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"cell_type": "markdown",
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"source": [
"#### Imports"
]
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"cell_type": "code",
"execution_count": 1,
"metadata": {
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"exclude"
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"outputs": [
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"data": {
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" \n",
" "
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"output_type": "display_data"
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" \n",
" "
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"source": [
"from datetime import timedelta\n",
"import json\n",
"import pprint\n",
"from copy import deepcopy\n",
"\n",
"import cufflinks\n",
"cufflinks.go_offline()\n",
"import numpy as np\n",
"from numpy.polynomial import Polynomial\n",
"import pandas as pd\n",
"from tqdm.notebook import tqdm\n",
"\n",
"from pyrecoy.assets import Heatpump, Eboiler, GasBoiler, HotWaterStorage\n",
"from pyrecoy.colors import *\n",
"from pyrecoy.converters import *\n",
"from pyrecoy.financial import calculate_eb_ode, get_tax_tables, get_tax_rate, get_grid_tariffs_electricity\n",
"from pyrecoy.framework import TimeFramework\n",
"from pyrecoy.casestudy import CaseStudy\n",
"from pyrecoy.plotting import ebitda_bar_chart, npv_bar_chart\n",
"from pyrecoy.reports import CaseReport, ComparisonReport, BusinessCaseReport, SingleFigureComparison\n",
"from pyrecoy.sensitivity import SensitivityAnalysis\n",
"from pyrecoy.prices import get_tennet_data, get_afrr_capacity_fees_nl\n",
"from pyrecoy.forecasts import Mipf\n",
"\n",
"%load_ext autoreload\n",
"%autoreload 2"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": [
"exclude"
]
},
"source": [
"#### Development backlog"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": [
"exclude"
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},
"source": [
"* aFRR (can improve the optimisation case)\n",
"* Report\n",
"\n",
"--\n",
"* Create strategy on imbalance POS (buy 100% day-ahead, and respond to high prices)\n",
"* Graphs\n",
" * EBITDA vs. baseline (earnings vs baseline)\n",
"* Show COP curves in different cases, just for illustration\n",
"* Energy report --> Check + add gas\n",
"* Fix comparison reports\n",
"* Model verification"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": [
"exclude"
]
},
"source": [
"#### Meeting Notes"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": [
"exclude"
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},
"source": [
"##### Meeting 25-11-2020"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": [
"exclude"
]
},
"source": [
"* aFRR can help optimisation case\n",
"* SDE++ should be included\n",
"* Tsource sensitivity really gives interesting insights\n",
"* Sensitivities should be verified (especially CO2, Tsink, Tsource, time period)\n",
"* AP TNO: Update/verify COP curve\n",
"* AP TNO: Update CAPEX\n",
"* AP Mark: \n",
" * Create graphs on COP curve with different Tsource, Tsink\n",
" * Generate table and output in .csv (send it to Andrew)\n",
"* Investigate opportunity to lower the COP and negative electricity prices\n",
" * Technically feasible, but not really needed/possible to do it in this project\n",
