7yFV4GvJHh9MtXAXgZEIB/X7wKNe6qZYvDz7cmTp6/jO7DxmHFtNEokCtbqPNOXbiC8g1byxrXB1bNh2e8uGYZDBg3HRt37cOhNQvh6sJd3g3xGFqb9TjxZAcXYGjt4BPM2zNLgKG1WVw82YkEGFo70WTzVk0KMLQ2ScQTKEABjQgYVl6wxrBEn+Mmz0THNs1l9Qe1hyh9vGr9ZrRv2US3X5/aa9WeF17lCWUxcNo0qSxamYKhtdrZsaPzAt6+Rb8xU1GvSgXkyPSHZka+de8htOk7DF8+f4aoRy0C4YzpfkPiBPGRwNMDCb084eURD/G9PJAgvhfELt/Kce+hPybOX4q79x/JLw3v3gENqlcM897a9xuO0oXzy80gzT3ECu88Fesib46s+MuvEVL/nMLcJhz6fIbWDj29vDkzBRhamwnG0x1agKG1Q08vby4SAgytI4HHSx1OgKG1w00pb4gCERYQIejhYyd11xtWNtCveiBOypcnR4hAVAl4lQYsXRnB2qG1CH6Hj5mC5o3r4ddfUupcDKtDGLtPYSWOKj5ldNUiDINvxVt8PVP63zF87BRkzvCHrtKECL7HTZ6Njm2a6vo33PNP9BFWueSwxh/hBwQAQ+vI6PFaswWu3b4rV0pn+SMt0v+W2uzrN+7ch+t37qFz8wbhXhsYFAx3N1ez21cu+OfcJfQZNRnnrlxDmSIF0K9jS/yczNvs9sTq8VMXLiM4+APKFy9kcszRo0fX/OpuhtZmPwa8wIEFGFo78OTy1swWYGhtNhkvcBIBhtZOMtG8TVUCDK1VMfEkCji0gLK3nLjJ7p1a61YGi4A0WTJvucJY/PeeA0cwsHcnxPfygrFr9M833K/OHgH1A2Jl/CJIHjpqEsqXLh4iXL556w5KlygiTxP3PmH6HFTzKSfDZtHO7v2HkSKFt27ltWhnxtxFePHiNVo08dUZP/L314XQypsEStitmCrBtpo9/kTQf+LkaYuttmZobY9PMsdsNYHt+49g+JQ5uHrrDvJmz4I2jWqjyJ85Q/Qv6m5v238YO/YfwZt373Tfu//IH4+f/qv7//BWh4swvu+YKShbtACGdGtntfuLSEe2Dq3nLFuDo2fO4+Hjp7j78DHixnFD0Xy5UShPDhTMnR1x3N0jclu8hgIREmBoHSE2XuSgAgytHXRieVuRFmBoHWlCp27g5esA9Bk1BQ1r+Og2n7dnEIbW9jx7HDsFLCNgagWzsrLYt3bVECUywvq6MioRup67eNnoPnTKtXlyZcWefYcRGBQUYs865Vo3d1ecPXdJrurOlSMbFi1bHSo4v3bjluxSf+V3WHvhKaGz6M/wGn1NJSAuW6pYiHsWQXEyb+8Q++4ZzoJhaRAl/BbniXsQbwKIdtKkToVN2/ZAcRXzsGX7bp3X7PnL4OrmglevXsvQ2XDltGjjfVAQggKDIQzc3dzQs2vbUKvCJ0ydi/atGss3GyJ7MLSOrCCvdwqB3YePY+qC5Thy6ix+TfkTEsb3lPf97n2g3PBRBKUlC+ZFqhRJdR5x48RG2l9TIVbMGNhz6ASmLPwbI3p2RP2qFXTn3Ln/EN2HTcCBE6dkKRexCn3BuMGyLa0etg6tU+UtjdxZMiJL+t8R44cf8Om//3D45BmIWubeiRPi9NYVWqXjuBxQgKG1A04qbynCAgytI0zHCx1cgKG1g09wFN7eys070Hf0FLx+8xaNa1bS/OIWNRQMrdUo8RwKWFbg7svneBb41rKNqmgtlVdCJIodeo8xUyt2wwu1wwtx1dRcThDfU4a04tAvj2G4ylh8X38cbq5u8vyECbx0q4i37dyLQvn/xNYde0OsClfGWKZkEXmNEkSLYHr1hi2oWrFsqLrTIiA2DHsNy6MkTJBAF6Dr8+uXBhFfV0LrMiWLyjrXvjWrYs2GLahSsSyGjZmiC631Q2lRplf0L8a69+BhuUL7kf8TzJy7GN07t5YBtLivM+cu6YJqY28ShBW+q3hcjJ7C0DqicrzOKQUu37gFUZv765ev8v6jx/gBebNlRp5smUx6KJtR9mjTFAm8PLF932GcvXwVOTNnQM82TWXtbLHaevmG7di7Yg6S/pjIZJu2OMGWobWyyaYIpkVArX88ff4C+So1QP/OfnITUh4UsIYAQ2trKLMPexFgaG0vM8VxWluAobW1xe23P7F/z/mrN3DywiUcPH4aD/2fonurxnBxdcHwKbNxcdda+725/42cobXdTyFvwA4F+u1Yj5UXvteOttYt9C9eETUyh/ykuujb1OphwxXA+uMNK5iOyOpt/dBVBM+Gq7T123z5KiBUvWcxLsMSGuJryvhbNK6LoaOnoGjBvOGulBbXGNtIUU2NaGPnGNahvv/wEapVqoA0qX9G38FjdaG1fsAswvx9B46ibs3KulIj5y9cgX75EEP7sOZJnKes8I7ss8bQOrKCvJ4CZggowbWo512ueEFULlUcKZOHrJVdok5zuLu7Yv3siWa0bL1TbRlai9Xqi1ZtxLENS4ze8Ojp87F80zb8s+lv64GwJ6cWYGjt1NPPmzcQYGjNR4ICxgUYWvPJUCOwaM0mdBsyVp6aPWM65MqSCX6+NZAogZdcaZ2uiA+WTxuFgrmyq2lOs+cwtNbs1HBgDizg6CutRXg6Y86iUKUq9KfUWGkR/dBVTWitv+pYaVsJfpWSIcrXlc0SxWplUZNaKQ9iuDmicr6x0NpwpbWxa40Fx/qhtf73g4KDQoTWom/lXFGCRBxiI0cldBa1qfVLkzC0duA/JHhrFFAE7j70DxVU6+vcffAYxWo3hV+9GujSsmGUwl2/fRcXr9/Ek2cv8OjpMzx59hxP/32OR0+ewTNePLni2/CwZWhdr10PxPf0wMSB3Y26BLx9i+xlamNAl1aoW6lslNrZU+NXbt6GWywXpPwpmT0N2y7GytDaLqaJg7SSAENrK0GzG7sTYGhtd1Nm9QEHf/iIPBXrolbF0ujeuonR/sXrYFGicHz/v6w+Pkt2yNDakppsiwL2KRCRVdHiTsMKnk0F1mFda8mV1oa1qI3NTHj3baw8iGjD1Kp0Y983tqFjeH6irrUoeyLKiYiNHMU4RYkQcSibOypjEf8W9a7FwZXW9vnzx1FTINICa7ftRqteQ7Bm5jj8mT1zpNszbODWvQcYOnk2tuw5CI+4cZEsSWLdPwk8PeTp05asRIcmddG2YZ0Ql9sytP41f3kM6toatX3KhGkiVluL+n/HNy61uJs9Nvjvi1fIVaE2EieIT5MomECG1lGAyibtVoChtd1OHQcexQIMraMY2AGan7F4JSYvWIYTG5fBzdXF6B2t3rILPYZPwPUDG+36jhla2/X0cfAUsIiAsjpZNCbqS7u5ucp2RdiaLJm33DhQ/PeeA0dCbYKof42p8Ft/sIaBt+H/G6vPHF5Na/361IY1rZXvibIgew8eRd0aleVQwhtvWLWglY0cy5curisxIr5289Yd5MqRBcPHTEHzxvVCbIZoTmitOIjxDezdSdauVvp0d3cPUUNbzUrrsML3iD44LA8SUTleR4EoFujQfwT2HzuJPcvnwMsjXoR7W7Z+K9Zv3wMPj7iynTdv3mPt9t34PXUq9GjTJMxNH2cvXY3Bk2Zh/6p5+DnZ9xImtgqtxYaXonTK0bWLwl0x/PrNG2QvVxtDu7VDzQqlIuzmKBeKX272Hj2Bf1++xoBOrVjv28ITy9DawqBszq4FGFrb9fRx8FEowNA6CnEdoOl3gYHIWa42urZoiMa1vgUbxg5xXpoC5TF39ECUKZLfbu+cobXdTh0HTgGLC4gQ9PCx77W2lZIa+iH2irXf36jLlyeHbpWvGIzh9eJr7m5uRsuEKOHs8xcvdPdRo3IFXRBsKrQWYa5hG/rjMSzlIdpWNmJUSoeENTZlQKbCZmXsitP5S1chSngoK5/VtuNbu6p8Y0Acxt5AUL6mv+mk4i3+Hd5KaxHMGxtTRB8ehtYRleN1FIhigcCgYBSv0xypUiTFkonDTfZ2//ETvHwdIIPp+J7xsPvQcQyfOgf3Hvojd7aMiIZoso2YMWLIjx5WKVPcZJtFazaVH0NcMW207lxbhdZzlq3B+LmLcWHnGpPjHj5lDtbv3Iuj6xabPNeRTxClaP70qYsZw/ri0vWbWLFpO85sW+nIt2z1e2NobXVydqhhAYbWGp4cDs2mAgytbcqv+c5HTZuHZRu2Qmw0bupo3KUffvghOmaN6GfqVM1+n6G1ZqeGA6OAQwsYKy2itRtWs/Gi/pgtueGhJSzMHb+aPhlaq1HiORSwkcDlG7dQrFYzdGzii/y5s8pRRI8WHR7x4sjazuLjg1v3HsbS9Ztx4szFUKMU4XTn5g2R3DtxhO7g5PnLqNCoDaYN7Y1KpYrKNmwVWjfp2g8xYvwgA1hTh7LaemSPjqha1nQ4b6o9e/1+yx6DcOPOfez+exYUk15tmqFxzUr2ekuaGzdDa81NCQdkQwGG1jbEZ9eaFmBorenpsengxIKTnBXqYHCXNuGWv1MGuWHHPrTrNxyXdq9BbHd3q4395t37SJI4IeJYoE+G1labNnZEAQroCdhDaC2GK1Yqj5s8E2Ft2KjckqXLcET2YVF806ZJFWrld2TaZmgdGT1eSwErCMxfuV7WrwvrcHdzRcUShVGheGG4usbSnZbcOwl+Spok0iMUZUp2Hz6Ofh39UK1sCV1ofePufYgSIgm8PFGtXAn8mvKnSPcVXgMZildGlxYN0bC6j6p+xGrrDbv248jaharOd7STLly7gZJ1WmDBuMG6EjDCZOn6LbJeoqvL92fF0e7dmvfD0Nqa2uxL6wIMrbU+QxyfrQQYWttKXvv99h0zBbsOHVf9ejUo+APEa+JRvToZ/dTk2cvXkOWPtJG+8cdP/8XBE6dx4NgpHPrnNJ69eCnb9ClZBDXKl0LRfLnM6uOB/1MEvHmLDGl/BUNrs+h4MgUoQAGnFmBo7dTTz5u3F4H3gUF4/eat/OfN23f4iq9y6KLkR9YM6aI0gHzxKgBteg/BvmMnkfTHRKhYohguXb8uX8hmTJsG74KCcOf+Q/kitGntqlFSR1qs7ihQtSH2rpgja3GrOV4FvEH2sjUxpk8XVC5dTM0lDnGO2H3+wtUbGDZltqxPtXXRNN19KautW9aphq5+jRzifm19EwytbT0D7F9LAgyttTQbHIuWBBhaa2k2tDMW/2fPka1MDUwf1keGwWqPzgNHQYTKy6aMDHGJKKU3ZPIs+dov7S8p1TanO0+85h8xdQ4OnjyDu/cfya+LdnJlySA39A4M/oA9h4/j2u27SJTACzXKlULdymWR6qfkYfZ15uIVTFm4HJt3H0D1ciUxcWB3htZmzwwvoAAFKOC8AgytnXfueecUMEvg3iN/LFq1ESs27UDhvDnQom51pP8ttWzj1IUrWLxmI/7esE2WERndu5NFP7K4eO1mDJ4wE1f3rTdrzOKa7QeO4ODq+WZdZy8nvw8MxM6DxyDqmX/88BHnrlzHrkPH5PCTJEqAqUN648/smUPczpiZCzB6xgKzf0GyFxNrj5OhtbXF2Z+WBRhaa3l2ODZbCjC0tqW+dvsW4fOZS9ewZ/lsswb59v17FK3ZBMXz/4lh3dvLa/85exEVm7STYXJsdzfsWDIDcWPHVt2ueJ1fq003vHv3HrUqlEHOLOmRK0tGeMaLG6oNEWiL3wdWbtmOh/7PUK5YQfxuJCS/fPM2tu49hFxZM8iyImJRxfkdqxlaq54VnkgBClCAAgyt+QxQgAJmCYRX0/r81eto2LE3XFxiYUCnVogWLRqCgj4g+ONHueo3+MMHBH4IRu2KZWWoqvZo1XMIAoODMH/sYLWXyPNEncAc5WphbN+uuprcZjWg8ZMHjp+BaYuW47dfUiJl8qTI8FtqZPg9jfwlI4GXR5ij7zVqEub+vVZu4lO+eCGN36W2h8fQWtvzw9FZV4ChtXW92Zv9CDC0tp+5stZIxacU81auH6KMmzl9KyH1nFEDkCNzehSp0QS5s2bE2L5dZHm4dGlSy7bVHBev3UQNvy7wTpwIC8cPQbIk6vfCOfTPGRw6cRrPX77Cy4C3ePvuHeLGiY34HvFkCcEyRQvIciWibEkZXz/sWjYLv/78Ez5+/oK47i5qhue054jfY8TCFM948eDlEQcecb+/gfDm3TscOnEG+47+g+37j6B76yaqaqI7LSZvnAIUsFsBhtZ2O3UcOAVsI2BqI0bxAqtRlz5GN4ZURpw1w+/YsmCq6hsQH51sXqcaWvrWUH2NcqJYbS1WH+9bOdfsa7V8gXgRm/t/G/c0qV3F7KFOmr8UQyfNhvhlp2zRAmZfzwu+CTC05pNAge8CDK35NFDAuABDaz4ZhgItegzEg0dPsGWh+tfDhm2Mnj4f0xevwi8/JUNgcDC2L54mP+l45eZtlK3fCp2a10fbhnV0l4m61I/8n+LRk2fyn7fv3uPTf/9h9vK1KJo3Fyb0/wtir5yoOtIXq4xWDWqiac2qdh1ai5C4//hpaFi1Imr5lA4RJquxE4Hz3iP/hFsSRpSOqdaiM27ffxBmk2KuCuXJCe8fE8rFKHNGD0DZInxNr2YOeA4FKGA/Agyt7WeuOFIKaELAVGitDFKUDInvERdenvHkCgHlEKuxfRq3kyufx/Xrpvv6lj0Hcf3OPXRoUi/Efa7ashNt+wzDzqUzZd1scw9lV/baPmXkzuyGR8Dbt2a/2DR3DFFxfrO/BuDitRs4um5xhJtfvnE7xEabs0f2lx/t5GG+AENr8814heMKMLR23LnlnUVOgKF15Pwc4epzV67BzcUFHvHi4vGTZyjboDVWTh+D/DmzRur2KjRqg8s372Dn4un45ecUurbW79iLlj0GGW3b3d0NSRMnQrIfE8H7x0Ryf5z6VStEahxqLm7dayiePn+OJRNH2G1offjkWVRr0UnusXP11h15203rVEXF4oWRM3P6cBnEfjszFq/EnL/X4l1gICqUKIyJA7qH2pvo7kN/VG/ZEWl/SSVDfmNHzB9iIGeWDLpviTcwxsxaiOXTRqFgruxqpoPnUIACFLALAYbWdjFNHCQFtCOgNrQOb8Rb9h5Eky79ZB2+kgXzovuw8dh58Ki8RAmzXV1iyRXSvu17on9HP7SoVz3CCEo7M4b1RcWShWU7oh6gX4/B+PjpE1ZMGx3htm1x4cnzlyF+SRHlUkoVyhupIcxdvg69Rk7k6owIKjK0jiAcL3NIAYbWDjmtvCkLCDC0jhyiCPjOX7mOvNmzRK4hG10tNlJPV8QnRO/iXlbPHBvpET3wf4rL128ZfT0oNkEM+vBB14eXRzy5qbp+mYlID8CMBlZv2YU2fYbi8u71iBErlt2VBxGe1Vp2RpG8ueSCD7Fies3W3Vj+/3v6iPInsd3ckTfHt71k4nvGQ0IvrxCB9NRFyxE92g/wrVpeBtxdh4zFz8m9sXDcUCSM7ymvu3HnnlxhnT3TH5g7eqAZuoBfz8HYceCIrGeeWu8NDLMa4ckUoAAFNCbA0FpjE8LhUEDrApYIrcU9KuUpRDgdL04c9GrXHO/eB8oANWv639GmUW2IWtatfGuiW6tGkWYR/Y2duVB+DDNmjBjw7dATrwPe4tOnz2hZrxq6tGwY6T6s1YCoCejm5oo1M8dZpMshE2dh8oJlmDdmEEoXzmd2m2IH+xlLVmLZuq2IHj06PD3iIL6nB/7MlhnN6lQzq3652Z3b+AKG1jaeAHavKQGG1pqaDg5GQwIMrSM3GaLU25SFf2Nkr07wrVI+co3Z4OqVm3egXd/h6Nysvq738iUKydW6znQ8f/kaGUtUwdzRg5A/d44oD61v33uAt4GB8hOfIkQ2Z2NKw3m5dvsufBq3R+Z0v8nVzIbHvy9eYcfBo9ix/4gMs5VDrK738vCAp2dc/JbyZ1QrV1y3Wb0o9VenzV8Qn/oUz8LJ85cQ/OGjXGAjFtqYe4hrq7boiNMXrugu/TXlT9g4b5LRDTXNbZ/nU4ACFLCFAENrW6izTwrYsYClQmtBIF7Ae3jExV9+jXJwR7UAACAASURBVOSu4uIQL7QadOoF8cK2YXUf3a7oliATH5M8dvo83r0P+rayYfwQuZN5o8598PfUUSiU23IfpxOrgpR7UjN2cf68FesQL3YceHrERcL4Xkj/W+oQLzLFSp0l6zZD/PK2fcl0ZPr9NzVNqzpHzIX4pSpPtkzy/NhubnLjHFPHrfsPsW77HvyczFvW5hNvCIhDrOwR7YkX8VVKF0f7JnXkhpGOdjC0drQZ5f1ERoChdWT0eK0jCzC0jvjsiteDYlNtsXL035cvcXzDUri52tcGfo279MWXL1/M3lA84mravbJU3ZYQe9v0au8XJaG1eN25ZusuuQJalCTUP0SAO6JnB7NX7IvV7OUatELyJD/Kki6x3d0sBiwC657DJ+HHRAmQPWM6pP/tV6RMkTRS7YvfF8TCnBevA9BxwEjEjeOOVdPHhvlzI8oFPnjkL/v8/OWL3Nzx1Zs3eB3wDt6JE2LvijmRGg8vpgAFKBAZAYbWenpBQcEYPnaK/Er3Tq3lSkZxrFm/FSvWbpT/nTZN6hDfiww+r6WAPQpYMrQO6/6fPn+BhSs3oKtf5FdY6/cRFPxB1tNO+VMyjO/XTbfZTP9x07Bi43a5o7n42GRkD7HRTbFaTTF5cC9VQbi431qtuulq4+n3nybVz8iZ6Q/cvP9At7mlqJ03qHPryA4z1PUT5y2VG/S8ki9238jNeUwd7q6uqFOpbJg1sZes24LJ85fi7oPHGN6jIxpUM79m4opNO+Qvqq3r1zI1HKt/n6G11cnZoYYFGFpreHI4NJ2A2IDOM14c3WpHa9AwtI64cu/Rk7Fz/xFsXTQNeSrWQ9vGtUNsLhjxlq1zpXjtKUqDjOrdCdXLlbROpxruZfiUOVi3cy92Lp1j8dB69+HjaNatP6JFiyYXUoia0S6xYkqN/z5/xvL127Fm2y65ktm3SgX8mDA+4nt6yhIeovzMyQuXcOr8ZXlt5dLF5HUvXgWgfKPWcIkZC+vmjA+xT4+GmXVDe+gv6qf7IXO6tFg0YWioIYtPW85ZvgaZw1iocvbSVfTr6CcXEvGgAAUoYAsBhtb/U1cC62s3boUIpo+fPItFy1ZjYO9OiO/lhUnT58or2rZsbIv5Yp8UsLmANULrqLxJsfrAM17cUF2Ua9ga/336jBIF8hjtvnalskiWJLGqoTXt1h+HTpyRH/fTr6Nt7GKxiUtNv65IlMALC8cPDRGai9rVp85fwj/nL8kX1oX/zClXh1hyhYeqG7LASWu37UaXIWNRumA+jOzVMcx7EPPz6nUAnr8KwKXrNzFlwTK5Mv7z5y/o0LQeWtU3viGNBYYYoSYYWkeIjRc5qABDawedWAe7rfxVGuD1mze4uGut1e6MoXXEqJ/8+wJZS1fHxIHdZeA7bs4iTJ2/HP9sXmY35Q627z+Chp1649r+DbIcnrMfJ85chE/Tdtizcj7S/fKTxTiUEiyNalRC73bNdQtTDDu4fvsuhk+dh617D4bqW2z4Hju2G46fviA3OezZuin6jJ4sN03cMGeSfK1uj4f4XaNCw7aoValMiEUvoiTjqs27sGzyCGTLmM7orYnNHecsW4NjGxbz+bXHyeeYKeAAAgyt/zeJIoxO5u0t/+/cxcu61dTK16v4lJHfMwyxHeAZ4C1QwCwBew+tw7pZUZd5/or1CPr4AcFBwbK8hVgdE/zhA27dfSBfqG2YNynEhipi9cXdh4/lx/mUQ9n0cefSmThw/BQGTZgRqgajqIt34uxFHDt9Dpt3H0SRvDkxeVBPuwyjzXl47tx/iKbdBuDNu7dI7p1EXvrl6xe8ev0WL1+/lqtZ9A+x8sWvXk34NaiBm3fuo2qLTujXsVWEVmubM05zzmVobY4Wz3V0AYbWjj7D9n9/s5auxtDJs2Td2DmjBqBs0QJWuSmG1hFj/mvoOBz85wyOrF0oGxDhYc5yteUnvPq0bxGxRq18VYf+I/Dk2XNZho7HN4E0Bcqhq19TNK9T2SIkot65KJ3n51sTfTuofy7EmyKvAgLwPjAYf6T5RRd033vkj2GTZ2P9jr2yPMbGeZNVL1yxyA1FQSNHTp2VG9CLT4OK8n9x48TG5Ru3ZLmTdL/+EmaP4nehP33qydXpA6PgU55RcKtskgIUcDABhtZiQzi91dOiFIgSWou5FuVCMmf4A0poffP2XYybPBsd2zTFrw5Yn9XBnm/eThQIOGpoHR6VqI9Xok5z5M+VVYbL4rh7/xFqtu4KsYlKvw4t0dK3BgKDglGgagP5ccT+Hf3keeIFr6ilbewQLxrFxw+b160WBTOl3Sb3ilp5rwPw6vUbBLx/j1gxY8DdxRWubq5wdYkJNxdXWZ4pY9o0SODlobuR/cdPoVarrujSooFcfS0+xnnx6g252ip50iTwTpwIKbx/hHeihEjqnTjEKiyxOl18NNLSB0NrS4s6b3vikxmzlqxG9QqlZI14ezwYWtvjrDnPmEVt5Nw+ddGpma8sAfDhw0csmTTcKgAMrcNnFivfxWuClwFv8eHjB3my2Jy7Qcfe8nVX1bLFdQ0oG3mLzaj/zJ7ZKvMXmU5EaZCebZvZ5QaSkbnv8K5t1KkP4sWLiwn9u0W4i827D+DgP6dx7dZduV9N+8Z10b11kwi3Z+zCs5evwSNObKT6KblF27VlY2Kl+cHjp3H83EW5klxN/WxRUqV1r6E4unaRLLHIgwIUoIA1BZw+tBYh9SN/f125D2OhddlSxZA7RxY5L4ahdWDwR2vOF/uigM0FgoI/wdUlhqwX50zH+as3ULlJW/Tt4IfsmdOjYcdeyJ0lI/LlzIohE2cgX85scjW2WD29c9nsEJud3Lr3ADfv3ocofRHw5i0SeHmiyJ+5EF8vkLWEZfRo0fDVEg1puI0tew6g98gJyPh7WoiPccaM+W3jx69fv+LZ85fwf/Ycj58+k/+INxH0j1gxY8nNfzL+/huCgoPwKuAt3r57j4oli6Bq2RIRuuvg4E+IFSsGokd3rp+HCGHxonAFWvYYgB37j6BD0/po17iuXWoFf/gPMWNExw8/RLfL8XPQji3QdchonL14Vf4dve/oCTTu3AeH1y2Wb3hG9fHpvy/4+uUrYsX6Iaq7sqv212zdiRFT5sp9K4wdKZMnw54V30ozKof4BFyFhq0hXlulSJoE1cuXkitF5Wust2/lho2F8uQM1Zz4W/rLV+u+Sjp+5jzqtOmG4xuXyQ22eXwT2HXwKFp0H4Bti2dA7N2if4yftRCXbtySi0LuP/THx0/Gf9cWn8bL8kc6+boud7bMKJArG3mjUED8DuTi6oK/p4yOwl6cq2l311jOdcO8WwpEUMDpQ2uxyvrwsZOh+MSGix38mmD8tDnhrrR+H/htNQAPCjiLgFgt5BrL+UJrMb/rtu9Gl8HfXqw1rlkFPds0k/8tasW16N4fYnOnWSMHyEDaFocITr98se4vZLa4z4j0KX4hPn3hCk6ev4QrN2/hy+dvTl/xFf+cu4hUKZKjfVNfZEufDg8e++P2/YeyXEvFEkXC7S744ye5Uly8YcCDAhEVWLFpG3qOmIAs6X/Hx48fsWHut02h7e348Ok/xPwhOqJHZ2htb3Pn6OMVm6xVad5eBi45MqWXt/unT13UrVIebRrUjvLbF5vAiTdXY8b49karsx+nL17GwHHTcPH6TdSsUDrE37UusWLBI14c+WkpL4/vn7YyNDt36So27t4PseLWMPRePnU0smf8Ns/KYYvXSAPHTcXlm7cZ9BlM3n+fv6BZt754HxiEFdPG6L47ctocLFu/BcUL5JWrm9OlTgmPeHHhKj6B5xpL/tvd1QWuri4QzwkP6wmcuXgF1f06oWi+PJjQv3uIxTnKKG7euYdL12/BxcUFpQvns97g7LSn2O4udjpyDpsC1hVw+tDakFt/pbX4eDprWlv3gWRv2hdwxvIg+rPSb+xU/JIiORpUrxhissTqnkVrNlnll1/tPyX2NcIH/k8xZsZ8LN+4PdTAkyRKgGZ1qqFelXJGN6BheRD7mmstjlbUei9WuxnaNq6DnJkyoHrLzvhn099I7q1u41ct3RPLg2hpNjgWfYEqzTsiScKEmDq0l+7LI6bOxeotO3Fi07Iox2J5kG/E4u/bgeOnY9Ou/XJj6cHd2oRbTzciE1OpWXtcu3kXWxdOU1X6ICJ9qL0me9maaOVbE01qV1F7iVOc9+HDJ9x88BjFazbC+P5/oWaFUthz+ATqtuuOuaMHokyR/E7hYG83efTUOTTs1EeWMFs8aRgSJ4iPHQeOyNfPB46dkjXnlUN8+uGvVo1RqlBee7tNjpcCFNCYAENrgwkxDK0NN17Ur3+tsbnkcChgFQFnD62tgsxObCJw96G/3CRSrOzy8oiLoKAPmLd8HeatXIc4sd10m0eK1dkfgj8iMPgDAgODECw27wz+KF+sp/8tNVo1qIkqpb/X37TJzbBTuxEQ9fLFm+Qb5kyUY05bqCK6tWwYoZBDbKokSjeJUkWe8eIgtru7VR0YWluVm52pFBCbHxeu3hhbFkxB1gzfN04Wm63lqVhXbpBXKHd2la1F7DSG1sC4OYswcuo8GXj16+gXZcGkqI9d2tcP0aJHx9YFU0PsbxGx2YvYVReu3UDJOi3s9k3IiN21uqtEaP3x8xdMm78UC1ZvwKoZY1C5aUfUrFgKAzq1UtcIz7KJgNjTp16HnvD/9zliu7lC7PtTLF9ulCqcD7mzZMBvv6TE7XsPMGL6PGzYsQ+/pvwJCeN7Gh1rd78myJ0to03ug51SgAL2I8DQ2kRoLb4tguwVazd++2UyTWp079Ra/oLJgwLOKMDQ2hln3bnvWeycfuLcRbx4+UpuFPX63Tt8/fxFogR/+F9N6/+VB/n35Sus3bYHsd1d0aJuddSvVlG3G71zK/LujQlMmLsEM5eswvbFM3Qrqzv0HyFreYpNxsw5xEd3yzZoHeKSFvWq6zaFNaetiJ7L0Dqico5znQg0tLZR119Dx+H0xSvYuXRmKOgafl3g6REPM4f3jdJJ0FpovW3fYaMf3x81bZ7ct6No3siXOVu1ZSdGz5iPew/9pa2bqws6NvNF24Z1otRaNC4+wVKmfmukTpkcRYzUtxbn1PIpG6WfaBkycRYOnzqDLQumRvn92lsHSmgd84doyF+lviyvlz1jOmyab5+lsezNP7LjffPuHfqPnYZsGf9A+WIFw3xj6MrN29i864DR7s5cvoozYo+BpTORLIn9fbIssoa8ngIUUC/A0Fq9Fc+kAAUAMLTmY0CB7wJhlQdZs3UXRk6fh7fvAtGuUR0ZXotf2HlQQBHYvv8IGnbqjfljB4f4+Kzy9Uu71yK+Z9j1XPUlxRsrRWs3RYbffkWjGj7yW2cvXcOgCTOwddE0ZPkjrVXgRWj9ITgQ7wMD5UanAe/e4eWrALwOeIME8T1RqVRRq4yDndhG4Mips/DrMRjrZ0/QTHAtwpUspapjSLd2qO1TJhTM+h170X/sVOxaNhsJLLw5coif0Q+f8OXzF2ihhunEeUsxbPJs+cmg3u1boHCeHBAf++80eDTEmw7i6NjEF91aNdLdglg1vOvQMbjGEnWFXeDm6gqxEZ74t7uba6hN8EQZkELVGqJ8sUIoX7wgUiZPKldgWvMQz+Oo6fONdnn73kOULpIPI3p0jLIh5SxfCy3qVEfTOlWjrA97bVgJreO6u0D8nde+3wjsWT4bSX+M+k1R7dXM0cYd/OEjKjZqKz8dtn7uRPnnCQ8KUIACxgQYWvO5oAAFzBJgaG0WF092cAFTNa1nL12N0TMXIkaM6GjXqC58q1YIEV6LIODtu/dmKUWPFh0Zf08jN4rkYZ8Cd0Utz9rN4Vu1PPp1bBniJkQAna6ID4Z1b280ZDN2x71GTpS/+O9dMQdxY8fWnVKnzV/wf/Zcfj2qjxt37qFGq6548ux5mF1NH9YHPiXD39w0qsfJ9qNOYPCEmZiy8G9Z53TtrHH45ecUkepMBJ8pvH+MVBtz/16LEdPm4ez2lWG+cZi5ZDU0qlkJHZrUi1RfhhffvHsfCbw84eURD1pZaX328jWU8fWT93rt9j1s3XtQrjZ+6P8MxfPnkX8ebdp9AKLed4Fc2VCpdDEs37gVJ85cDNemYK7smD9usM64crMO+PjpEzZrdOXslj0H0aRrP5zfsRqJEnhZdN5FY/+cu4SKjdvK5+7HhAks3r69N6gfWot7ERua/546lb3fFsdvpoD4M75E7eYoXiA3Jg/qaebVPJ0CFHAWAYbWzjLTvE8KWEiAobWFINmMQwiYCq3FTb5+8xajZy7AnGVrZF2/xrUqy2Bvx/4jePLviwg7iBqsJQvmRdliBSE2jIzsIcb57n1QlH5cOrJjdITrRShdtn4rxInjjo1zJxm9pcZd+uK//z5j4fghJm/50D9n5OaN62ZNCFUb8vHTf1GgWkO52r9947om24roCSLQqte+B/7MnhlNalVGjBg/hGpqydrNWLN1NzbOm4wcmf6IaFe8TsMCxWo1kx/xv//IH5dv3pYlbkQ904gc4s/GrKWr46ekSVC2aEFUKF4I2TJ+r0etts28leujWP7cGNQ5ZOkc/etFmR4Rbp/bsUpts/K8F68CcP/RY9x5+Aj3Hz3B3QePIOpk33v4WL5ZJA6xwZzYaE4LoXVgUDCK1W4qw8F5YwbJ8YmP709buALVypeACJ6VQ5QbatljkCxVJFaoN6lVRa7MNnaIP2cqN20P7ySJsGTCMCzfsB2DJ83EnmWzNbPi3ti48/jURcXiRdCzbVOz5l3NyeKNxKs372L1zLFqTne6cwxDa6cD4A3rBPYdO4narbthYOfWqFu5HEvq8dmgAAVCCTC05kNBAQqYJcDQ2iwunuzgAmpCa4VArK4dOGE6tu49BO/ECVG5dDHUqFAKac38yPT7wCDsO/oPtuw9iB37j8oNIEXYINoqW7SAWWVINu3aj9Vbd+HC1RuypqSoK3hw9QKz2nDwKbb47Q2dNBuL127C7r9ny+fA2LFy8w606zscNw9uDndFvQiLW/YciKplSqBXu2ZG21qwaiO6DxuHQ2sWIHUEV75eun4L+4+dlCtGxT8JPD3g6RFXblp65ORZtOgxEDXKl8TArh3g7hIDMWPGMDoWEa6LtrYsnCbfaDl76ap89nJmyWC1EiYWn1A2KAWePn8hy3AsmzJSlpto3n0gjpw8gx1LZkboI/+dB47C2cvXUb9qBYg3PMSnUvLlyIJpQ/uoXhl74MQp1PTrisNrFoS76vtVwBtkLV0DEwd0R8WShUPMqCiXcc//iSybIQLpuw8f4cHjJ7j94JHciFc5POLGxS8/JUOSxAmRKkUyuLm44MXrAMxfuV6WPUiZIoVVy4OIj97fvv8An798Qca0aeQwhakIiMR4xHhNHeLvls+fP6s6VwTXVZp1QIwYMfDQ/ykGdW0D3yrlTXVh0++LN5LFKvzT25YjjoU3rc1QvDL+atVE8wa2mgCG1raS12a/S9ZtwaDxM/Dpv0+oUroYsmRIh8vXb+LU+Su49+gxalYsjcY1K8s3MXlQgALOJ8DQ2vnmnHdMgUgJMLSOFB8vdjABc0Jr5dbFBlGpfkpuMQmxO/uiNRshVtyKlXC7ls1S1bb46HqBqg3lym+v/wUYC1ZvgG/lCiFqmapqjCepEhBvOGQrUxN9OrRAvcrlwrwm4O1b/F7YR67SFB/PFyGgOG7fe4Anz1/g7/XbsGXPIXzFF1QqWQRj+nYNt3+fpu3gEjMW5o0ZiNhmhjPiY9uVm3aQnxgI62hUoxKG/tUOpjZiFPWFyzdsi8dP/sX7oMAQzYmfiapli6NB1YryEwk87Etg+cbtEJuI3j68VfemV/HazZD0x8SqPjGgf7fKn00Lxg2WnyYRh3izo9OAUXj87BlmjeiPPNkyya/vPnwcJ85cwItXr/Ey4C3evnuHuHHiIIFnPIhSGJ7x4mLl9DEmMbsMGo3rd+9jw5yJ8lzxsXWfxm11K6ZFOyKMTpI4EVKlSIpkPyZGyhTJ4P1jQqRMnizMN/pEmQx3V1fMHj0oykNrUUu+6+BxELWcxZsI+od4Q1K8Mbl+9kTkyprBpEdEThCryys3ay/fHFsycXhEmrDqNcqfx+2a1EHr+rUs1rfyZsmVvevD3KDOYp3ZaUMMre104qJw2OJNsnkr1mHqguXy9YaogV8wT3a4xXLBqi075J/FJQr8ifH9u6ne70O8mSb+bJ8+vA/ixYkThaP/3vSeIycwad5S+WegqPfPgwIUiLwAQ+vIG7IFCjiVAENrp5pu3qwJgYiE1lGFeu32XVmrtFntqujRxvTHncW5KZJ5Y+bwvrohKcHTsQ1L8HMy76gaqtO2K1b2jZm1EKe3rjC56dDkBcuwevMuWesztps7YsWKAbEiVKwIzJ01I6qVK4HShfObbEdgizIGYpWzS6yYciWsCODUHCI89GnSHkXz5sKkQT1CXCLafBUQgDdv3+vKNpgKrUUDonZu3zGTkSndb8j8R1o5ptcBb+UnB7bvOwIvj7hYPnWURd/YUXOvPCdyAmK1/Zs37+TzpRynL1xBuYatMXf0QJQpkl91B6LWsP/Tf7Fl4dRQ13QcMBJ/b9gmS8xcuHoTHz5+lM9frJgxQ5wr6infuf8Io3p1QrliBU32Lf78LFy9MXYunSnrUItyF8m9f8Tgbm1lKB3RTcLOXbmG0vX8sHjiCOTJminKNmJ8/vI1arfphi9fvqJM4XxG7zfNLz9HeU15ESz98EN0WdfcHg6xWa34ZIuobW2pQ7x5I+Zj8cRhlmrS4dphaO1wU2qxGxIl1P59+SrUquoVm3Zg8MQZSJ8mdYi/Z8LruHzD1jh14Yr8JNfyaaPCDK7F6xLx51ZYn35Te3MDxk3H9MUr5OnlixfCrBH91F7K8yhAgXAEGFrz8aAABcwSYGhtFhdPdnABLYXWgnrp+q3yI+BitaAouRDWMW7OIkxfuFKWjDDchKpsg1bwihcPSyZpf6WcvT1eeSrWRZXSxc1ayf7sxUvsPfKP/Ji/qBdsbjkZxUis3q7VqhsCgz9gxbRRJjcHE58I8GnaXtapnjHs+xsb4ZmrCa3Du16sFPXt0AtXbtyWv2Bm+v23cKdYBEOPnj5F5nRp7e1RcLjxpi1UEV1aNECzOlVD3Fu3IWPlamhRdkjNqjNlo0CxOjp/zqxGnUTJDfFmjngzJV+OrBbblFaUEokR8wfcefAYiRJ4YtmkkarGbGoy/XoOxvU797BhzuQIh9aiPMr5KzdQt1LZUN2JN5dqtuqK339NJd+ENPfTFKbG78jfFyF7tjI1YGyTWPFGxsYd+9ClZUOzCH4rWEFupCs+OcLDuABDaz4ZEREQtfbLNmiNvh1awM+3ZrhNiLryqzbvwtLJI9C+33DEje2OFdNHy82qRamn7fsO4/DJszh5/hJevg6QbVUuVQwtfKuZ/ZpCfIpM/P0h/v4a0q0d8uXMIvcu6dS8vkU/xRERM15DAUcQYGjtCLPIe6CAFQUYWlsRm11pXkBrobUAa9S5Dy5du4k9K+YYrdN58dpNlKjTXG4OJspPGB7nr15Hqbotof/RfM1PhB0McMuegxArSMVmb7ZahaiEwrfuPsAvP38rUfPl6xe8fPVG/tKm/OKmcIrVsWKVrNojsqG16EessmratR+OnTmPprWqIGaMb/WxP376T9bK9f/3X7kKV/zSqRyidu7IXp3UDlOz54kSPwePn1L1SQkt3YRYySZWtB1cPT/UxoviY975KtdH9fIl0b+jn8lhi3Ia4lg7a7zJcy19ggjX67XrId8cWj51tMXCcPGsijesWtT9trGk+Mj6gydP5L8fiWf62XNZN9rLM66sF1+pZFE01Qv/127bjVa9vm3KKlbvFsuXW3fr4s/rGi27omrZYjIs4WG+gCgfsOPgUexbMTdE2YGC1Rrhxp17GNW7c6hyTuJNkxu378mSNOITJ/99+k92/OjpM6zdtgeXdq/hmwfhTAVDa/OfU17xTUB8Yq336MnYsmAKsmYwvjnvuu17IN4snDN6AMoWKSA/pVbDr4t8HfF/7d0HeBzV2fbxR10ry7Jky0XYYOOKjYmpoSahJKGEXhNiSsAQUxxeG0gIIXQSUx1CCSbgAKYn2IABOy8llFBfbEwvtsG9ypJcpFXX9z1nNdJ4vdLOakbS7sx/rkuX2szsnN+c3Z29z5lzMjMy5ItFS8xz/eD995Z9xo2VkUMHS+nGCnnw6Vmic4WMHj7UrFdVXS3VNTWik9jqd70+aWsZstNAefCWa2XMiMiEtfNef9tcjz95762iE6ezIIBAxwUIrTtux5YIBFKA0DqQp51CtyGQjKG1hkR6m7v2kD3jpMhEWHX1DfL14u9k85at8vwrb0j/4t7tjvOqH+Kff/kNmTfz3nYnMAt6xVi+eq3MeGq2lFdskorNW6Viy2Ypr9giFZs3y4aN5WYSrqsnTzSNB9qDfdhOO243zEZXG+oEbTqR56Kly8zwCavXrpc+RUVmEk4dn3fHHQZIv+LeMrB/f+lT1Cuhw/MitLYe8JzLrpE33vs/M5RJYUGB9C4skKLCXuZ774Jekp6eZla1JrvT0DrZJ35rD1N7dR591sVmYtVZ908zz99UWW677yF5cs48+fDFJ2Mest7WrT3dtMd+cZ/IeOVbK6ukfNMWKauokHWlZeb1Scv+4SdfyJx/3G2G/+iO5cIrb5Jbrprs+cR8v7/lLnlu3msmtNbnlz7X+hYVbVdEHd7jsWdfNLeqTz7vTFmybIVMf/SfMnH8qbJm/QZ5+a13Zc4/7jLBiI7zffKvp8gvjjvK9Dxk6ZiANuYd9vPzZMTOg2XmnX8yO9EJc7VH/z6772p63r8z+5GWna/dsFEOPPFMkaamlslpdYLaQp2otqCnjNt1Fzn9uCM7djAB2YrQOiAnupOKqdcHn331jUy79neSFrkUaFl0yLILB9aZYwAAIABJREFU/3CjmdDxtj9e1vJ3fX/5/Z/vlFHDh8gh+3/fzAETa9GGwFf++76EcrIllJsb+crJkdzcbMkLhSRXf87Jlrxc/Zv+X3/PiTmvgQ4Hp++Pj/zlJjMeNwsCCHRMgNC6Y25shUBgBQitA3vqKXgMgWQMrfUwtcfmlTf/VZavWmPGfLWWXYbtLLvtMsLc7tzeLOw6lMSJ502RDWVl8vwDfxXtQcKyvcDv/jRNXnztTTlg7z3MWMx9ehW2hKl19fXyyDNzTG/N8SceLTffO0NeffLvLb1w/OjpZWidiM/Vt98jf3/8mU6dZC6R40l0XZ00T28lHrnzYMnKypLPv1ksr/9zhrmNORUWbZAZO3J4u73dNQx+6//mm7F+7cuOJf1l6E6DzGvMkIE7yJhRw+SH3/dfr7RwTZ3jiRi3VFbK1HselBlPPWvC879ef0XLmOCnX/w70QYODWMuvPJGOfWYw+W6KRemQjVJ6mP86POvzHNw6u8ny9hRw82dA/fcdKXsNmqEaI9r+7jseseMjrlrTdqZ1AVL0oMjtE7SE5Mih6UBtE70u2xl6x1X9kPXiZ1fefx+T4Z3ckvyx9vvkQcef8a8Tp//y5Pd7o7tEQikAKF1IE87hUag4wKE1h23Y0v/CSRraG2XXrV2vazbsFFGDRuS0O3u2mNbJ+9bX1omz824S4YMYmJGu6vebrrHEafKdZdeJGedfEzMyq3rXHXrXTJr7qtywF67yzP33+G/J4GtRN0VWush/PzCy+WTrxaZifS013iqLJVVYTl+wiXmcJ994C9SU1snPzz5bPnB9/eSv/3pqqQvht5VMPqQ4+XBW6+Tow79Qdzj1durFy9bbm691luwg7IkElpbJjp+q84vYG801NvUT544RT767CszhMgNl14UFMJOL+ddDz0ud9z/iBnvf8zIYS1DI51z2dWyvnSjvPDQPfLa2x/IL39zhbzyxN/b7KnZ6QfqgwcgtPbBSaQIjgX+9dLLMumPf5YzTz5mm8lw9bqQBQEE4gsQWsc3Yg0EELAJEFpTHRBoFUiF0NrN+dIe16dd8FtZunK1XH/ZRXLq/x+XliUioLd9znhythkSQW8PbW957Z0PJDMzw5c9SO3l7s7QWuvqEWdcIAU98uW6Sy+U/fb8XkpUVQ3Avvl2qbz48L0tY51bwZiG1scffminlkPvANDxef/4m/MdDwW0dOUaWb1unTmuDxZ+Zu4i+ObNOSnTM7xTQdvYeUdC67aOUxsUZ86aI5POPr07iuLrxzzx/Mnm+fjmvx5qGd/a6oWtk4NOvu5mOeyg/WTqFZGx11k6JkBo3TE3tkpdAR125OzJV5k5DKxlzfzXUrdAHDkCXShAaN2F2DwUAn4QILT2w1mkDF4J+D20ViedFf1/rr1F5v7nvyYIvP2qS7cLt3Rs54WffWV6o+31vTEtk+Poh32dROyFV96QCb84SS48s/3Z3r06L529Hx0Xes8jTzW3ev7PueM7++FSZv/dGVorkvZsv/HO6fL4c3PllJ/9VK7+n4lS3DsyhnIyLjp2/AuvviUvPny3DBu84zaH+Nub7pBZc1+T00840tQxnTTK6+XR2S/K5TfeLjv072smBdQxwS+f+Cvp22f7sZZ13N/nXn5DnnjuJfnw48+3OZTv7zHWDM3C0raAl6E1zp0noIGSTtJmn+xSH00ncXvrgwVSkJ8v7z3/qBnLmqXjAoTWHbdjy9QW0LuTyis2mzkd9twt9kSSqV1Cjh4B7wUIrb03ZY8I+FqA0NrXp5fCJSgQhNDaInnj/fny+6l3ynfLV0peXkj69NLJ8Qpl1bp1241Tq9uU9Cs2PUoG9O0jQ3YcKAs//8qE2XffcKUJyZJt0WELrrz5Tpl2zW/jHtrMWS/INbffIwvmPm0mCmSJCHR3aG2dh/mffika+paWlctTf7tVdCz3ZFt0KAKd7E3Hxd1n97HbHZ4OAzH13gfNWN15oVy5YPypZix6r5b/ffMdOWvyVWYCvwvOOE0e/tccmfb3R0TH125r0TsKjvnxj8zEf6nSk90rL7f7IbR2K9i92+s8ETpc1p+vuETOPuW47j0YHzw6obUPTiJFQAABBLpIgNC6i6B5GAT8IkBo7ZczSTm8EAhSaG15aWC7znZ7Y9/iPrLPuDEtEwxqLxINDZcsXSH77z3OTGSly9IVq82M7kuWrZT7b7lGfrRvck229o+nnzWTV/56/Cly7eQL2q0eB5xwpvz4oH3lesaT3cYpWUJrPSgNfSdcfo2pi4/dNVX2/t4YL57ybe5j5Zr1MuX6W+TjL74xDTY6rrY2zgws6S879O9n/paRkW62/3rJUlPXnIwDrQ0/d9z/sGiv6HN+foLcdPkk1+V49e33jc1pxx6x3TAH78xfGHP/aZImu++6S9yhcFwfnE93QGjt0xNLsTokQGjdITY2QgABBAIpQGgdyNNOoRHouAChdcft2NJ/AkEMrd2exVvu/Yfc99jTMvuBv8i40aPc7s6z7fc79pdS0r+vvLfgE5n6+8kxJ1f8cvG38vYHH4nOBq9jWafShH+eQbWzo2QKra3D/M3VU2XOK6/LTb+7RE4/7khPGLThZqeBJbLn2F3MOM6PPDNHrp82XYp79zJ1yFrqGxqktLxCyss3i465bV90Aj2dSM/p8vz/vi6//v31Mv3PV8uxPz3Y0WaLvlsmI3Ye3LKuNihdN+0+efL5efKTH+wvj/zlJkf7YSX3AoTW7g3Zg38ECK39cy4pCQIIINDZAoTWnS3M/hHwmQChtc9OKMVxJUBo3TG+G++8X554fq78+9HpMqikX8d24uFWOub2eb+7Tj6a90956dU35Q+33mV65+4+ZpT8+413ZN7rb8s7Hy6UrVVVkpOdLef+/AT54yW/9vAI/LGrZAytVfaGO6fLvY88JT1CeXL4jw6Qow49SH522A87hK71ROuLteiY2aVlFTL53DPktxf+qkP7dLrR9X+ZLg/981mZN/NvMnLokDY304B8yvW3yUuvvSV9inqZ8Xl33mmQTH/0n9LUJHLZ+WcmFJg7PT7Wa1uA0JragUCrAKE1tQEBBBBAwKkAobVTKdZDAAEjQGhNRUCgVYDQuuO1YcJvr5Vvvl0mLzx0l5ncys1SWRWWua//V95f8InccPkkyc3JTmh3R4y/QMaMHCp3XH252W7ydbeY3qjWor1Sf/qjA2TcmJEtw50k9AABWTlZQ2vl1+FpdBznl996V3R82sGDSuSKC8+V4w8/1NHZ0V7K43/ze/lq8TK59arJ0r9vH9EJORd/t1wO3GcP2XXkMEf7cbuSTgi3cu16+d/H7pP8vLztdqd3Clxw5Q2S36OH/GHSeaLPDS2zTiJ3wpGHyWXnn8U47G5PQge2J7TuABqb+FaA0Nq3p5aCIYAAAp4LEFp7TsoOEfC3AKG1v88vpUtMgNA6MS/72hr4nTJxiny3YpXcf/M1csBeuye8szc/mC9PPT9PXnz1LenVM18qq6rlgL3HJTTswbvzP5YTz58sb896WIYO3rHlGC674TbZZ/fdTK9cHQKCJb5AMofW9qPXAPvW+x6SWfNeMWHzET86MG7hnvn3q1JVGZYn771FRg8fGnf9zlqhYvMW+enp58uKNevafIhJZ58uV06a0FmHwH47IEBo3QE0NvGtAKG1b08tBUMAAQQ8FyC09pyUHSLgbwFCa3+fX0qXmAChdWJe0WuHq2tk6r0Pyv2P/Usmjj9VfnfhOVLfUC/hcI1UVVdLdU2NmVCvpqZWGpsazeYNDY3y2tsfyOx5r8q60o1y5CE/kF+ecJQZAuH9BZ/K8eddIiceeZjcc+MfHB2c9p7Nzs6WGbdd52h9VmpbIFVCa6sEX3+7VG6b/rCUlpXHPa3aq/nmKyebyRWTYTHPi9ra5udHjYRrak3P76KC/G0aX5LhWDkGEUJragECrQKE1tQGBBBAAAGnAoTWTqVYDwEEjAChNRUBgVYBQmtvasOCT7+U31wzVZYsW+Fohzqe7/gTfianHP0TKSwo2Gabuf/5r5xz2dVy5knHyHGHH9Lu/srKN5mxrOfO/JsZv5rFnUCqhdbuSsvWCDgXILR2bsWa/hcgtPb/OaaECCCAgFcChNZeSbIfBAIiQGgdkBNNMR0JEFo7YnK8kvaUzg1lS15uruTk5Jjvodxs6RFj7N72dvrYsy+JDu8Ra8kL5UqPvFDkKxQyYfVtf7zM8TGyYtsChNbUDgRiCxBaUzMQaBUgtKY2IIAAAgg4FQh8aB0OV8vUO+6RrxctaTGbfPH5su/erWNrznpurjw9e475/6gRw+SKKRdJKJTr1Jj1EPCVAKG1r04nhXEpQGjtErATN//4y68lPT1d8kMhycsLSb4JqrefuK4TDyFwuya0Dtwpp8AOBQitHUKxWiAECK0DcZopJAIIIOCJQOBD67Lycnnsqdky4azTTRD9/ocLZfqDM+XKyyfJ8KFDzO8zn3hGrr9qivQuKpK77pth4CdNPMeTE8BOEEg1AULrVDtjHG9nChBad6Yu+041AULrVDtjHG9XCRBad5U0j5MKAoTWqXCWOEYEEEAgOQQCH1pHnwYNsa++8Q454xcnmd7WGlIPLCmRE4870qwaHWInx2nkKBDoOgFC666z5pGSX4DQOvnPEUfYdQKE1l1nzSOllgChdWqdL462cwUIrTvXl70jgAACfhIgtI46m4u/XSrT7n5AJl88QQaWDDBDh4wbO6YltLb/X3tisyAQNAFC66CdccrbngChNfUDgVYBQmtqAwKxBQitqRkItAoQWlMbEEAAAQScChBa26Ss8a2tkNr6/ajDD2sZ4zo6tNbAggWBIAnUNzRKZkZ6kIqcMmXNyMyQhvqGlDlePxyoPh8y0tMlLc0PpaEMCLgTqG9okoz0NJ4P7hjZ2ocCjY1N0iRinh8s3SOQkZEuDQ2N3fPgPOo2Ao1NTdLUxPOBahFsgcIC5lkJdg2g9E4FCK2bpayAurhPUct41dEhtq4aHVrXERA5rWus5xOBzVurJT8v20xwxpJcApGPwnwg7sqzsrWyWkKhbBNcsyAQdIHKcI3kZmVIRmZm0CkoPwLbCNTU1UtTQ6Pk5mYj020CkYYDlu4XqKutl7rGRsnj+dD9J4Mj6DaBrMyMbntsHhiBVBIgtBaRWIG1dRIZ0zqVqjPHagl8V14qTU1NMrR3X89RkmF4kC211VJRVSXl1VWSkZYmJQVF0jtEa7XnJ5sdxhVgeJC4RKwQIAGGBwnQyaaoCQkwPEhCXKzscwGGB/H5CaZ4CCCAgIcCgQ+tY/WmtvtGT7yoIbYukyae4+FpYFcItApoIPvGt1/Lqk0Vkp+dI3nZOdJTv3JzJSczW/KzsyUvK0fyc7KlICckn6xdKQtWLpMFq5bJ16XrZEVFWcvOdizsLQcPHSUHDB4u2r+kuq5OwvV15nt1fa1U19dLVa1+17/VSnVdvVQ31ElYf67X79a61t/qzd9HFveTPQYONl/Hjh7n2emrqquVtVs2yYbKrbJ+62bztXbLZllfuUU2NP++evOmmI+Xk5Ep/XoWyA49C2VAzwIZXNRHjhg5Vob0Lvbs+FJ5R3ouK+tqpaqmRirrasx531pbI5W1NeZ7lX7V1Yresmkt6WlppgdxZnq6ZKRlRL7bvvT3zPS0lv9p73trnayMDCnOy++UhpNkOg+E1sl0NjiW7hYgtO7uM8DjJ6sAoXWynhmOqzsECK27Q53HRAABBFJTIPChtQ738adb75KqcHibM3jgfnu3BNOznpsrT8+eY/4/asQwuWLKRRIK5abmGeeoO03g27INUlq1tcP7157Dj3/0vnyw8ruE9zGkqFjGlQySXfqVyPDifqKBoWaPH69ZIa8v+UoWrl4hoawsyc20fWVltfwtlJUtuRlZkpuVKblZ2RLKzJLsNm7v1g9emRlp8vn61fLR6hUm4NZ9j+5XIqP77SBj+u9gft6l74C45dDw9NnPPpL5q5bJwtXLTUBtXzScH9SrUAb2KpKdCnvLwIIi0SA+lJ3VspqGr+XhKqkIV8qmcFg2Vm01v39Tuk5WbiqX3XfYUcbvsb8ctctucY/HyxX08UcW9/dylwnv6/Vvv5ZXF30h/1nylZSFu2/8/Z2KestPhu8qOQkOGbBuyyZZVrFRvt24Qarq6mRAz16yQ0EvGZBfICW9iszvAwsKZdcBO0jP7O55TSa0TrhasoFN4O1li+Xj1StMI1JdY4PUNtRLfUOD1NTXS21jg/lZ/1anfzP/azS/1zY0SH1jvdTUN0id+b1RqupqzJ53LxkkBw8fbRosu/o1iNB6++q9oXKLeU/aXF0tjdI6nm5WeqbkZmaa18Vsff/Vn7Myu+21jCdm5woQWneuL3tPLQFC69Q6XxwtAggg0J0CgQ+tuxOfx/aHgAbC9733urz53TcxC6SBbqb2Us3QXqgZkpWhvVUzJDMt8rv+PSs93YTEI4oHyCHDdpGDhgyPuS8NMqxesVvraiRcWydD+/SVwtxQl2FGDw+iQ5F8vX6tfLp2lXy5frV8sW6NbK7ZthEo3sGN7T9Q9ttpqPQKhUwwPaiwyHwvcjnkx/srvpVnPpkvLy/6wgQ+uw0YJAcMHiYHDRkhew0aHO+wEv7/f5culhe+WChvfPeNbKoOi4a1Z+15oBy/6x4m2E9kWbd1s3yyeoWUVWsgXyWVNTXNveS37RGvAVasRRsANLTfd8ehcvCwUaLGOnaaNmhor3QNTPRnrXfZpg5GwhMvlzVbNsnyio2ypHSDaHCjPbm1R7/pwd9QH+ndb3r515u/1TRE/heuqzcBnPaY/17JjjK8Tz9zWDrkjZZJ9/n1hnVmW2sZ0ae/7Dd4qBw2YvQ2RchKy5D83BzJz86VnjmR714uyRJal+rdCZWbzeuDfdGQs6GpUXQSsPrGBmOov9c3Nppe9Q361dhovhpb1ov8vM16jdtOXpWblSU9snKkR06O5GVlS8+cXMnTv2XnNH/pXSHeWnt53rp6XxurKmXNlgrzHNDl0QXvydtLF5n6rq9LWjezMzIlU5+f6ZmS3fxczTLP1Qzz3HQ6bnpFdZX8Z/FXos8/fZ3TUe7TJV165eWZux/65feU4h49pX9+gRSFQi0/t2eid7joXTA5mRmijZw5mdromW2CVj3/2mi7oqJcPl29yjRqar3QBlD9vzaC5mgjaWa2aRjV18KcjGzzPaTbZ+d09enw5PH0vU/vbNIGyg1bt0h5VaV53df3P208LasKtzQkdOQB9ZznZGSZc69hdk66Nizr7/oa3vx3tc3IMH/X13JtfO6dl28aa/XLL4s+T+qbtBFHX7u0oUZfsxpMQ4++