"* Could be interesting to run this model on a usecase with higher delta T\n",
"* Conclusion: Finalize this model, but not add too much extra complexity, next steps is to go towards industrial partners with the results"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": [
"exclude"
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"source": [
"# ENCORE : Heatpump Optimisation Framework\n",
"\n",
"***\n",
"© Mark Kremer \n",
"July 2020\n",
"##### Cases\n",
"In this model, 3 cases are compared:\n",
"* **Baseline** : All heat is supplied by steam turbine\n",
"* **Heatpump case** : All heat is supplied by heatpump\n",
"* **Hybrid case** : Steam turbine and heatpump run in hybrid mode, and are optimised on costs in real-time"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": [
"exclude"
]
},
"source": [
"#### Loading config"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
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"outputs": [],
"source": [
"class Config():\n",
" start = '2019-01-01'\n",
" end = '2019-12-31'\n",
" \n",
" hp_vdg_e_power = 23.3 # MW\n",
" hp_ndg_e_power = 7.7 # MW\n",
" hp_min_load = 0\n",
" hp_lifetime = 25\n",
" hp_capex = 200_000 # EUR/MWth\n",
" hp_opex = 0.01 # in % of CAPEX\n",
" hp_devex = 0.005 # in % of CAPEX\n",
" \n",
" gb_power = 35 # MW\n",
" gb_efficiency = 0.9\n",
" \n",
" storage_power = 25\n",
" storage_volume = 1000\n",
" storage_cap_per_volume = 50 * 1e-3\n",
" storage_lifetime = 25\n",
" storage_temperature = 95\n",
" storage_min_level = storage_volume * storage_cap_per_volume * 0.05\n",
" storage_capex_per_MW = 7_000\n",
" storage_capex_per_MWh = 5_000\n",
" storage_opex_perc_of_capex = 0.02\n",
" # storage_initial_level = 5\n",
" threshold = 20\n",
" \n",
" tax_bracket_g = 4 \n",
" tax_bracket_e = 4\n",
" \n",
" include_transport_costs = False\n",
" grid_operator = 'Liander'\n",
" connection_type = 'TS/MS'\n",
" \n",
" discount_rate = 0.1\n",
" project_duration = 12\n",
"\n",
" forecast = 'ForeNeg'\n",
" gas_price_multiplier = 1\n",
" e_price_multiplier = 1\n",
" e_price_volatility_multiplier = 1\n",
" co2_price_multiplier = 1\n",
" tsource_delta = 0\n",
" tsink_delta = 0\n",
" energy_tax_multiplier = 1\n",
" \n",
" # Review the SDE implementation\n",
" sde_base_amount = 81\n",
" longterm_gas_price = 24.00\n",
" longterm_co2_price = 37.90\n",
" sde_switch_price_correction = 40\n",
" \n",
" day_ahead_buying_perc = 0.3\n",
" \n",
" afrr_capacity_fee = 25_000\n",
"\n",
"c = Config()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"tags": [
"exclude"
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},
"outputs": [],
"source": [
"class Store():\n",
" pass"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": [
"exclude"
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},
"source": [
"## Model set-up"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"tags": [
"exclude"
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},
"outputs": [],
"source": [
"def load_demand_data(c, s):\n",
" demand = pd.read_csv('data/smurfit_demand_preprocessed.csv', delimiter=';', decimal=',')\n",
" dt_index = pd.date_range(\n",
" start=s.time_fw.start,\n",
" end=s.time_fw.start + timedelta(days=365), freq='1T',\n",
" closed='left',\n",
" tz='Europe/Amsterdam')\n",
" demand.index = dt_index\n",
" demand['Total demand'] = demand['MW (VDG)'] + demand['MW (NDG)']\n",
" demand = demand[c.start:c.end]\n",