lunf9LtOsle3zXoN5rWtdb1G0wBkttV9mXUbzHNL32u08V8b9ztjIbTuDFX2maoChNapeuY4bgQQQKDrBQitu96cR/SRwPgn/y4LVi2XAwcPl1/tc5AJRP2+OBnTWgMODRb1g7sGrptrqk1AquGFFWSYXt9ZWaJho4YonblouPnhymUmJHp32RITMujj77vTzmaoFA3nrEUDVG0cqGmsk1r9br4aHIcPew7cScaV7GQCmW82rJVXFn9pwr3R/Vt7nut+t9bWmn1W1tSKDgkTa9HQrzAvJMWhHhLK0hAo0lNeg56c5h7xedkaBOnfNBjSXvIaPkfCw137l/g6OFy/dYtocKQ9sbW+LSpdJxXhsPHcWlNteje25arD6xjfUEhG9S2RvQcNlj12GGzCV/swKpVmGJVqM4yK/qzDqOj/t9SETUOC3iFR21gvVfV1srU6MvSKrqs9ZzWE3GOghkc7ydgBg0wQ2dFFgxctrzVkjg6Xow0B2jihDRxuF9Pb0zRkRBrQNDzV300DR/Pf7I+hzxNreBnj0tzLN/o4tNfvHgOHmGF61Mwa2ki/a+/4vOzW8FvrrAagqbBoWdY026/aVC7rTCNRhZRWbm55PdGBdvSc2Yds0teFAfm9ZFifvnLoiDFyyNCR0iu3c8bj/2rDWllRvlFKqyrNa7HWHQ3Py8OV5ng11LYv2vjZJ6+n9M3PN99LehbIsk1l8tGqZaKNIp256B0UgwuLZWTf/uY1zjSoaEOKaDgZaWjRhhfTmGI1uGhI2SQtDSy6TaMJMJsbXaz1ba/vXpVh7dbNsrKi3OxudN8SKcrLkx45uZKflR0Z0isnV3pkZ9sacSKNOWm2eXJr6xtMw1uNfmlPem240/ebhsh3HcLL/G7+rj3tm//fvI41nJe+n0T2s/37lAbXgwqKzN1K/Xv2kkHme0/ZsVdvE+RWVIWlvLrShMHmTitzN1akQcG81zhobG3vLjM9V8vKN5qvxaXrzeujnk8NircNnCPhsU7MZoLppsjdBt2x6PXcOBeBvzYMVlSHZVN1lZRXVZmh2UyDVFq6aCNUj2xtYNCv1sYHfc3V19pII/K2P+t50ddis755nW7eVveRkZEyr5nR51IboL9Yt9rcBaZW2pgQb9HrSK3DOvybNmZ3VgNDvOPoyP+/3LBG3lu2xHQQ0Ou6olAPc0ek3q2oz21trDeN+vpcNkP5NTfw24b109eK4h4FMqxPsegdlkeMGtuRQ0mKbQitk+I0cBAIIIBASggQWqfEaeIgk1FAP6gd/Y+/yszTJnRKr91kLLMek5PQOlmP3Tou/ZCkHx40xF6xqXUMcO2NqCGw+dIAOEuDzRwJafigv2svUv0gr9/N79mSl2mtnxWzx6A+1ryvPpWycGULi37w0v1aIYd9vHINNnTc8p45Xdd7PtnPl5vj0+Bji47bXR0Js3WYkS3aG9L8TYPtSvlkzUpZuCYy1E2sRT8YawClYVS+jiefGwlX9VxlNqVLYY88yc+J3atYw8IFK5fLoo3r3BTDbNsrN/JBt3denhTm5pk7EbRXpd6hUBjqIUW5IdPD1VrSmtIkq7knvQYh2mNXQxN773onoZTTAzeBfU2tCaa00UAD0o9WLZf5q5aaxj2nizby5OdYPbb1e+R5aMxzcsxY/vrc03ORp+tlZUtBbq4J27QxokdWrvTIyU54mAW9M2P+ymWmkcIaz98ECM3zANgbt7QRzFrMnSE9C03P5ZKCwm16RPfJyzeBoTbMaQjcWQG1U9vo9TR81zkEyqqqZEPlZhNOl1VVmoBbfy4M5ZlGl2HFzib1rQzXSk5WhmTGaKDRME8bOKy5FWp13oT6OtPAExniKfKlQWe6GStf70pKk3TzPV3SdIx9628SGW9fJ+LVsfT177pNZN3IOPv6P2sMfmt8/pbvYq1n3y5drP9npInZlwaNac2Po/uy9q93T5UURELgZFu0Ye3r0vWytLxUlpdvFG1UWbs10lNeG1YSXTRMjfSsjzQ0awOpPv+0ftgbZNrarw7xtVNhH9MgoQ2FEcc0M/+B8Ww+v63nvHnuhDRpOY96DlrWT49sq/XB60UbA/WOAX3fMD23tSd2850o1h0pkZ7d2pAS+Z/VUKL/t7aJdVza6CJNIulauZoXDWqtxgd9nTF3HDU3QiRaNj0/1h1T2htfh5yJBOGRO6rMz82v/5Gf9e+RdfSaRK+FlpeXmfcqq8FAr4HMHYJqnqHfMyRD7xpsnuPCuntQ99+/R4G58294cX9zR4/efRBpZN1k5iXRBjxtLNP3B2vRhste2jCfl2/OabxFvb4pXW/eq3XbUf22H4JNr+N0CDltGNW7f7SjhL5/WHcHad3VOmxd61nv7/r+oe/p+r+6xnpZtGG9fFexUdZurmiZ2yNi0Wxg3k8jd03q3ZIZ+nPz3ZTqp50jlpWVmte4T9askLbmY9HnRGRoviwJmTtQIu/R7S3aQPVN6do2G3ZM2dVAr10z9X0ycq2aa35vvYa1P44+J627O0x9aa4z5u685qEFIz9bQxpFXhe0rnVkeLZUD62XlpWaa0q9U4oFAQQQQKBzBQitO9eXvftYQMcJvujZx+SLS2/wcSm3L5ofQutAnTAK61hAe6bqh00NPk2PYAeNB4kOD6KBkoafdbbehnpLu/YsND0PTW/DJmloaDBhnPYEtwJqxwVJ0hV1aAxtNAhrT/R67bUeCYS31FSbnqIaaIZ12KO6OtlqhsPRdSI9z9TNrKOheH2NVNdqOB6ZILa9RYMcDbUj4bbVu1uD7Ugwrg0RGqbo2P8apuzaf6D0DuU1D2dhD+oiwXiv5saB4h75UtKzUPQ7S6sAY1onf23QOzS0l719eKW2jlp7gmojgwlUt5mcudY0omlIqYF0Sc9eyV/wbj7CjgwPoo1KOmG2mTy7ITIxtgaWkYmya6VW/6a98G3/Nw1utsY2HYrL6sVvTcCt+6ppGZYrEpTr3Q72xoVEuOxDd2monC5ppqGuX36B+a7zT5jfe/SUvvpzj57m8Tq66N0j2mCyuTpsHPTuJ+2lrO8xZtLpWn0faf3dvI/oBNTNk5BH3msiTp219MnrYRop+/boKQftPNzM66FDxnm56HnTMpvy1OtdXnou9U6wSPkjjYQRB/Oeav4WGWpOv+uwOvZFe3tH7vyob77TMHIXSLz32bbKpA0iZjjEdL3LYNshEjMkMpG3NpxEhk9s/r8ZNjHDNBRoA4HZVv9n/hYZYlEbTTRA11B+RHF/M+fN0N5tN6xad38u2bjeNJDqubfmjzBzRNQ3SK1eg9VH5o/Qu+fMnXjm7qN8c22gd7VpQ8zKTWXmTgr7oneUHTJ8tKM7NKzOBDqskxmiL735zjbTSKAGkSG0NBC37oRxWk+H9+lvrl9Y3Alo453ewdiU1joxvTY66rW73ilk3fGlr3uRYfasIfVkmzvB9H9Nzdu0rhPZRhs79fuF+x/i7mDZGoGACBBaB+REU0zvBR6e/4488fH7Mu+cyd7vPIn3SGidxCeHQ+tygURD6y4/wAA8oH4AjYQVkQ/nGkzoB3cr+DYf6Gsjt1vrkC7Wuhp0hGsjE8nqxIWHDB3lehz9AHC3W0RC66DG+imcAAAcvUlEQVTXAMrflkBHQms0O19AG0Sr6uvNe0FVfWSuGO31r0PXeXknUueXpPMfQd87dRJgDbZN0NtoDVmkje3bDuej4a81Bn2sceVrNFCvb5CMzDTTWK93Keg2ZjvbuPRWQ74G7C3j2DePba/h/BfrVzsuuE7k3r8DwxHqXV7aeaAwT+9w6xH5yg1JQSjPNKjr3Eafrl1pGgtMw1LU/CyOD9CDFbVh5Hv9B8mJu+1l6rEuZkiaUOROva6cA8mD4nTqLvSO6Y/XrDR3JJk7I8o3mvk54i16d0bkLqG0yB1g5u6u1ru+9HcdC8zcRaR3gTX/bN1NpP/WTinaIPPIaRPiPRz/RwABESG0phog0EGB61+ZY267nX7SmR3cQ2puRmidmueNo+4cAULrznFlr6kpQGidmueNo+58AULrzjfmEVJHwMvhQbQn9erNFWYOhFiLDj/TXk/srlDTuyYi45bXSbiheUL15qHH9A6IsLmjonX4LA2Yh+rY5YXFjuf90fB84erlsmDVMlnW3FtYJwaOXjS41v3r0HKbq6vNmPI6nJv2jDdDyuik5c0TbZs71ZqHRNS/a3iv4b+OK68NO15P4N4Z50KHp9OGEF00cP5i3RqZ9el8+WzdKvM3HQZpdL8B5k670f13MD+PKm6dh6gzjol9IoBAYgKE1ol5sTYCLQIT/vWQmVzsqkOPDpQKoXWgTjeFjSNAaE0VQaBVgNCa2oBAbAFCa2oGAq0CXobWuLYvoJOe6twV67duknVbtrRM4l0e3ioD8gtkQEFhmzuITEIemYi8srZaNtdUyzcb1juenD7eudGh+HrnRYZh0UXH+I+E+pHJSTXs10UbHXQYGB0ORodVibdouP7u8iXyzrLF2439rkO//Gz0bvLjEWPMfCT6WZ4FAQSSW4DQOrnPD0eXxAI/feAOOXPPA2T8nvsl8VF6f2iE1t6bssfUFSC0Tt1zx5F7L0Bo7b0pe/SHAKG1P84jpfBGgNDaG8fu2ov2zF5eUbbdsDCJHI/OmaCBuk5YqhPA6hjRZg6XvB5mUtToRSfKXV5RLtoz3QxP0zz+uA4hY8Ymb9AhZurNWPU6mf0hQ0fKocNHm2FdrEXHUt9r0OBEDpN1EUAgCQQIrZPgJHAIqSegEyrsdsc1cu/x4+XgYaNSrwAujpjQ2gUem/pOgNDad6eUArkQILR2gcemvhYgtPb16aVwCQoQWicIxuoIIIBAgAUIrQN88il6xwW+KyuVn/3jTplz9m9kWJ+2Z6zu+CMk75aE1sl7bjiyrhcgtO56cx4xeQUIrZP33HBk3StAaN29/jx6cgkQWifX+eBoEEAAgWQWILRO5rPDsSWtwJvffiMTZ8+UT6dcZ2YGDtJCaB2ks01Z4wkQWscT4v9BEiC0DtLZpqyJCBBaJ6LFun4XILT2+xmmfAgggIB3AoTW3lmypwAJzFzwnjw8/2155bxLA1TqSFEJrQN3yilwOwKE1lQPBFoFCK2pDQjEFiC0pmYg0CpAaE1tQAABBBBwKkBo7VSK9RCwCdz02guyZGOpzDjl7MC5EFoH7pRTYEJr6gACjgQIrR0xsVIABQitA3jSKXKbAoTWVA4EEEAAAacChNZOpVgPAZvAr2c9IiU9C+XanxwbOBdC68CdcgpMaE0dQMCRAKG1IyZWCqAAoXUATzpFJrSmDiCAAAIIuBYgtHZNyA6CKHDkjGlyym77yDn7HBS44hNaB+6UU2BCa+oAAo4ECK0dMbFSAAUIrQN40ikyoTV1AAEEEEDAtQChtWtCdhA0gYamRhk37VqZdszP5ScjxgSt+IxpHbgzToHbE2BMa+oHAq0ChNbUBgRiCxBaUzMQaBVgeBBqAwIIIICAUwFCa6dSrIdAs8CKijI5/MFpMvvMi2VU3/6Bc6GndeBOOQVuR4DQmuqBAKE1dQCBeAKE1vGE+H+QBAitg3S2KSsCCCDgToDQ2p0fWwdQ4O2li+S8Zx6Rjy65RnIyMwMnQGgduFNOgQmtqQMIOBKgp7UjJlYKoAChdQBPOkVuU4DQmsqBAAIIIOBUgNDaqRTrIdAs8PjC92X6e2/KGxMvD6QJoXUgTzuFbkOAntZUDQRaBQitqQ0IxBYgtKZmINAqQGhNbUAAAQQQcCpAaO1UivUQaBa4+fWX5PN1a+SR084NpAmhdSBPO4UmtKYOIBBXgNA6LhErBFSA0DqgJ55ixxQgtKZiIIAAAgg4FSC0dirFegg0C1w4+1HpnddDbjz8hECaEFoH8rRTaEJr6gACcQUIreMSsUJABQitA3riKTahNXUAAQQQQMCVAKG1Kz42DqLAMQ/9VY4Zvbucv+8Pg1h8IbQO5Gmn0ITW1AEE4goQWsclYoWAChBaB/TEU2xCa+oAAggggIArAUJrB3yznpsrT8+eY9YcNWKYXDHlIgmFch1sySp+FBh7x9Vy29GnyhEjx/qxeHHLRGgdl4gVAiTAmNYBOtkUNa4AoXVcIlYIqAChdUBPPMUmtKYOIIAAAgi4EiC0jsP3/ocLZeYTz8j1V02R3kVFctd9M8wWkyae4wqejVNTYM2WCjns/tvlmfEXyuj+JalZCJdHTWjtEpDNfSVAaO2r00lhXAoQWrsEZHPfChBa+/bUUrAOCDCmdQfQ2AQBBBAIqAChdZwTryH1wJISOfG4I82a0SH2mU89ENCqE8xiV9bWypfr18iHk66SvOycQCIQWgfytFPoNgQIrakaCLQKEFpTGxCILUBoTc1AoFWA0JragAACCCDgVIDQuh2pcLhapt5xj4wbO6YltF787VKZdvcDMvniCTJ86BCZ9ubLTq1ZzycC2RmZ8qs9D/RJaRIvhn7wys3OlLS0tMQ3ZgsEfCZQXVMn2dmZks7zwWdnluJ0RKC6tl6yMtMlIz29I5uzDQK+FahraJCmxibJzsr0bRkpGAJOBeobGqShsUlyeD44JWM9HwrkhbJ9WCqKhID3AoTWDkLrow4/TPbde3ezZnRoXVq+1fuzwh4RQAABBBBAAAEEEEAAAQQQQAABBHwnUFyU77syUSAEOkOA0NpBaN1eT+uqcG1nnBf2iUDSCtDTOmlPDQfWDQL0tO4GdB4yaQXoaZ20p4YD62YBelp38wng4ZNKgJ7WSXU6OJhuEqCndTfB87ApJ0BoHeeUxRvTOuXOOAeMgEsBxrR2CcjmvhJgTGtfnU4K41KAMa1dArK5bwUY09q3p5aCdUCAMa07gMYmCCCAQEAFCK3jnPjoiRc1xNZl0sRzAlplKHbQBQitg14DKL9dgNCa+oBAqwChNbUBgdgChNbUDARaBQitqQ0IIIAAAk4FCK0dSM16bq48PXuOWXPUiGFyxZSLJBTKdbAlqyDgPwFCa/+dU0rUcQFC647bsaX/BAit/XdOKZE3AoTW3jiyF38IEFr74zxSCgQQQKArBAitu0KZx0AAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBwJEBo7YiJlRBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQS6QoDQuiuUeQwEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABRwKE1o6YWAkBBBBAAAEEEAiWQDhcLVPvuEfGjR0jJx53ZLAKT2kRQAABBBBAAAEEEECgWwV8GVov/nap/OnWu6QqHO60iRPvum+GvP3ehy0n79QTjtnmA937Hy6UaXffb/5f3KePXH/VFOldVGR+t/9Pf4+e3DF635MvPl/23Xv3bq0oPHjyClihwsayim3qWVl5uVx94x3mwO31z01JrMf6etGSlt1E18/2Ji5t73ljHW/pxo0xnzdujpttgyNg1b/oemnVPa9fT3lOBKdu+aGk9uuPA/fbWyZNPKfdYsULrZ3U//auh+JdS3E95Idal9xliK5jeaGQXHn5JBk+dIinBx7v2j/6uWT/XGH/XBPrc0X0/5k03tNTF5idWddP9vcGvTafevs9cv454z19Tjh57+DzRGCqHgVFAAEE2hXwZWhtlVgvEF/696tyxZSLJBTK9awq6BvtAw8/Lr887QQTRFsXi78+9wwTLuvv0+5+QCZfPMG8weub7seffdFyHPr7wIElZl3rTbu4T5H58KgXB489NVsmnHW6OebofXlWCHbkGwGrDlWFq2T/ffZuaTzRevbu/30o4XCtZ6F1dP3U59j0B2e2fMDT32c+8UzL4+mHQV20bsd73ui2q1at2eb47c8b35wwCtKpAlrvX33jbdlxxxK5ZOK5La+j02fMlI0bK8R6nfbqIHhOeCXJfrpSQJ8nq9ascR1ax6v/7V0PaXnbu5bieqgra0QwHyv6+lwVoq9FvJJp79pfH8N+vWQ14p/xi5PMZ4XoY9J1SzeWx/xcEb0vr46f/fhfwHo+hMPhlpC6s0LreO8dfJ7wf32jhAgggIBTgUCF1vYWWwWy97jTC8DKcFjCVdWivUgT6WkR3RMp+sNgvOA51kWzdQKjL1ydnljWC46AVf/2//6e8u4HC+SSCyM95+68d4bo316Y91pLiBzdG8femyL6ORB990As0ej6qfsYWFLSEjxHX3Ta9xGvB1972wbn7FLSRAWs11/d7vt772k+8Gu9HDFsZ/NcsEKAtp4LsV5z472G24+R50SiZ4z1u0PAfp0SXb+t1+ajDj9MvrfrLgkNDxJd/xO5Hor3nsD1UHfUFP8+Zrz6ZpW8rTsFrOfN/vvuKS/MfcWs7uTuBWu/9mv/cHV4u96s9hA7+izEuz5q73OFf88oJXMrYL1e63W81agZHVpH3xVpfZaOdZ0Ur55y7eT2jLE9AgggEAyBwITWejqfef4lOenYo0zPO31jfu3Nd7bpEfrRx5+39BhN5IIvVkihj2fddhvvg1a8C1N7T9ZgVEtKmYiAPWDQnsq6aE9+/Vm/23s+z3v5PzJ82M7mDoDoOwS0HtqfA06OwX6ROrBkwHbhRnthn5Pnhb0nkZPjYR0ErA9dR/70UPnXcy/KGaedJLOef0lOPPYo+fPt97SE1u09F6KDtvZeo6PFeU5QB1NBoLNC6+jX/OjnTnuv+/HeE6Lv7EkFZ44xuQXiXfdE17no540ORbjHuF1b7pTUIdmshtF4Jbc/N2JdK7X3OaS9/0XfwRnvOPg/ApaAVb/1TmJrSJDeRb1afo6+zo/1OcLecSW6I0t70lw7UQ8RQAABBNoSCExoHT08SLwPVokMLRL9oSz6Tbq9D2JttULbewF6PQYrTwd/CdhD6xHDBpuLy1AoZHpcL1qybJvQ2l7y6F5GiQRzup/o7e3HYY3B3l5o3dbjWXdERI8F76+zRmk6S8AeKmgdW75ylZx8/DGiz422AoXoumzvWWT/wBZvjFOeE511Vtmv1wKdEVrH6rmayPVQW+8JXA95ffbZn10gekxr+3jQ0XVS6+L9Mx6VKy69SMrKN20zFKDu0+l1VPS1v32/1vw3bQXT8a6rdL4dxrSmjndEwP6+ECvA1n3ah7+MrvP2z86x7h5o65i4durI2WIbBBBAIDgCgQqto28Htw8BEn2h6TS0jh5XLtZFa1uhtZNeQ/F6HgWnqlLSeBd7eiu3NRSC1dMh+oNRrIlPrGFAnH7YsgfW1ljssUJs/VtbH65iPW+iy5fIbYXUDgQsAfuHrugPUPbQur3ngvU6rs8jvVvBydwIsXq3xQrxeE5QV5NBwOvQuq3enU57Wjt5T+B6KBlqjr+Pwapjo0bsbHpPRwfaWnqrQT1WaO1krPhY1/5Oe1pH92xt62wkcreov88opUtEwF5/rcb7k44/Wp559gUzxrUuVqONvXEl1lAiOjk8106J6LMuAggggEBbAoEJrVetWSt6G19bkyV2JLRu60OWkzEcnQTW1klL5PYqqnrwBGL1cLYU7MFvKDdkhu+wguaO9rRu79ZTJ2NaOwkn9Pg7a/KX4NWQYJW4rdDAHnhZ4/S29VywN7joz2eefrJpEGpr4TkRrDrmh9J6GVq3V/+dXA85fU+wNyadeNyRfjgNlCEJBeyBr04Uah/uwH64sYLmeI3/bV37x7reidXL2/45pj26WD23k5CaQ0oygejXa+u5YE3MqIfbXk9r+2u0BtnWvCJcOyXZieZwEEAAgRQT8HVo3d54cdEXjomG1u1dmEZfyEb3eGivB6lu+/qb78qEs39hqpLTXhUpVu84XA8FEg2tx40dYyZKtEK8Q394gPk93octPeR4Exe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   ],