" return demand"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"s = Store()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"tags": [
"exclude"
]
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\mekre\\AppData\\Local\\Temp\\ipykernel_19048\\332434720.py:3: FutureWarning:\n",
"\n",
"Argument `closed` is deprecated in favor of `inclusive`.\n",
"\n"
]
}
],
"source": [
"def setup_model(c):\n",
" s = Store()\n",
" \n",
" s.time_fw = TimeFramework(start=c.start, end=c.end)\n",
" mipf = Mipf(start=s.time_fw.start, end=s.time_fw.end, tidy=True, include_nextQ=True,\n",
" #folder_path = r\"C:\\Users\\Shahla Huseynova\\Recoy\\Recoy - Documents\\03 - Libraries\\12 - Data Management\\Forecast Data\"\n",
" ).data\n",
" \n",
" s.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.afrr_case = CaseStudy(time_fw=s.time_fw, freq='1T', name='Optimisation + aFRR', data=mipf)\n",
" s.storage_case = CaseStudy(time_fw=s.time_fw, freq='1T', name='Heatpump + Storage', data=mipf)\n",
" \n",
" s.cases = list(CaseStudy.instances.values())\n",
" #s.optcases = [s.hpcase, s.hpcase_sde, s.optcase1, s.afrr_case]\n",
" s.optcases = [s.hpcase, s.storage_case]\n",
" #s.sde_cases = [s.hpcase_sde, s.optcase1, s.afrr_case]\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": 9,
"metadata": {},
"outputs": [
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"plotlyServerURL": "https://plot.ly",
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"s.demand.resample('15T').mean()[['Tsource (VDG)', 'Tsink (VDG)']].iplot()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" Tsource (VDG) | \n",
" Tsink (VDG) | \n",
" MW (VDG) | \n",
" Tsource (NDG) | \n",
" Tsink (NDG) | \n",
" MW (NDG) | \n",
" Total demand | \n",
"
\n",
" \n",
" \n",
" \n",
" | count | \n",
" 525600.000000 | \n",
" 525600.000000 | \n",
" 525600.000000 | \n",
" 525600.000000 | \n",
" 525600.000000 | \n",
" 525600.000000 | \n",
" 525600.000000 | \n",
"
\n",
" \n",
" | mean | \n",
" 63.658798 | \n",
" 138.637674 | \n",
" 17.636712 | \n",
" 62.176305 | \n",
" 145.351645 | \n",
" 5.823824 | \n",
" 23.460537 | \n",
"
\n",
" \n",
" | std | \n",
" 6.422773 | \n",
" 14.328580 | \n",
" 5.123252 | \n",
" 10.252555 | \n",
" 14.896056 | \n",
" 1.691697 | \n",
" 6.814125 | \n",
"
\n",
" \n",
" | min | \n",
" 25.310000 | \n",
" 82.480000 | \n",
" 0.000000 | \n",
" 13.540000 | \n",
" 106.330000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
"
\n",
" \n",
" | 25% | \n",
" 64.892000 | \n",
" 126.074000 | \n",
" 17.014000 | \n",
" 63.516000 | \n",
" 131.551500 | \n",
" 5.612000 | \n",
" 22.676000 | \n",
"
\n",
" \n",
" | 50% | \n",
" 64.991000 | \n",
" 142.450000 | \n",
" 19.892000 | \n",
" 64.313000 | \n",
" 148.490000 | \n",
" 6.540000 | \n",
" 26.441000 | \n",
"
\n",
" \n",
" | 75% | \n",
" 65.076000 | \n",
" 151.730000 | \n",
" 20.819000 | \n",
" 65.546000 | \n",
" 158.100000 | \n",
" 6.880000 | \n",
" 27.690000 | \n",
"
\n",
" \n",
" | max | \n",
" 70.070000 | \n",
" 166.020000 | \n",
" 23.250000 | \n",
" 73.470000 | \n",
" 172.050000 | \n",
" 7.650000 | \n",
" 30.900000 | \n",
"
\n",
" \n",
"
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" DAM | \n",
" POS | \n",
" NEG | \n",
" RS | \n",
" ForePos | \n",
" ForeNeg | \n",
" ForePos_nextQ | \n",
" ForeNeg_nextQ | \n",
" Gas prices (€/MWh) | \n",
" CO2 prices (€/ton) | \n",
" CO2 prices (€/MWh) | \n",
" Tsource (VDG) | \n",
" Tsink (VDG) | \n",
" MW (VDG) | \n",
" Tsource (NDG) | \n",
" Tsink (NDG) | \n",
" MW (NDG) | \n",
" Total demand | \n",
"
\n",
" \n",
" \n",
" \n",
" | 2019-01-01 00:00:00+01:00 | \n",
" 68.92 | \n",
" 34.85 | \n",
" 58.01 | \n",
" 2.0 | \n",
" 46.83 | \n",
" 52.70 | \n",
" NaN | \n",
" NaN | \n",
" 22.38 | \n",
" 24.98 | \n",
" 4.82 | \n",
" 64.990 | \n",
" 143.360 | \n",
" 0.0 | \n",
" 20.510 | \n",
" 147.620 | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-01-01 00:01:00+01:00 | \n",
" 68.92 | \n",
" 34.85 | \n",
" 58.01 | \n",
" 2.0 | \n",
" 32.12 | \n",
" 54.45 | \n",
" NaN | \n",
" NaN | \n",
" 22.38 | \n",
" 24.98 | \n",
" 4.82 | \n",
" 64.985 | \n",
" 143.089 | \n",
" 0.0 | \n",
" 20.387 | \n",
" 147.642 | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-01-01 00:02:00+01:00 | \n",
" 68.92 | \n",
" 34.85 | \n",
" 58.01 | \n",
" 2.0 | \n",
" 30.97 | \n",
" 48.64 | \n",
" NaN | \n",
" NaN | \n",
" 22.38 | \n",
" 24.98 | \n",
" 4.82 | \n",
" 64.980 | \n",
" 142.818 | \n",
" 0.0 | \n",
" 20.264 | \n",
" 147.664 | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-01-01 00:03:00+01:00 | \n",
" 68.92 | \n",
" 34.85 | \n",
" 58.01 | \n",
" 2.0 | \n",
" 51.13 | \n",
" 48.35 | \n",
" 57.71 | \n",
" 73.05 | \n",
" 22.38 | \n",
" 24.98 | \n",
" 4.82 | \n",
" 64.975 | \n",
" 142.547 | \n",
" 0.0 | \n",
" 20.141 | \n",
" 147.686 | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-01-01 00:04:00+01:00 | \n",
" 68.92 | \n",
" 34.85 | \n",
" 58.01 | \n",
" 2.0 | \n",
" 48.04 | \n",
" 52.01 | \n",
" 63.60 | \n",
" 79.07 | \n",
" 22.38 | \n",
" 24.98 | \n",
" 4.82 | \n",
" 64.970 | \n",
" 142.276 | \n",
" 0.0 | \n",
" 20.018 | \n",
" 147.708 | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
"
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" DAM | \n",
" POS | \n",
" NEG | \n",
" RS | \n",
" ForePos | \n",
" ForeNeg | \n",
" ForePos_nextQ | \n",
" ForeNeg_nextQ | \n",
" Gas prices (€/MWh) | \n",
" CO2 prices (€/ton) | \n",
" ... | \n",
" from_storage_MW | \n",
" storage_level_MWh | \n",
" hp_output_MWh | \n",
" hp_input_MWh | \n",
" to_storage_ndg_MWh | \n",
" from_storage_ndg_MWh | \n",
" to_storage_vdg_MWh | \n",
" from_storage_vdg_MWh | \n",
" to_storage_MWh | \n",
" from_storage_MWh | \n",
"
\n",
" \n",
" \n",
" \n",
" | 2019-08-09 23:08:00+02:00 | \n",
" 31.26 | \n",
" 256.25 | \n",
" 256.25 | \n",
" 1.0 | \n",
" 114.11 | \n",
" 120.66 | \n",
" 42.95 | \n",
" 47.21 | \n",
" 10.925 | \n",
" 28.09 | \n",
" ... | \n",
" 0.0 | \n",
" 2.500 | \n",
" 0.347 | \n",
" -0.060 | \n",
" 0.0 | \n",
" 0.000 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.000 | \n",
"
\n",
" \n",
" | 2019-01-15 13:06:00+01:00 | \n",
" 54.90 | \n",
" 39.85 | \n",
" 46.18 | \n",
" 2.0 | \n",
" 35.77 | \n",
" 31.27 | \n",
" 37.64 | \n",
" 35.14 | \n",
" 21.500 | \n",
" 22.47 | \n",
" ... | \n",
" 25.0 | \n",
" 8.882 | \n",
" 0.183 | \n",
" -0.059 | \n",
" 0.0 | \n",
" 0.417 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.417 | \n",
"
\n",
" \n",
"
\n",
"
2 rows × 38 columns
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" DAM | \n",
" POS | \n",
" NEG | \n",
" hp_output_MW | \n",
" to_storage_MW | \n",
" Total demand | \n",
"
\n",
" \n",
" \n",
" \n",
" | count | \n",
" 525600.000000 | \n",
" 525600.000000 | \n",
" 525600.000000 | \n",
" 525600.000000 | \n",
" 525600.000000 | \n",