   "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)"
   ]
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   "execution_count": 106,
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    "# #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"
   ]
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QIEBgBQJC6xWguYQAAQIECBAgQIAAAQIECBAgQIAAAQIEmhEQWjfjalQCBAgQIECAAAECBAgQIECAAAECBAgQWIGA0HoFaC4hQIAAAQIECBAgQIAAAQIECBAgQIAAgWYEhNbNuBqVAAECBAgQIECAAAECBAgQIECAAAECBFYgILReAZpLCBAgQIAAAQIECBAgQIAAAQIECBAgQKAZAaF1M65GJUCAAAECBAgQIECAAAECBAgQIECAAIEVCAitV4DmEgIECBAgQIAAAQIECBAgQIAAAQIECBBoRkBo3YyrUQkQIECAAAECBAgQIECAAAECBAgQIEBgBQJC6xWguYQAAQIECBAgQIAAAQIECBAgQIAAAQIEmhEQWjfjalQCBAgQIECAAAECBAgQIECAAAECBAgQWIGA0HoFaC4hQIAAAQIECBAgQIAAAQIECBAgQIAAgWYEhNbNuBqVAAECBAgQIECAAAECBAgQIECAAAECBFYgILReAZpLCBAgQIAAAQIECBAgQIAAAQIECBAgQKAZAaF1M65GJUCAAAECBAgQIECAAAECBAgQIECAAIEVCAitV4DmEgIECBAgQIAAAQIECBAgQIAAAQIECBBoRkBo3YyrUQkQIECAAAECBAgQIECAAAECBAgQIEBgBQJC6xWguYQAAQIECBAgQIAAAQIECBAgQIAAAQIEmhEQWjfjalQCBAgQIECAAAECBAgQIECAAAECBAgQWIGA0HoFaC4hQIAAAQIECBAgQIAAAQIECBAgQIAAgWYEhNbNuBqVAAECBAgQIECAAAECBAgQIECAAAECBFYgILReAZpLCBAgQIAAAQIECBAgQIAAAQIECBAgQKAZAaF1M65GJUCAAAECBAgQIECAAAECBAgQIECAAIEVCAitV4DmEgIECBAgQIAAAQIECBAgQIAAAQIECBBoRkBo3YyrUQkQIECAAAECBAgQIECAAAECBAgQIEBgBQJC6xWguYQAAQIECBAgQIAAAQIECBAgQIAAAQIEmhEQWjfjalQCBAgQIECAAAECBAgQIECAAAECBAgQWIGA0HoFaC4hQIAAAQIECBAgQIAAAQIECBAgQIAAgWYEhNbNuBqVAAECBAgQIECAAAECBAgQIECAAAECBFYgILReAZpLCPRV4O9/vDc945kHpmcedGBfCaybAAECnRZ4dPeP06Hrn93pNVocAQIE+irw5E9+ln7y05+l5zxrXV8JrJsAAQIEZkhAaD1DzTJVAtMWEFpPuwPuT4AAgWYFhNbN+hqdAAEC0xQQWk9T370JECBAoK6A0LqumHoCPRYQWve4+ZZOgEAvBITWvWizRRIg0FMBoXVPG2/ZBAgQmFEBofWMNs60CUxDQGg9DXX3JECAwOQEhNaTs3YnAgQITFpAaD1pcfcjQIAAgdUICK1Xo+daAj0TEFr3rOGWS4BA7wSE1r1ruQUTINAjAaF1j5ptqQQIEOiAgNC6A020BAKTEhBaT0rafQgQIDAdAaH1dNzdlQABApMQEFpPQtk9CBAgQGBcAkLrcUkah0APBITWPWiyJRIg0GsBoXWv22/xBAh0XEBo3fEGWx4BAgQ6JiC07lhDLYdAkwJC6yZ1jU2AAIHpCwitp98DMyBAgEBTAkLrpmSNS4AAAQJNCAitm1A1JoGOCgitO9pYyyJAgMAvBITWHgUCBAh0V0Bo3d3eWtnsCOz7759K+/7+P8cnfNA/Tmuef15ac8Cz49eoJNARgd6G1t/efn+6/KrrFtp49JYj04UXnJ3m5tal+fm96ZLLrk67Hns8XXzRBWnD+vWDusd2704f+/hlg/9dfn9HngXLILCsgNB6WSIFBAgQmGkBofVMt8/kCRAgsKSA0NoDQmD6Avv+6n9N+575T9OatQfHJvPEd1PafG5a84x/EqtXNXMCRQaZJ17kkkst4sprtqYHdjzci1yyt6H1bXdsS5s3b0qvOeaVCyH1oRvXp3PPOm3h73vm96TX/dox6aQTjh88L/mab/3Z9jQ//5NePBwz95luwo0LCK0bJ3YDAgQITFVAaD1Vfjcn8A8Cj38t7dv3JBECYxV46qmnU/7/ZzzjwLGOazACWWDNc16X0oHPhbGMwCRD62Lj5aO7di3M6pQT37WQceV3PviDH6ZPfPLKtGd+fqHm/HPOHGRlOQO75fY7U/H3oiCHpvfet32/91eXPuz+5Zo8l5zLlTeUFh8v5jlsjPKm01HcxRyLj1evKcbduOGQRUFxESA/sOOhhaGPfe0xg6wwvxUm1ftmo507H0nf+e73F41X3Oe41//6Ivfy9XnMnY88snCP4mPVe5X7kNe3edOmkWN25ROxt6F1tYH5YSgervyxvNP6da9+VfrWn/55Ou93f/5wXvEHWwfvu+vue4TWXfkMsI5aAkLrWlyKCRAgMHMCQuuZa5kJd1Bg3/93b0q77k77DvhHHVydJU1TYN++fenpffvSAWvXTnMa7t1FgX17U1r7rLT2sAu6uLqxrmkaofWp7z15EEJXA9TiBIJyGJprbvrj29MZH3xf2valr6Wv/sm96bDDNqXzzjp9cDJBDrmv3Xpj2rXr8fSh008djBt5K+5dzKW4Js/hxptvHZqxFQHyK37lJYvC2es/dXN6w+tfl4464oX73XrUruXyxtV8Ub7vF7741TQ/P5/OPO0DC2NV71n8vdjkWs4Os0f1rRom57/ntyL0rtZnl0suvXrRHHLNsN3UN91yezr+LW8YnAaRr8sZZc4ri9MhIn2YtRqh9S86Vn6QiofyHW970+AnJfkt//Qn/+/856hPqFlrvvkSqCsgtK4rpp4AAQKzJSC0nq1+mW03BXJove/x/5jWrHtBNxdoVVMTeOrpfempp59OzzjwgKnNwY07KvCzx9O+p3+S1j7/X3Z0geNb1jRD67yKYldvDqXzZs1qIFxeaVGb3/fqY141CKhzdrblyMMHmzmrAfRSSisJrXNAfvlV16fzzzljaEA97H5LheDl+ryOvKY/3f7ni3YsDwvKi4A7H92Rg/zqburyuOUQOr//uq2fThd++OyRwXJ57CIEz+te7ro8drGG6A8OxvcUT24kofUvfsJSDqLLofWWI18w+KnH3Nzc4CcYOx76q0Wh9d8/sXdy3XInAlMW+OnPnkpr165NB6xdM+WZ9O/2BxxwQHrqqaf6t3ArJkBgogI/+Un+tXE78CaK7mYEKgIH7vl2OuiJb6WnnnFYZ23Wrlkz2PHrbbICmTzvtl7re/nJwvfgbmue+ru05umfpL2HntW61T7nWfvvhp3mJKcdWhcbNo9/63HLBsJFaJ1rP3vH59Op7zk53fa5L6STfusd6f+49OrGQ+tRR3gs1b/ldjbna8u7lHPGl3dcV1/jrhzml3dXLxda5/FzEH3rf7hrMM2Tf/udS+5Gz2Pnt+JY4siRLsX6Rx0rMs3ne9z37n1onR+ma2+4MX30I+fu9+sAead18ZOk4qyY6k9t8otZeCPQF4G9e3+aDjxobTrwALszJt3zNWvWDP4jwxsBAgSaFHjiiSfTs571zCZvYWwCBJYRWPvjb6W1f39v2vdMO609LOMVePrpp1P+dvKAA/xwcryyRlvz1M93Wj/1T85uHcYzW3aG+zRD6+L86nysRz7LebndvOVQNIfBf/2jnendv/2ulDd3fuzjl40ttK57pnX1XO7yQxc56znnenmHdT6yo7oDvLrTunqkylJnWpd3PEfC8zzvYbulo2F0eR2t+8Qb04R6HVoPC6yza3mndXWbffRXDcbUH8MQaJWA40Fa1Q6TIUCAwNgFHA8ydlIDEqgt4HiQ2mQuCAo4HiQIpay+gONBwmbTCK3LL8RYnF8dOXqjHJ6Wj7GY3zs/1tC6zhG8w87hrobW+e+jzpAelvcNOy64/EKM5ZB8uTOt873zHP/oM58dnJe93Lnf1dC6utN6qRedFFqHP+1mrzBy2Hux07q8OqH17PXajMcnILQen6WRCBAg0EYBoXUbu2JOfRMQWvet45Nbr9B6cta9u5PQOtzyaYTWw86eHvUih+WFjNrxO+p86qUQVnKm9bDxlpv3cpldsdt8z/z8ouEP3bhx8GKQc+vmljzre7nQunym9a7HHl/2NfGqx4PkSUXPtBZahz/tZq8w/zTj3vu2L5r4wXNzg2NCNm963uAhFVrPXl/NuFkBoXWzvkYnQIDAtAWE1tPugPsTSElo7SloSkBo3ZSscZPQOvwQtCW0zhMetms5h643/fHtKb9QYz6/eecjj+y3a3lSoXUOb/NZ2ueddXoqv0jhUi/OWITaeX3FOdX5f+dwePPmTWnnzkf2eyHF8u7rl7/0RasKravHkyx3TMiwF2LM883XPbDj4UGQvmH9+sHzddMtt6fj3/KGhb97Icbwp51CAgT6ICC07kOXrZEAgT4LCK373H1rb4uA0LotnejePITW3etpa1YktA63ok2hdZ70sJ3HxREik9ppPepM6+Pf+sZBgFw+qqPYbHrUES9c0ry6UTUfs/Gv/sXp6d/82xtS+UUWi0GKteawPt9zWE0Rft9y+5373TubDQvEq2diVy8s78yurql6fnbRlzxG+cUki1A7/BDOUGGvz7SeoT6ZKoFWCAitW9EGkyBAgEBjAkLrxmgNTCAsILQOUymsKSC0rgmmPC4gtA5bTTK0Dk9K4VQFoi+8WJ5k5AUnp7qoMd1caD0mSMMQ6IOA0LoPXbZGAgT6LCC07nP3rb0tAkLrtnSie/MQWnevp61ZkdA63Ip9//1Tad/f/3lKaU3smoP+cVrz/PPSmgOeHaufcFV1N3D59tFd0ROecutuN+pIk1ETHXZ0SOsWNaYJCa3HBGkYAn0QEFr3ocvWSIBAnwWE1n3uvrW3RUBo3ZZOdG8eQuvu9bQ1KxJat6YVJkKgSwJC6y5101oINCwgtG4Y2PAECBCYsoDQesoNcHsCyQsxegiaExBaN2fb+5GF1r1/BAAQaEJAaN2EqjEJdFRAaN3RxloWAQIEfiEgtPYoEJi+gJ3W0+9BV2cgtO5qZ1uwLqF1C5pgCgS6JyC07l5PrYhAYwJC68ZoDUyAAIFWCAitW9EGk+i5gNC65w9Ag8sXWjeI2/ehhdZ9fwKsn0AjAkLrRlgNSqCbAkLrbvbVqggQIFAICK09CwSmLyC0nn4PujoDoXVXO9uCdQmtW9AEUyDQPQGhdfd6akUEGhMQWjdGa2ACBAi0QkBo3Yo2mETPBYTWPX8AGly+0LpB3L4PLbTu+xNg/QQaERBaN8JqUALdFBBad7OvVkWAAIFCQGjtWSAwfQGh9fR70NUZCK272tkWrEtoHW7C45/8/bT3G18L1x/4/MPShkuuSGufe0j4GoUEuiIgtO5KJ62DwAQEhNYTQHYLAgQITFFAaD1FfLcm8AsBobVHoSkBoXVTssZNQuvwQ/A/Tn9vOmjLi9KaZz87dM2Tf/rNtOF/vzwdeNg/DdUrIrBagQd/8MP0iU9emd759jenk044fsnhHtu9O33s45elo7ccns4967TV3nq/64XWYyc1IIHuCgitu9tbKyNAgEAWEFp7DghMX0BoPf0edHUGQuuudrYF6xJah5swydC6CBRPfe/J6TXHvHJhjldes3Xwv1cTMo4aOwwx4cLb7tiWbrn9zoW7HrpxY7r4ogvShvXrF7nce9/2hb8fveXIdOEFZ6f5vfODYHbjhkMGf5+bWzeoKcLdw57/S4veX13a/PzedMllV6cHdjy08KFjX3vMIv9vb78/XX7VdemUE9+1KCgunB/dtWvh2qJm2Li5KK/to793drp2603pFb/ykkXj5ftce8ON6aMfOTcddcQL9+tCMeY73vamRc9M9V5lvzzHSy69Op152geGjrmaVgutV6PnWgI9ExBa96zhlkuAQO8EhNa9a7kFt1BAaN3CpnRkSkLrjjSyjcsQWoe7IrQOU421MIfW3/nu9xfC5fz3e77xzUFwPbdubhAq57dyKJ1rNm/elLYc+YJBKPvEnr3pd95vIYcKAAAgAElEQVT37oUwN4f/f/2jnenguYNHhtajdiJf/6mb0xte/7qFkLf4QcKju3YvGqv6w4Hi78e9/tfT8W9942De1WC6gKuGyZEfNORQ+wtf/OrQOZR3U+extn356+n9p5w4uF2+7k+3//mqfhAyrOFC67F+GhiMQLcFhNbd7q/VESBAQGjtGSAwfQGh9fR70NUZCK272tkWrEtoHW5CG0Pr6m7e8885c1EwW+w+PnhubmGHbg5Zy7uS8+7fl7/sxenyq65Pr3vNq9Jd274yMCnvKK7u8C4HpDsf+dvBtYcdtind/53vLVz76mNeNdiBXB2rCKHnDl63UF+ed7Uh1dC6HOjueuzxdOPNt+6387oa/h73G8em+7/7/XTeWaenPN/P3vH59Pxf2pR2PPjwyNC6et9hD0qeyxV/sDX9zvtOTtfe8OlFO5aHBc15zJ2PPJLO+OD7lgytizC5CKG3felrg+uW2mGfe7R506ZFu7OL+y11XbGG8373tEW718OfGCMKhdarFXQ9gR4JCK171GxLJUCglwJC61623aJbJiC0bllDOjQdoXWHmtm2pQitwx1pW2hd3rmbzy/OR15ct/XT6cIPnz1YU3k3bQ40i53AxZEZ5aNHiuMyfvUVLx0Eo9XAdbnQunyOcnWs/Pccap9/zhmD3cnFcR9FUJ0D8KWC52p4XB5v25fuGax1VChbDrhzbQ7Sd+58ZLALO/9Z3sFdfhCKIzVG7YQuasu7lKuh8bDQunCMhNb5Hrn+ifn59Fjexf3hs0eGynm+V1xzQ3r3Cb+5sAO8OLakmGv5BxfD1lo9ViT8iSG0Xi2V6wkQEFp7BggQINBtAaF1t/trdbMhILSejT7N4iyF1rPYtRmZs9A63KhphNbl85CLiRY7oKth76gzjfN15dr893zOczW0LgfLRWBaBMLLhdbla0cdi1Hcb9jO6ep8yk2p1pcD+Ov/8DP77S4uX1sOrfP7r916Y9q4ccNgx3XevbxcaL1ckJvnkoPwfO54tR9VhyLM/9Dpp6aXv/RF+52VnedXPa87cixIvm7YbumlnofqQ19eR/gTYplCO63HJWkcAj0QEFr3oMmWSIBArwWE1r1uv8W3REBo3ZJGdHAaQusONrUtSxJahzsxjdB6qRdirO6kLRZS3sFcHM9RDkSjoXX5aIkmQ+vlwtXqCzEWL7KYX1RxuRemLIfWmzc9bxAUF0H0Usd/RHZal3e25xeFHBXWl3/wUPQmMn7xg4N89vb8/E9GHoEyKrSuPh/VF4osP/hC6/CXAYUECDQhILRuQtWYBAgQaI+A0Lo9vTCT/goIrfvb+6ZXLrRuWrjH4wutw81vY2hdfeG9YjE5sLz2hhsXzrHu0k7rcsOWO1qk+oKG5WuXO7M68vFbbr9zv+en2Am/1C7pSGhdPjc87yjPb6OOQRl2PEiuj5xpXYTjxY7x8CfEMoV2Wo9L0jgEeiAgtO5Bky2RAIFeCwite91+i2+JgNC6JY3o4DSE1h1saluWJLQOd6JtoXX1TOu8kBx0Fm/lc6JzeHnPN7452K07t25uvxcBrJ47Pewc6uIojTx+3rGc3y684OzBCxuu5niQSDi83DEexVzy7usirM3nVm858gXpkkuvXvQCiYXPcvctfI/ecviisPj6T908eMHKW267K1XPvK6eKz7q2JPlQutq2B45JmTYCzEOW0N+X/m8cy/EGP4SoJAAgaYEhNZNyRqXAAEC7RAQWrejD2bRbwGhdb/73+TqhdZN6vZ8bKF1+AFoW2idJ16EksURFMWZyEUw/cCOhwbrO+z5mxYdMVE+OiIfG/Hyl7045RdT3DM/v+BRHGWR31GErHm8/IJ+x73h2LTjwYdXHFqXdyhXz3GuNmS5cDnX58D23vu2L1xaHCGSX3RypaF1dd3F4Hkn9fFvPW5RUF98rHzUSQ7Mlwuti/4U12eLj/7e2enarTftF4hXd89Xnco7s4vwftgaqt7lF5MMfzIECu20DiApIUDg5wJCa08CAQIEui0gtO52f61uNgSE1rPRp1mcpdB6Frs2I3MWWocbNcnQOjypMRVWd1aPadihw0RC6Cbv39WxlzsbfNi6lzo+ZbVOQuvVCrqeQI8EhNY9aralEiDQSwGhdS/bbtEtExBat6whHZqO0LpDzWzbUoTW4Y48/snfT3v/5J6U1qwJXXPg8w9LGy65Iq197iGh+mkWCa2nqT++e+c+5h3z73z7m9NJJxy/5MCjjj8Z12yE1uOSNA6BHggIrXvQZEskQKDXAkLrXrff4lsiILRuSSM6OA2hdQeb2pYlCa3b0gnzINApAaF1p9ppMQSaFRBaN+trdAIECExbQGg97Q64P4GU9u3+Vnr6b/7vtO+nsV14zAhEBfblwn3hDZ7RYdURSGntvrT24OeltUf9LzQIECAwNgGh9dgoDUSg+wJC6+732AoJEOi3gNC63/23+nYI7Ln7c+mp79+W1m58bjsmZBadEdi3b196OqV0QPBYgs4s3EIaF9i3d2/66Y8OTOt//+rG7+UGBAj0R0Bo3Z9eWymBVQsIrVdNaAACBAi0WkBo3er2mFxPBHJovecLn0sH/fKLe7Jiy5yUgONBJiXdv/s8/T/+3/T0k3vTxkuu6N/irZgAgcYEhNaN0RqYQPcEhNbd66kVESBAoCwgtPY8EJi+gNB6+j3o6gyE1l3t7PTXJbSefg/MgEAXBYTWXeyqNRFoSEBo3RCsYQkQINASAaF1SxphGr0WEFr3uv2NLl5o3ShvrwcXWve6/RZPoDEBoXVjtAYm0D0BoXX3empFBAgQKAsIrT0PBKYvILSefg+6OgOhdVc7O/11Ca3jPfjw529J2/7yv4QvOHzDoenG95yRNhz8rPA1Cgl0RUBo3ZVOWgeBCQgIrSeA7BYECBCYooDQeor4bk3gFwJCa49CUwJC66ZkjSu0jj8Db/l3l6aX/pNfSs9dNxe66Gs/eCD9+//5tHTkxv8pVK+IwDgEHvzBD9MnPnlleufb35xOOuH4JYd8bPfu9LGPX5aO3nJ4Oves08Zx+4UxhNZj5TQYgW4LCK273V+rI0CAgNDaM0Bg+gJC6+n3oKszEFp3tbPTX5fQOt6DSYbWRZh46ntPTq855pULk7zymq2D/72agHHU2HGJyVV+e/v96cabb00XX3RB2rB+/cKN8xouufTqdOZpH0i7Hns8XX7VdYsmdfSWI9OFF5yd5ubWLXp/EejumZ9feP+xrz1mSc/5+b3pksuuTg/seGjkNXmeeQ6nnPiuRUFxYf3orl0L1xY1w8bNRYdu3Jg++ntnp2u33pRe8SsvWTRevs+1N9yYPvqRc9NRR7xwv0YUY77jbW9a9NxU75XvUZiWLYeNudJuC61XKuc6Aj0UEFr3sOmWTIBArwSE1r1qt8W2VEBo3dLGdGBaQusONLGlSxBaxxsjtI5bjatyVMCew9svfPGrg2D6L773l/sF2zncf2DHw4vC7tvu2Jbuuvsr+wW+ufbVx7xqUchbzH/UTuTrP3VzesPrX7cQHBc/THh01+5FYXl1/sXfj3v9r6fj3/rGQRheDabL9y6C+RwmR37YUHYpAvtha8jv2/blr6f3n3Li4Hb5uj/d/uer+mFItedC63F9FhiHQA8EhNY9aLIlEiDQawGhda/bb/EtERBat6QRHZyG0LqDTW3JkoTW8Ua0MbSu7uQ9/5wzF8LXHKTee9/2wQIPnptbCGvL788fyzt/X/6yF6fLr7o+ve41r0p3bfvK4JryDuTqDu9yOLrzkb8dXHvYYZvS/d/53sK1OQgudkCXx8rh8Xe++/00d/C6hfryvKsdGba7PL9v86ZNg13Io3Zjl6+LBL7DnoRirsN2bZfD5Sv+YGv6nfednK694dOD3d/FjuVh981j7nzkkXTGB9+3ZGhdhMlFOL/tS18bXLfULvuySzG/4n5LXZfnmddw3u+etmhHe/yzY/9KofVq9FxLoGcCQuueNdxyCRDonYDQunctt+AWCgitW9iUjkxJaN2RRrZwGULreFPaFlqXd+3m8DYffXHd1k+nCz989mBR5Z20OcwsdgHP750fnGNcPnqkODbjV1/x0kEoWg1blwuty2coV8fKf8+h9vnnnDEIc3OIesvtd6YiqB4VOhedqX68epzFqOvL79/x0F8NPWZkqe4XR2qM2gldnl+xS7kaGg8LrQvLSGid75Hrn5ifT4/lXdwfPntkqJzne8U1N6R3n/CbC6F5cWxJMdfyDy/Kax91rEj8s0NovRor1xLovYDQuvePAAACBDouILTueIMtbyYEhNYz0aaZnKTQeibbNhOTFlrH2zSN0Lp8FnIx02LXcjWsXSp4LNfmcYaF1uVguQhL8585xF4utC5fO+pIjCIkr+5eXm4XdHVd1SMwRoXW5RA/h9bFjuV8bEb1bOthO72jQW75eJFhAXvZurjvh04/Nb38pS/a76zs7F0+bzr/fTmf4rkYtls6uoai36OOSYl/lvxDpZ3WK1FzDYGeCgite9p4yyZAoDcCQuvetNpCWywgtG5xc2Z8akLrGW9gi6cvtI43Zxqh9VIvxFjdRVuspLyDufwChUUYGg2ty8dKNBlaR4LV6lzK4epqdlovFQhHdlqXg/H8QpGjAvvyDx+K/kTGL8Lkv/7RzjQ//5P9XpCy/PQOC62rz0j1hSLL1y91tnf8s0RovRIr1xDovYDQuvePAAACBDouILTueIMtbyYEhNYz0aaZnKTQeibbNhOTFlrH29TG0Lq8e7i8khxWXnvDjQvnWM/yTuu8riIc/tDpH0h/9JlbF529vJozrZfbxbzcmdbFUSfVp6jYDb/aULy8q/z6P/zM4DajzqYedjxIro+caV2E43Zax78eqCRAYIwCQusxYhqKAAECLRQQWrewKabUOwGhde9aPrEFC60nRt27Gwmt4y1vW2hdPdM6rySHnMXbjTffurAzNweX93zjm4O/z62b2+8FAKvnTg87hzq/eGJ+QcL8dsllVw/+zH8vXoixOLO67vEgywXD+T7FruRDN67fL7gdFlrnXcMP7Hh40c7kfJ+77v7KQpCfB1outC4+fvSWwxeFxdd/6ubBi1becttdqXrmdfVs8epRLEV/lttpXT27e7m5FsFz8QKVxX2GrSG/r3zmuRdijH8dUEmAQAMCQusGUA1JgACBFgkIrVvUDFPprYDQuretb3zhQuvGiXt7A6F1vPVtC63LoWtx/ERxBEgRTD+w46HBAg97/qZFx0uUj43IR0a8/GUvTvnFFPfMzy+AlM95LgLWPF5+Mb/j3nBs2vHgwysOrfMLMRZv1TOcR3Wk+gKORd2wY1KO3nLkYG75/OryW/Us6/yxYedZl68pr714f95Jffxbj1v0ApPFx8rHnWw58gX7nR9erSt6VPb46O+dna7detN+gXh1B33Vqnre96h7Vc3zdcWLScY/I5audKb1uCSNQ6AHAkLrHjTZEgkQ6LWA0LrX7bf4lggIrVvSiA5OQ2jdwaa2ZElC63gjJhlax2c1nsrqzurxjDp8lMjO6ibv3+WxI+eDV9df3dE9Lh+h9bgkjUOgBwJC6x402RIJEOi1gNC61+23+JYICK1b0ogOTkNo3cGmtmRJQut4Iz581y3pC3/5F2nNmjWhiw7fcGi68T1npA0HPytUP80iofU09cd772I3+Tvf/uZ00gnHLzn4qONPxjEjofU4FI1BoCcCQuueNNoyCRDorYDQurett/AWCQitW9SMjk1FaN2xhrZoOULrFjXDVAh0SEBo3aFmWgqBpgWE1k0LG58AAQLTFRBaT9ff3QlkAaG156ApAaF1U7LGFVp7BggQaEKgc6F1+RU2N6z/+SuCDnsbdnB6cYh4rs+vzLlxwyGLDl0vrjns+b809DD2JhpkTAJtEhBat6kb5kKAAIHxCwitx29qRAJ1BYTWdcXURwWE1lEpdXUFhNZ1xdQTIBAR6ExoXZyhkl/tNPKqoUudtVMcIP7Enr3pd9737vSaY145sLzymq3pr3+0Mx08d7DQOvJ0qemcgNC6cy21IAIECCwSEFp7IAhMX0BoPf0edHUGQuuudnb66xJaT78HZkCgiwKdCa2L5tTZaX35Vden8885Ix11xAsX9bYIrY/7jWPT/d/9fjrvrNPTzkf+Nn32js+n5//SprTjwYeF1l38bLCmZQWE1ssSKSBAgMBMCwitZ7p9Jt8RAaF1RxrZwmUIrVvYlI5MSWjdkUZaBoGWCfQ6tP7EJ69Me+bnBy0p784uQuszT/tA2vale9Krj3lV2rnzkbR586bBn9/57vcXQut9+1rWUdMh0KDAj5/Ym57xjAPTMw46sMG7GHqowJp9Ke2LvcI0QQIECKxUYNfje9LGQw5e6eWuI0BgDAI5tJ7f9rl04C+/eAyjGYLAPwg8/dS+9NS+p9NBBx6AhcBYBXJovW/v3rThkivGOu44BlvjP6HGwWgMAlMR6G1oXdXOR388umv3IIye3zufLrn06pRD6/x27dYb08aNGwY7rrd96WuLQutdj/94Ko1zUwLTEBj8kGbN4P+8TVjggAMOSE899dSE7+p2BAj0TWDfvjVpTf4hmTcCBKYm8PQ929LTX92W0pG/PLU5NH3jtWvWpqf3Pd30bYw/TOAX38/DITBWgV2PpvTk3nTgRZeMddhxDLbxkGePY5ixjfGhf/376XNf+lp4vCNfcFi644Yr0sb1h4SvUUigKwJC6190snysSH5XEVpv3vS8dMllV6d3vO1Ng7Otb7tj26LQuisPgnUQiAg4HiSipIYAAQKzK+B4kNntnZl3R8DxIN3pZdtW4niQtnWkO/NxPEi8l7/2zvemX33Ji9Jz/1EsTP/iN76Zbr328rTl8H8av8kEKleajc3P7x1kbK/4lZekk044fvDacfnt3LNOm8Cs23mLnEfmkyDe+fY3D0yWe8tmD+x4OF180QVpw/r1y5XP9MeF1suE1tXzrlf6iTnTT4nJE/iFgNDao0CAAIFuCwitu91fq5sNAaH1bPRpFmcptJ7Frs3GnIXW8T5NI7QuQtHieNw822Nfe8yqguKVZmOTCK2Lezyw46GFxlTXm48F/tjHL0sbNxyy6DXrivc/umvXwrWnnPiuQZg8bNxcVBw3/PVv3LffJtdivONe/+tDA+lizGKjbHHT6r3KRxrnmhxcb960KRRyx5/O9lX2JrTOn1D3fOObCz+JuPvLX0tHHXn4woswln+6Uz7TWmjdvofWjKYnILSenr07EyBAYBICQutJKLsHgaUFhNaekKYEhNZNyRpXaB1/BiYdWucs7K67v5I++pFzF/KvIvTMr9+WTxRYydtKQ+vqvca907oIiY/ecviiUP76T92c3vD61y0YfHv7/ekLX/xqmp+fHxwNXGR/xfWnvvfkgU05dD7+rW9ctEt8mFs1TF5ufcU88lHFc3PrBkMOW0N+37Yvfz29/5QTF2qu+IOt6bzfPa3Tu607E1oP+2lI+Scp1dA6PxiXX3XdwjN29JYjF366IrReyZcs1/RBQGjdhy5bIwECfRYQWve5+9beFgGhdVs60b15CK2719O2rEhoHe/EJEPragA7apY5L7vl9jsXPnz+OWcuhNnVXdpFzpavue/P/tPgmr/+0d8M/ixfV83oio8tt9N61HXF+1/76l9N93z93sH9qkF8fl80TM9hcg7t/3T7ny/asTzMLI+585FH0hkffN+yoXU5T8zzuW7rp9OFHz57ZLA8bMd0cb/ljkwp1rDSHzzEn9rpVXYmtJ4eoTsT6I+A0Lo/vbZSAgT6KSC07mffrbpdAkLrdvWjS7MRWnepm+1ai9A63o9JhtZ5s+aNN9+65NnHOUS+9XNfSCf/1jsGO33LGz7n1s0teo23cu22L31t0Q7u8r2K64pzq4vg+0Onn5pe/tIXjTzTunqURvW154Yd51GWrwbio7qS71PsUt7x0F8NdlwXO52HhdbFbulIaJ3vmS1u/Q93DW5/8m+/c+Ru9jzfK665Ib37hN9ctAO8vMH24Lm5oeF8EdDnMH25cDv+dLavUmjdvp6YEYHWCgitW9saEyNAgMBYBITWY2E0CIFVCQitV8Xn4iUEhNYej6YEhNZx2UmH1uVAtrprurwzulhBrrn8quvT+eeckTasf+7g3Odh5zFXdzSXw958TnQxRnHsxqjgt3x8RjVkL5/3vOXIFwzmUhzbMUx81PnQ1dp8n7zDOoe9o44DKe4zLHAvn5Wdx66eN53ft9yxILmmHJ4XL6gYXUMRjhfriD+Bs1U59tA6N+bRXbsXHWRekBT4h25c3+mfBMzWI2C2BOICQuu4lUoCBAjMooDQeha7Zs5dExBad62j7VmP0Lo9vejaTITW8Y5OOrQettO6GtRWw+zy7t5RQXc1tC6HrTm0rh6LMeqIjWpoXd5lXKjmcL1OaF3s8I4G29XXuMvhePmFGEcdbTKq6zkU/6PPfHZwXnbeXT7q+I5hoXX1KOPiRSCH3ascvsefwNmqHGtoHTkvJ/LrCbNFaLYE+iMgtO5Pr62UAIF+Cgit+9l3q26XgNC6Xf3o0myE1l3qZrvWIrSO92OSofWojK66K/oTn7xyIVwt77QudkkXqyvneV//xn3pO9/9/tBjNVaz07q8M7ysGskbc/1yZ1pXQ/jiHsVu6fz3UTu6I8ePlM+03vXY40sezzLseJBiDZFjP4TW8c+7QeVSL2BYDFU+k6bY/l7zNsoJEJiSgNB6SvBuS4AAgQkJCK0nBO02BJYQEFp7PJoSEFo3JWtcoXX8GZhkaF0EoHfd/ZVF5yIvdZRHDkKvveHGQX0+HmTbl7+e3n/KiYMFLhVal8PiXHvJZVen4pSFlZ5pXdwz/xnZaV3kkjl0PnrL4YtOeLj+UzenN7z+dekv/st/XRS252uix5BEQuvqCysud0zIsBdiLPpTXkN+X7kXed5eiDH+eTeorP7kIz+0mzdvWrQV3k7rmqjKCbRIQGjdomaYCgECBBoQEFo3gGpIAjUFhNY1wZSHBYTWYSqFNQWE1nGwSYfWeWbDdheXz7PO4ee9920fLGLjhg2DP/OZ1ps3PW8QPhdnOJePDcl53y2337mw8Oq5zkU+WByzMeqIjWqoW70usgO6ql+Ey+Wzp4997TFpqRdSLI4vef97Tlx2p/WoM62ru8/LOemwc8Hzx3NGOmx3eXUNw3yLF5Ps8obgsR4PksHLD1wRWhcPUD7HZbmfMsQ/1VUSIDBpAaH1pMXdjwABApMVEFpP1tvdCAwTEFp7LpoSEFo3JWtcoXX8GZhGaB2fncpJC9R54cXy3Ibt0J703Cdxv7GH1gV4nvyWow5PW448YrCOvXv3pnv+5N6Uz3S5+KILUpd/EjCJxrkHgWkICK2noe6eBAgQmJyA0Hpy1u5EYJSA0Nqz0ZSA0LopWeMKrePPwIf+9e+nO754T1qzZk3ooiNfcFi644Yr0sb1h4TqFc2eQLET/p1vf3M66YTjl11ADqwf2PFwL7LVsYfWhW751wuK9+Xt+OeeddqyDVBAgEA7BYTW7eyLWREgQGBcAkLrcUkah8DKBYTWK7dz5dICQmtPSFMCQuumZI1LoN8CjYXWmXXY8SD95rZ6ArMtILSe7f6ZPQECBJYTEFovJ+TjBJoXEFo3b9zXOwit+9r55tcttG7e2B0I9FGg0dC6j6DWTKDLAkLrLnfX2ggQIJCS0NpTQGD6AkLr6fegqzMQWne1s9Nfl9B6+j0wAwJdFBBad7Gr1kSgIQGhdUOwhiVAgEBLBITWLWmEafRaQGjd6/Y3unihdaO8vR5caN3r9ls8gcYEhNaN0RqYQPcEhNbd66kVESBAoCwgtPY8EJi+gNB6+j3o6gyE1l3t7PTXJbSefg/MgEAXBYTWXeyqNRFoSEBo3RCsYQkQINASAaF1SxphGr0WEFr3uv2NLl5o3ShvrwcXWve6/RZPoDEBoXVjtAYm0D0BoXX3empFBAgQKAsIrT0PBKYvILSefg+6OgOhdVc7O/11Ca2n3wMzINBFAaF1F7tqTQQaEhBaNwRrWAIECLREQGjdkkaYRq8FhNa9bn+jixdaN8rb68GF1r1uv8UTaEygsdD6sd2708c+fll6dNeu/SZ/6MaN6eKLLkgb1q9vbGEGJkBg/AJC6/GbGpEAAQJtEhBat6kb5tJXAaF1Xzvf/LqF1s0b9/UOQuu+dt66CTQr0FhofeU1WwczP/es05pdgdEJEJiYgNB6YtRuRIAAgakICK2nwu6mBBYJCK09EE0JCK2bkjWu0NozQIBAEwKNhNZ5l/Ull16dzjztA+moI17YxLyNSYDAFASE1lNAd0sCBAhMUEBoPUFstyIwQkBo7dFoSkBo3ZSscYXWngECBJoQEFo3oWpMAh0VEFp3tLGWRYAAgV8ICK09CgSmLyC0nn4PujoDoXVXOzv9dQmtp98DMyDQRYFGQusMlY8H2bxpUzrphOO76GZNBHopILTuZdstmgCBHgkIrXvUbEttrYDQurWtmfmJCa1nvoWtXYDQurWtMTECMy3QWGj94A9+mD57x+fTeWednubm1s00kskTIPBzAaG1J4EAAQLdFhBad7u/VjcbAkLr2ejTLM5SaD2LXZuNOQutZ6NPZklg1gQaCa3zmdYf+/hl6dFdu4Z6HLpxY7r4ogvShvXrZ83LfAn0WkBo3ev2WzwBAj0QEFr3oMmW2HoBoXXrWzSzExRaz2zrWj9xoXXrW2SCBGZSoJHQeiYlTJoAgWUFhNbLEikgQIDATAsIrWe6fSbfEQGhdUca2cJlCK1b2JSOTElo3ZFGWgaBlgkIrVvWENMh0GYBoXWbu2NuBAgQWL2A0Hr1hkYgsFoBofVqBV0/SkBo7dloSkBo3ZSscQn0W0Bo3e/+Wz2BWgJC61pcigkQIDBzAkLrmWuZCXdQQGjdwaa2ZElC65Y0ooPTEFp3sKmWRKAFAoHlSUoAACAASURBVGMNrYuzrN/59uPSXXff40zrFjTYFAiMU0BoPU5NYxEgQKB9AkLr9vXEjPonILTuX88ntWKh9aSk+3cfoXX/em7FBCYhMNbQehITdg8CBKYnILSenr07EyBAYBICQutJKLsHgaUFhNaekKYEhNZNyRpXaO0ZIECgCQGhdROqxiTQUQGhdUcba1kECBD4hYDQ2qNAYPoCQuvp96CrMxBad7Wz01+X0Hr6PTADAl0UEFp3savWRKAhAaF1Q7CGJUCAQEsEhNYtaYRp9FpAaN3r9je6eKF1o7y9Hlxo3ev2WzyBxgSE1o3RGphA9wSE1t3rqRXNpsCu/3R7+unfPTSbkzfrVgv89Kc/SwcddGCr52hysylw0HOPTBv/2YmzOfkJz1poPWHwHt1OaN2jZk94qULrCYO7HYGeCAite9JoyyQwDgGh9TgUjUFgdQI//smT6Ymvnpc2HHbQ6gZyNQECBCYo8Oh/+1l67puvSAcf9IwJ3nU2byW0ns2+zcKshdaz0KXZnKPQejb7ZtYE2i4gtG57h8yPQIsEhNYtaoap9FZg9/ye9JbrL02/efTLemtg4c0J7H3yp2ndM/1ApDnh/o5813/9i/S1D30k/aN1c/1FCK5caB2EUlZbQGhdm8wFQQGhdRBKGQECtQTGGlo/tnt3uumPb09nfPB9aW5u3dCJzM/vTdf/4WfS+99zYtqwfn2tySomQGC6AkLr6fq7O4EsILT2HDQpILRuUrffYwut4/0XWsetVNYTEFrX81IdFxBax61UEiAQFxh7aP2xj1+WHt21K51/zpnpNce8ctFMvr39/nT5VdelQzduTBdfdIHQOt4nlQRaISC0bkUbTKLnAkLrnj8ADS9faN0wcI+HF1rHmy+0jluprCcgtK7npTouILSOW6kkQCAuMNbQurhtEU4fveXIdOEFZw/efcllV6cHdjyUTjnxXemkE46Pz1AlAQKtERBat6YVJtJjAaF1j5s/gaULrSeA3NNbCK3jjRdax61U1hMQWtfzUh0XEFrHrVQSIBAXaCS0Lm5/5TVb0733bR/8tQiwRx0bEp+ySgIEpiUgtJ6WvPsS+AcBobWnoUkBoXWTuv0eW2gd77/QOm6lsp6A0Lqel+q4gNA6bqWSAIG4QGOhdT67uthdnadz7GuPSeeedVp8ZioJEGidgNC6dS0xoR4KCK172PQJLlloPUHsnt1KaB1vuNA6bqWynoDQup6X6riA0DpupZIAgbhAI6H1bXdsS7fcfufC7uo8nSLAHnbWdXy6KgkQmKaA0Hqa+u5N4OcCQmtPQpMCQusmdfs9ttA63n+hddxKZT0BoXU9L9VxAaF13EolAQJxgbGG1o/t3p0iL8ToqJB4g1QSaJOA0LpN3TCXvgoIrfva+cmsW2g9Gec+3kVoHe+60DpupbKegNC6npfquIDQOm6lkgCBuMDYQ+ub/vj2dMYH35dGnV2djw25/g8/k97/nhPThvXr4zNVSYDA1AWE1lNvgQkQsNPaM9CogNC6Ud5eDy60jrdfaB23UllPQGhdz0t1XEBoHbdSSYBAXGCsoXX8tioJEJhFAaH1LHbNnLsmYKd11zrarvUIrdvVjy7NRmgd76bQOm6lsp6A0Lqel+q4gNA6bqWSAIG4QO9D6wd/8MN03dZPpws/fPbCzu/iRSR3PfZ4uviiCxbeXxx/knnL749zqyQw2wJC69nun9l3Q0Bo3Y0+tnUVQuu2dmb25yW0jvdQaB23UllPQGhdz0t1XEBoHbdSSYBAXGCsoXUOdS+59Op05mkfSEcd8cJU/Xue1rCQOD7d8VWWz98+dOPGRSF0EVrvmd+TXvdrx6STTjh+cOP8ApPf+rPtaX7+J0Lr8bXCSDMkILSeoWaZamcFhNadbW0rFia0bkUbOjkJoXW8rULruJXKegJC63pequMCQuu4lUoCBOICvQ2tC6Kldlq/7tWvSt/60z9P5/3uaYPyK/5ga8rvu+vue4TW8WdMZYcEhNYdaqalzKyA0HpmWzcTExdaz0SbZnKSQut424TWcSuV9QSE1vW8VMcFhNZxK5UECMQFhNZLHA/yjre9Ke3c+chAc/PmTYP/nf+88eZbhdbxZ0xlhwSE1h1qpqXMrIDQemZbNxMTF1rPRJtmcpJC63jbhNZxK5X1BITW9bxUxwWE1nErlQQIxAWE1suE1luOfMHgyJO5ubnBjusdD/3VotD6x3uejGurJDDjAj/9yc/S2gPWpgMOWDvjK5m96a9duyY9/fS+2Zu4GY9d4PG98+mET1+Z3nbUS8Y+tgEJPPXU077GewwaEbh7x/fS53/nX6bnPHOukfG7NOhPv/L59NMvfT6tPeroLi1r0VrWrFmT9u3zfc2kG5zJs3v+vtIbgXEK7Hv0f6R9T+5NB/9v/+c4hx3LWM8++JljGccgBAhMXkBovUxo/ZpjXpmuvGZr2rxp0+Bs629vv39RaJ13JHkj0BeBJ3/ys3TAgWvTgWuF1hPv+Zo1+b8yJn5bN2yfwON796Tf/MP/K719y0vbNzkzmnmBn/3sqXTggQfM/DosoH0Cd/8/3013//N/JbQOtObJL92VftL50Nq3NYFHYewlObDO304KrcdO2/sBi9D6Ob9/aess1j3zoNbNyYQIEIgJCK0DoXWZshpax5hVEeiGgONButFHq5htAceDzHb/2j57x4O0vUOzOz/Hg8R753iQuJXKegKOB6nnpTou4HiQuJVKAgTiAmMPrT/28cvSo7t2LTmDQzdubM2Z0Eu9EGM+0zrvtBZaxx8old0WEFp3u79WNxsCQuvZ6NOszlJoPauda/+8hdbxHgmt41Yq6wkIret5qY4LCK3jVioJEIgLjDW0jt92+pWP7d6dqgH7sa89Jp171mlpfn5vuuSyq5PQevp9MoN2CQit29UPs+mngNC6n32f1KqF1pOS7t99hNbxngut41Yq6wkIret5qY4LCK3jVioJEIgL9Da0jhOpJECgEBBaexYITF9AaD39HnR5BkLrLnd3umsTWsf9hdZxK5X1BITW9bxUxwWE1nErlQQIxAUaCa3zCxfee9/2wSyK3cvxKakkQKCtAkLrtnbGvPokILTuU7cnv1ah9eTN+3JHoXW800LruJXKegJC63pequMCQuu4lUoCBOICYw+tb7tjW/rOd7+fLrzg7DQ3ty7lAHvzpk3ppBOOj89KJQECrRQQWreyLSbVMwGhdc8aPuHlCq0nDN6j2wmt480WWsetVNYTEFrX81IdFxBax61UEiAQFxhraD3sLOhhL3QYn55KAgTaJCC0blM3zKWvAkLrvnZ+MusWWk/GuY93EVrHuy60jluprCcgtK7npTouILSOW6kkQCAuMNbQOr+44SWXXp3OPO0D6agjXjiYxbD3xaenkgCBNgkIrdvUDXPpq4DQuq+dn8y6hdaTce7jXYTW8a4LreNWKusJCK3reamOCwit41YqCRCIC0wktP7Yxy9Lp7735PSaY14Zn5lKAgRaJyC0bl1LTKiHAkLrHjZ9gksWWk8Qu2e3ElrHGy60jluprCcgtK7npTouILSOW6kkQCAuILSOW6kk0HsBoXXvHwEALRAQWregCR2egtC6w82d8tKE1vEGCK3jVirrCQit63mpjgsIreNWKgkQiAuMPbTOu6of3bVryRkcunFjuviiC9KG9evjM1VJgMDUBYTWU2+BCRBIQmsPQZMCQusmdfs9ttA63n+hddxKZT0BoXU9L9VxAaF13EolAQJxgbGG1svdNp9vnUPt/Ca0Xk7Lxwm0T0Bo3b6emFH/BITW/ev5JFcstJ6kdr/uJbSO91toHbdSWU9AaF3PS3VcQGgdt1JJgEBcYCKh9be3358uv+q6wawOnptLH/3IuQsv1BifqkoCBKYtILSedgfcn0Cy09pD0KiA0LpR3l4PLrSOt19oHbdSWU9AaF3PS3VcQGgdt1JJgEBcoNHQ+sprtqZ779u+MJvzzznTizHGe6OSQOsEhNata4kJ9VDATuseNn2CSxZaTxC7Z7cSWscbLrSOW6msJyC0ruelOi4gtI5bqSRAIC4w9tC6OAKkONc6B9VbjnzB4FiQU997stA63huVBFonILRuXUtMqIcCQuseNn2CSxZaTxC7Z7cSWscbLrSOW6msJyC0ruelOi4gtI5bqSRAIC4w1tB61JnVxfuF1vHGqCTQRgGhdRu7Yk59ExBa963jk12v0Hqy3n26m9A63m2hddxKZT0BoXU9L9VxAaF13EolAQJxgUZC640bDkkXXnB2mptbN5iJ0DreEJUE2iwgtG5zd8ytLwJC6750ejrrFFpPx70PdxVax7sstI5bqawnILSu56U6LiC0jlupJEAgLjDW0LocUOfjQYoXXdyw/rmOB4n3RCWB1goIrVvbGhPrkYDQukfNnsJShdZTQO/JLYXW8UYLreNWKusJCK3reamOCwit41YqCRCIC4w9tC7f2gsxxhuhksAsCAitZ6FL5th1AaF11zs83fUJrafr3+W7C63j3RVax61U1hMQWtfzUh0XEFrHrVQSIBAXaDS0Lqbx7e33p8uvum7w16O3HLno6JD4VFUSIDBtAaH1tDvg/gRSElp7CpoUEFo3qdvvsYXW8f4LreNWKusJCK3reamOCwit41YqCRCIC0wktC6mM+qFGuPTVUmAwDQFhNbT1HdvAj8XEFp7EpoUEFo3qdvvsYXW8f4LreNWKusJCK3reamOCwit41YqCRCIC0w0tI5PSyUBAm0UEFq3sSvm1DcBoXXfOj7Z9QqtJ+vdp7sJrePdFlrHrVTWExBa1/NSHRcQWsetVBIgEBcYe2hdHAVy/jlnptcc88pFM1nqY/EpqyRAYFoCQutpybsvgX8QEFp7GpoUEFo3qdvvsYXW8f4LreNWKusJCK3reamOCwit41YqCRCIC4w9tM4vvpjfzj3rtKGzWO7j8amrJEBg0gJC60mLux+B/QWE1p6KJgWE1k3q9ntsoXW8/0LruJXKegJC63pequMCQuu4lUoCBOICYw2tizOrT33vyfvtsi6mlHdb33jzreniiy5IG9avj89UJQECUxcQWk+9BSZAwJnWnoFGBYTWjfL2enChdbz9Quu4lcp6AkLrel6q4wJC67iVSgIE4gJjD60vufTqdOZpH0hHHfHCobN48Ac/TNdt/XS68MNnC63jfVJJoBUCQutWtMEkei5gp3XPH4CGly+0bhi4x8MLrePNF1rHrVTWExBa1/NSHRcQWsetVBIgEBcYa2g9P783XXLZ1ekdb3vTkjutv/DFr6YLLzg7zc2ti89UJQECUxcQWk+9BSZAwE5rz0CjAkLrRnl7PbjQOt5+oXXcSmU9AaF1PS/VcQGhddxKJQECcYGxhtb5trfdsS3tfOSRJc+03rxpUzrphOPjs1RJgEArBITWrWiDSfRcwE7rnj8ADS9faN0wcI+HF1rHmy+0jluprCcgtK7npTouILSOW6kkQCAuMPbQuthtnadQ3k1dvH/XY487zzreH5UEWiUgtG5VO0ympwJC6542fkLLFlpPCLqHtxFax5sutI5bqawnILSu56U6LiC0jlupJEAgLjD20Lq4dd5xfcvtdy6aySknvssO63hvVBJonYDQunUtMaEeCgite9j0CS5ZaD1B7J7dSmgdb7jQOm6lsp6A0Lqel+q4gNA6bqWSAIG4QGOhdXwKKgkQmBUBofWsdMo8uywgtO5yd6e/NqH19HvQ1RkIreOdFVrHrVTWExBa1/NSHRcQWsetVBIgEBcQWsetVBLovYDQuvePAIAWCAitW9CEDk9BaN3h5k55aULreAOE1nErlfUEhNb1vFTHBYTWcSuVBAjEBYTWcSuVBHovILTu/SMAoAUCQusWNKHDUxBad7i5U16a0DreAKF13EplPQGhdT0v1XEBoXXcSiUBAnEBoXXcSiWB3gsIrXv/CABogYDQugVN6PAUhNYdbu6Ulya0jjdAaB23UllPQGhdz0t1XEBoHbdSSYBAXEBoHbdSSaD3AkLr3j8CAFogILRuQRM6PAWhdYebO+WlCa3jDRBax61U1hMQWtfzUh0XEFrHrVQSIBAXEFrHrVQS6L2A0Lr3jwCAFggIrVvQhA5PQWjd4eZOeWlC63gDhNZxK5X1BITW9bxUxwWE1nErlQQIxAWE1nErlQR6LyC07v0jAKAFAkLrFjShw1MQWne4uVNemtA63gChddxKZT0BoXU9L9VxAaF13EolAQJxAaF13Eolgd4LCK17/wgAaIGA0LoFTejwFITWHW7ulJcmtI43QGgdt1JZT0BoXc9LdVxAaB23UkmAQFxAaB23Ukmg9wJC694/AgBaICC0bkETOjwFoXWHmzvlpQmt4w0QWsetVNYTEFrX81IdFxBax61UEiAQFxBax61UEui9gNC6948AgBYICK1b0IQOT0Fo3eHmTnlpQut4A4TWcSuV9QSE1vW8VMcFhNZxK5UECMQFhNZxK5UEei8gtO79IwCgBQJC6xY0ocNTEFp3uLlTXprQOt4AoXXcSmU9AaF1PS/VcQGhddxKJQECcQGhddxKJYHeCwite/8IAGiBgNC6BU3o8BSE1h1u7pSXJrSON0BoHbdSWU9AaF3PS3VcQGgdt1JJgEBcQGgdt1JJoPcCQuvePwIAWiAgtG5BEzo8BaF1h5s75aUJreMNEFrHrVTWExBa1/NSHRcQWsetVBIgEBcQWsetVBLovYDQuvePAIAWCAitW9CEDk9BaN3h5k55aULreAOE1nErlfUEhNb1vFTHBYTWcSuVBAjEBYTWcSuVBHovILTu/SMAoAUCQusWNKHDUxBad7i5U16a0DreAKF13EplPQGhdT0v1XEBoXXcSiUBAnEBoXXcSiWB3gsIrXv/CABogYDQugVN6PAUhNYdbu6Ulya0jjdAaB23UllPQGhdz0t1XEBoHbdSSYBAXKBTofVtd2xLt9x+52D1R285Ml14wdlpbm7dUI0Hf/DD9IlPXpn2zM8vfPzQjRvTxRddMPj7xz5+Wdq44ZBFYxTXHPb8X1py7Di/SgKzJSC0nq1+mW03BYTW3exrW1YltG5LJ7o3D6F1vKdC67iVynoCQut6XqrjAkLruJVKAgTiAp0Jrb+9/f504823DkLnDevXpyuv2TpQOPes00aG1pdfdX06/5wz0lFHvHBRzWO7d6dLLr06PbFnb/qd9707veaYVw4+nsf86x/tTAfPHSy0jj9jKjskILTuUDMtZWYFhNYz27qZmLjQeibaNJOTFFrH2ya0jluprCcgtK7npTouILSOW6kkQCAu0JnQOgfKmzdtSiedcPxg9dUQu0qSd00vF1of9xvHpvu/+/103lmnp52P/G367B2fT8//pU1px4MPC63jz5jKDgkIrTvUTEuZWQGh9cy2biYmLrSeiTbN5CSF1vG2Ca3jVirrCQit63mpjgsIreNWKgkQiAt0IrSen9+bLrns6vSKX3nJQmi9VCidearHgxRHg+Rd2sVO6zNP+0Da9qV70quPeVXaufORtHnzpsGf3/nu94XW8WdMZYcEfvzE3nTQMw5MzzzowA6tylIIzJaA0Hq2+jVrsxVaz1rHZme+Qut4r4TWcSuV9QRyaP3000+ngw48oN6FqgksIyC09ogQINCEQKdC63e87U0LR3ksF1pXMfNO7Ud37R6E0fN75wfHg+TQOr9du/XGtHHjhsGO621f+tqi0PrR3T9uoi/GJNBKgX37UlqzppVT6/ykDjzggPSzp57q/DotcHmBv3tyPp1yyzXpzYe/aPliFQQIEGiJwJd/8F/Tre/53fScZw5/vZmWTLMV03j6nm1p3z3bUjril1sxnyYmsWbt2rTv6aebGNqYywjsSyn5dt5jMnaBXY+m9OTedMBFl4x96NUOeOj6Z692CNcTIDAlgU6F1nV2Wle9c8h93dZPpws/fPbgQ0VovXnT8wa7uItAPL/Yo53WU3pa3XbqAo4HmXoLTIBAstPaQ9CkgJ3WTer2e2w7reP9t9M6bqWynoDjQep5qY4L2Gkdt1JJgEBcoBOhdV5u3TOto6F19UUahdbxh0tl9wSE1t3rqRXNnoDQevZ6NkszFlrPUrdma65C63i/hNZxK5X1BITW9bxUxwWE1nErlQQIxAU6E1pXX3gxh9j57dyzThv8mcPme77xzXTxRRekfG713V/+WjrqyMNTEUqX68tnWgut4w+Tyu4LCK2732MrbL+A0Lr9PZrlGQqtZ7l77Z670DreH6F13EplPQGhdT0v1XEBoXXcSiUBAnGBzoTWRTB9y+13DlZ/9JYjF71YYjW0ziH35VddtyBVrhdaxx8glf0SEFr3q99W204BoXU7+9KVWQmtu9LJ9q1DaB3vidA6bqWynoDQup6X6riA0DpupZIAgbhAp0Lr+LJVEiCwEgGh9UrUXENgvAJC6/F6Gm2xgNDaE9GUgNA6Liu0jluprCcgtK7npTouILSOW6kkQCAuILSOW6kk0HsBoXXvHwEALRAQWregCR2egtC6w82d8tKE1vEGCK3jVirrCQit63mpjgsIreNWKgkQiAsIreNWKgn0XkBo3ftHAEALBITWLWhCh6cgtO5wc6e8NKF1vAFC67iVynoCQut6XqrjAkLruJVKAgTiAkLruJVKAr0XEFr3/hEA0AIBoXULmtDhKQitO9zcKS9NaB1vgNA6bqWynoDQup6X6riA0DpupZIAgbiA0DpupZJA7wWE1r1/BAC0QEBo3YImdHgKQusON3fKSxNaxxsgtI5bqawnILSu56U6LiC0jlupJEAgLiC0jlupJNB7AaF17x8BAC0QEFq3oAkdnoLQusPNnfLShNbxBgit41Yq6wkIret5qY4LCK3jVioJEIgLCK3jVioJ9F5AaN37RwBACwSE1i1oQoenILTucHOnvDShdbwBQuu4lcp6AkLrel6q4wJC67iVSgIE4gJC67iVSgK9FxBa9/4RANACAaF1C5rQ4SkIrTvc3CkvTWgdb4DQOm6lsp6A0Lqel+q4gNA6bqWSAIG4gNA6bqWSQO8FhNa9fwQAtEBAaN2CJnR4CkLrDjd3yksTWscbILSOW6msJyC0ruelOi4gtI5bqSRAIC4gtI5bqSTQewGhde8fAQAtEBBat6AJHZ6C0LrDzZ3y0oTW8QYIreNWKusJCK3reamOCwit41YqCRCICwit41YqCfReQGjd+0cAQAsEhNYtaEKHpyC07nBzp7w0oXW8AULruJXKegJC63pequMCQuu4lUoCBOICQuu4lUoCvRcQWvf+EQDQAgGhdQua0OEpCK073NwpL01oHW+A0DpupbKegNC6npfquIDQOm6lkgCBuIDQOm6lkkDvBYTWvX8EALRAQGjdgiZ0eApC6w43d8pLE1rHGyC0jluprCcgtK7npTouILSOW6kkQCAuILSOW6kk0HsBoXXvHwEALRAQWregCR2egtC6w82d8tKE1vEGCK3jVirrCQit63mpjgsIreNWKgkQiAsIreNWKgn0XkBo3ftHAEALBITWLWhCh6cgtO5wc6e8NKF1vAFC67iVynoCQut6XqrjAkLruJVKAgTiAkLruJVKAr0XEFr3/hEA0AIBoXULmtDhKQitO9zcKS9NaB1vgNA6bqWynoDQup6X6riA0DpupZIAgbiA0DpupZJA7wWE1r1/BAC0QEBo3YImdHgKQusON3fKSxNaxxsgtI5bqawnILSu56U6LiC0jlupJEAgLiC0jlupJNB7AaF17x8BAC0QEFq3oAkdnoLQusPNnfLShNbxBgit41Yq6wkIret5qY4LCK3jVioJEIgLCK3jVioJ9F5AaN37RwBACwSE1i1oQoenILTucHOnvDShdbwBQuu4lcp6AkLrel6q4wJC67iVSgIE4gJC67iVSgK9FxBa9/4RANACAaF1C5rQ4SkIrTvc3CkvTWgdb4DQOm6lsp6A0Lqel+q4gNA6bqWSAIG4gNA6bqWSQO8FhNa9fwQAtEBAaN2CJnR4CkLrDjd3yksTWscbILSOW6msJyC0ruelOi4gtI5bqSRAIC4gtI5bqSTQewGhde8fAQAtEBBat6AJHZ6C0LrDzZ3y0oTW8QYIreNWKusJCK3reamOCwit41YqCRCICwit41YqCfReQGjd+0cAQAsEhNYtaEKHpyC07nBzp7w0oXW8AULruJXKegJC63pequMCQuu4lUoCBOICQuu4lUoCvRcQWvf+EQDQAgGhdQua0OEpCK073NwpL01oHW+A0DpupbKegNC6npfquIDQOm6lkgCBuIDQOm6lkkDvBYTWvX8EALRAQGjdgiZ0eApC6w43d8pLE1rHGyC0jluprCcgtK7npTouILSOW6kkQCAuILSOW6kk0HsBoXXvHwEALRAQWregCR2egtC6w82d8tKE1vEGCK3jVirrCQit63mpjgsIreNWKgkQiAsIreNWKgn0XkBo3ftHAEALBITWLWhCh6cgtO5wc6e8NKF1vAFC67iVynoCQut6XqrjAkLruJVKAgTiAkLruJVKAr0XEFr3/hEA0AIBoXULmtDhKQitO9zcKS9NaB1vgNA6bqWynoDQup6X6riA0DpupZIAgbiA0DpupZJA7wWE1r1/BAC0QEBo3YImdHgKQusON3fKSxNaxxsgtI5bqawnILSu56U6LiC0jlupJEAgLiC0jlupJNB7AaF17x8BAC0QEFq3oAkdnoLQusPNnfLShNbxBgit41Yq6wkIret5qY4LCK3jVioJEIgLCK3jVioJ9F5AaN37RwBACwSE1i1oQoenILTucHOnvDShdbwBQuu4lcp6AkLrel6q4wJC67iVSgIE4gJC67iVSgK9FxBa9/4RANACAaF1C5rQ4SkIrTvc3CkvTWgdb4DQOm6lsp6A0Lqel+q4gNA6bqWSAIG4gNA6bqWSQO8FhNa9fwQAtEBAYEr7AwAAFgdJREFUaN2CJnR4CkLrDjd3yksTWscbILSOW6msJyC0ruelOi4gtI5bqSRAIC4gtI5bqSTQewGhde8fAQAtEBBat6AJHZ6C0LrDzZ3y0oTW8QYIreNWKusJCK3reamOCwit41YqCRCICwit41YqCfReQGjd+0cAQAsEhNYtaEKHpyC07nBzp7w0oXW8AULruJXKegJC63pequMCQuu4lUoCBOICQuu4lUoCvRcQWvf+EQDQAgGhdQua0OEpCK073NwpL01oHW+A0DpupbKegNC6npfquIDQOm6lkgCBuIDQOm6lkkDvBYTWvX8EALRAQGjdgiZ0eApC6w43d8pLE1rHGyC0jluprCcgtK7npTouILSOW6kkQCAuILSOW6kk0HsBoXXvHwEALRAQWregCR2egtC6w82d8tKE1vEGCK3jVirrCQit63mpjgsIreNWKgkQiAsIreNWKgn0XkBo3ftHAEALBITWLWhCh6cgtO5wc6e8NKF1vAFC67iVynoCQut6XqrjAkLruJVKAgTiAkLruJVKAr0XEFr3/hEA0AIBoXULmtDhKQitO9zcKS9NaB1vgNA6bqWynoDQup6X6riA0DpupZIAgbiA0DpupZJA7wWE1r1/BAC0QEBo3YImdHgKQusON3fKSxNaxxsgtI5bqawnILSu56U6LiC0jlupJEAgLiC0jlupJNB7AaF17x8BAC0QEFq3oAkdnoLQusPNnfLShNbxBgit41Yq6wkIret5qY4LCK3jVioJEIgLCK0DVrfdsS3dcvudg8qjtxyZLrzg7DQ3ty5wpRIC3RIQWnern1YzmwJC69ns26zMWmg9K52avXkKreM9E1rHrVTWExBa1/NSHRcQWsetVBIgEBcQWi9j9e3t96cbb741XXzRBWnD+vXpymu2Dq4496zT4soqCXREQGjdkUZaxkwLCK1nun2tn7zQuvUtmtkJCq3jrRNax61U1hMQWtfzUh0XEFrHrVQSIBAXEFovY5VD6s2bNqWTTjh+UFkNsePUKgnMvoDQevZ7aAWzLyC0nv0etnkFQus2d2e25ya0jvdPaB23UllPQGhdz0t1XEBoHbdSSYBAXEBovYTV/PzedMllV6dX/MpLFkLrB3/ww3T5Vden8885Ix11xAvj0ioJdEBAaN2BJlrCzAsIrWe+ha1egNC61e2Z6ckJrePtE1rHrVTWExBa1/NSHRcQWsetVBIgEBcQWgdC63e87U3pNce8clBZDa0f3f3juPaEKr/79T9KL3/OX0zobm5DgACB1Qs8+eS+dNCvX7r6gXowwt89OZ9OuOnKdND8z3qwWkskQKArAj9dd2C68wP/Mj3nmV4XZrmePn3PtrTrpuvTroOesVypjxMgQKAVAgc/9bP0rEM2po2fvKYV8ylP4tD1z27dnEyIAIGYgNA6EFovtdO6jaF1rPWqCBAgQIAAAQIECBAgQIAAAQLdFRBad7e3VtZ9AaH1Mj12pnX3PwmskAABAgQIECBAgAABAgQIECBAgACB9ggIrZfpRfWFF3OInd/OPeu09nTRTAgQIECAAAECBAgQIECAAAECBAgQINARAaF1oJG33bEt3XL7nYPKo7ccmS684Ow0N+c8vgCdkh4IlH+Q44VKe9BwSyRAgMAEBfy7MkFstyJAgAABAgQIECDQIgGhdYuaYSoEVivw2O7d6WMfvyw9umvXwlCHbtyYLr7ogrRh/frVDj/0eqF1I6wGJUCgAwLV39bKSyq+Tp/63pMXXuR5JUsd1zgrufckrxFaT1LbvQjMhsCor3/j+I3YvnxtzZ3OXvfet32h6QfPzaWPfuTcdNQRL0x509Z3vvv9mdusNT+/N11y2dXpgR0PLazr2Nces+i3pPO/K5/45JVpz/z8Qs3555w5+Dc5/7t9+VXXpVNOfFc66YTjFz5ebGKrvn82PmPMkgABArMrILSe3d6ZOYH9BIZ9oz2Ob+CXom56fG0mQIDArAoIrVffOaH16g2NQKBrAkLr1Xd0WCid/83aufORQVg766H1K37lJYN1FCH2oRvXD4LrIpQuQuosmZ+nm/749nTGB9+X/uJ7f5n+6DOfTc86eF268MNnDzb95I9fcunV6Yk9e9ObfuP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   "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"
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  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
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   "outputs": [
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       "                            \n",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "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": 109,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ebitda_report.show(comparison='relative')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "outputs": [
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   "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": 111,
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "outputs": [
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    "_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",
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    "\n",
    "npv_graph"
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  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {
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",
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   ],
   "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": 113,
   "metadata": {
    "tags": [
     "exclude"
    ]
   },
   "outputs": [
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    "_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",
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    "\n",
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    "    text=_series.values, \n",
    "    textposition='outside', \n",
    "    texttemplate=\"%{text:.1f} years\", \n",
    ")\n",
    "\n",
    "spt_fig "
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  {
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   "execution_count": 114,
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",
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       "<div>                            <div id=\"2cedcac5-2361-4272-8a68-ad219e4d491f\" class=\"plotly-graph-div\" style=\"height:400px; width:600px;\"></div>            <script type=\"text/javascript\">                require([\"plotly\"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById(\"2cedcac5-2361-4272-8a68-ad219e4d491f\")) {                    Plotly.newPlot(                        \"2cedcac5-2361-4272-8a68-ad219e4d491f\",                        [{\"marker\":{\"color\":\"rgba(70, 165, 121, 0.6)\",\"line\":{\"color\":\"rgba(70, 165, 121, 1.0)\",\"width\":1}},\"name\":\"COP\",\"orientation\":\"v\",\"text\":[2.899979700142095,2.717906557159644],\"x\":[\"Heatpump only\",\"Heatpump + Storage_PCM\"],\"y\":[2.899979700142095,2.717906557159644],\"type\":\"bar\",\"textposition\":\"outside\",\"texttemplate\":\"%{text:.1f}\"}],                        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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "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": 117,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'BREAK' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[117], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[43mBREAK\u001b[49m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'BREAK' is not defined"
     ]
    }
   ],
   "source": [
    "BREAK"
   ]
  },
  {
   "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 = setup_model(c=c)\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."
   ]
  }
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