" 525600.000000 | \n",
"
\n",
" \n",
" | mean | \n",
" 41.195801 | \n",
" 40.391060 | \n",
" 42.554082 | \n",
" 24.325753 | \n",
" 1.225095 | \n",
" 23.460537 | \n",
"
\n",
" \n",
" | std | \n",
" 11.278173 | \n",
" 51.226931 | \n",
" 52.003252 | \n",
" 7.030977 | \n",
" 3.623716 | \n",
" 6.814125 | \n",
"
\n",
" \n",
" | min | \n",
" -9.020000 | \n",
" -487.650000 | \n",
" -487.650000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
"
\n",
" \n",
" | 25% | \n",
" 34.100000 | \n",
" 24.470000 | \n",
" 25.530000 | \n",
" 22.766000 | \n",
" 0.000000 | \n",
" 22.676000 | \n",
"
\n",
" \n",
" | 50% | \n",
" 39.700000 | \n",
" 31.110000 | \n",
" 32.160000 | \n",
" 26.975000 | \n",
" 0.000000 | \n",
" 26.441000 | \n",
"
\n",
" \n",
" | 75% | \n",
" 47.392500 | \n",
" 40.900000 | \n",
" 42.540000 | \n",
" 27.990000 | \n",
" 0.000000 | \n",
" 27.690000 | \n",
"
\n",
" \n",
" | max | \n",
" 121.460000 | \n",
" 936.120000 | \n",
" 936.120000 | \n",
" 31.000000 | \n",
" 25.000000 | \n",
" 30.900000 | \n",
"
\n",
" \n",
"
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" DAM | \n",
" POS | \n",
" NEG | \n",
" hp_output_MW | \n",
" to_storage_MW | \n",
" from_storage_MW | \n",
" Total demand | \n",
"
\n",
" \n",
" \n",
" \n",
" | 2019-03-28 09:54:00+01:00 | \n",
" 46.78 | \n",
" 33.66 | \n",
" 33.66 | \n",
" 22.770 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 22.770 | \n",
"
\n",
" \n",
" | 2019-06-04 18:38:00+02:00 | \n",
" 45.13 | \n",
" 25.58 | \n",
" 25.58 | \n",
" 22.768 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 22.768 | \n",
"
\n",
" \n",
" | 2019-01-09 17:57:00+01:00 | \n",
" 75.64 | \n",
" 75.64 | \n",
" 75.64 | \n",
" 27.728 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 27.728 | \n",
"
\n",
" \n",
" | 2019-11-29 17:20:00+01:00 | \n",
" 54.13 | \n",
" 47.24 | \n",
" 47.24 | \n",
" 22.740 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 22.740 | \n",
"
\n",
" \n",
" | 2019-11-27 06:22:00+01:00 | \n",
" 41.94 | \n",
" 36.07 | \n",
" 36.07 | \n",
" 27.464 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 27.464 | \n",
"
\n",
" \n",
" | 2019-11-29 15:23:00+01:00 | \n",
" 51.04 | \n",
" 112.24 | \n",
" 112.24 | \n",
" 22.828 | \n",
" 0.0 | \n",
" 25.0 | \n",
" 22.828 | \n",
"
\n",
" \n",
" | 2019-06-18 14:24:00+02:00 | \n",
" 36.06 | \n",
" 32.12 | \n",
" 32.12 | \n",
" 20.774 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 20.774 | \n",
"
\n",
" \n",
" | 2019-01-23 14:02:00+01:00 | \n",
" 85.59 | \n",
" 285.59 | \n",
" 285.59 | \n",
" 27.514 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 27.514 | \n",
"
\n",
" \n",
" | 2019-02-06 06:16:00+01:00 | \n",
" 50.66 | \n",
" 38.91 | \n",
" 42.39 | \n",
" 27.388 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 27.388 | \n",
"
\n",
" \n",
" | 2019-05-28 11:25:00+02:00 | \n",
" 48.08 | \n",
" 348.08 | \n",
" 348.08 | \n",
" 29.575 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 29.575 | \n",
"
\n",
" \n",
" | 2019-04-04 00:03:00+02:00 | \n",
" 35.60 | \n",
" 165.12 | \n",
" 165.12 | \n",
" 22.650 | \n",
" 0.0 | \n",
" 25.0 | \n",
" 22.650 | \n",
"
\n",
" \n",
" | 2019-03-31 11:14:00+02:00 | \n",
" 37.38 | \n",
" 30.86 | \n",
" 46.86 | \n",
" 27.870 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 27.870 | \n",
"
\n",
" \n",
" | 2019-07-02 12:06:00+02:00 | \n",
" 40.98 | \n",
" 24.50 | \n",
" 24.50 | \n",
" 26.808 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 26.808 | \n",
"
\n",
" \n",
" | 2019-11-17 00:59:00+01:00 | \n",
" 32.90 | \n",
" 21.24 | \n",
" 21.24 | \n",
" 22.931 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 22.931 | \n",
"
\n",
" \n",
" | 2019-12-24 07:54:00+01:00 | \n",
" 35.24 | \n",
" 26.38 | \n",
" 26.38 | \n",
" 29.544 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 29.544 | \n",
"
\n",
" \n",
" | 2019-06-27 20:07:00+02:00 | \n",
" 52.23 | \n",
" 41.01 | \n",
" 41.01 | \n",
" 29.629 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 29.629 | \n",
"
\n",
" \n",
" | 2019-11-18 17:19:00+01:00 | \n",
" 54.94 | \n",
" 40.81 | \n",
" 40.81 | \n",
" 0.000 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.000 | \n",
"
\n",
" \n",
" | 2019-02-26 18:13:00+01:00 | \n",
" 62.98 | \n",
" -0.45 | \n",
" 39.92 | \n",
" 31.000 | \n",
" 8.2 | \n",
" 0.0 | \n",
" 22.800 | \n",
"
\n",
" \n",
" | 2019-10-24 16:27:00+02:00 | \n",
" 37.81 | \n",
" 23.91 | \n",
" 23.91 | \n",
" 22.780 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 22.780 | \n",
"
\n",
" \n",
" | 2019-07-20 23:52:00+02:00 | \n",
" 37.29 | \n",
" 31.12 | \n",
" 31.12 | \n",
" 26.908 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 26.908 | \n",
"
\n",
" \n",
"
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" DAM | \n",
" POS | \n",
" NEG | \n",
" Total demand | \n",
" hp_input_MW | \n",
" hp_output_MW | \n",
" cop | \n",
" to_storage_MW | \n",
" from_storage_MW | \n",
"
\n",
" \n",
" \n",
" \n",
" | 2019-08-05 09:26:00+02:00 | \n",
" 51.55 | \n",
" 196.71 | \n",
" 196.71 | \n",
" 27.630 | \n",
" -5.222 | \n",
" 27.630 | \n",
" 5.291 | \n",
" 0.000 | \n",
" 0.00 | \n",
"
\n",
" \n",
" | 2019-02-03 21:08:00+01:00 | \n",
" 51.94 | \n",
" 32.38 | \n",
" 40.81 | \n",
" 20.632 | \n",
" -3.431 | \n",
" 20.632 | \n",
" 6.013 | \n",
" 0.000 | \n",
" 25.00 | \n",
"
\n",
" \n",
" | 2019-12-17 12:53:00+01:00 | \n",
" 34.70 | \n",
" 26.06 | \n",
" 26.06 | \n",
" 22.863 | \n",
" -3.946 | \n",
" 22.863 | \n",
" 5.794 | \n",
" 0.000 | \n",
" 0.00 | \n",
"
\n",
" \n",
" | 2019-11-13 00:32:00+01:00 | \n",
" 34.00 | \n",
" 26.37 | \n",
" 26.37 | \n",
" 27.938 | \n",
" -5.017 | \n",
" 27.938 | \n",
" 5.569 | \n",
" 0.000 | \n",
" 0.00 | \n",
"
\n",
" \n",
" | 2019-02-03 21:29:00+01:00 | \n",
" 51.94 | \n",
" 27.95 | \n",
" 27.95 | \n",
" 20.560 | \n",
" -4.083 | \n",
" 28.401 | \n",
" 6.956 | \n",
" 10.440 | \n",
" 25.00 | \n",
"
\n",
" \n",
" | 2019-11-24 05:10:00+01:00 | \n",
" 38.30 | \n",
" 40.00 | \n",
" 40.00 | \n",
" 26.740 | \n",
" -4.954 | \n",
" 26.740 | \n",
" 5.398 | \n",
" 0.000 | \n",
" 0.00 | \n",
"
\n",
" \n",
" | 2019-07-08 19:52:00+02:00 | \n",
" 42.90 | \n",
" 31.01 | \n",
" 31.01 | \n",
" 27.686 | \n",
" -5.253 | \n",
" 27.686 | \n",
" 5.271 | \n",
" 0.000 | \n",
" 0.00 | \n",
"
\n",
" \n",
" | 2019-01-23 00:26:00+01:00 | \n",
" 45.70 | \n",
" 49.91 | \n",
" 49.91 | \n",
" 26.366 | \n",
" -4.926 | \n",
" 26.366 | \n",
" 5.352 | \n",
" 0.000 | \n",
" 0.00 | \n",
"
\n",
" \n",
" | 2019-01-18 11:41:00+01:00 | \n",
" 71.28 | \n",
" 44.23 | \n",
" 44.23 | \n",
" 20.850 | \n",
" -4.402 | \n",
" 31.000 | \n",
" 7.042 | \n",
" 10.150 | \n",
" 0.00 | \n",
"
\n",
" \n",
" | 2019-01-11 23:56:00+01:00 | \n",
" 45.88 | \n",
" 35.68 | \n",
" 35.68 | \n",
" 20.788 | \n",
" -3.591 | \n",
" 20.788 | \n",
" 5.789 | \n",
" 0.000 | \n",
" 0.00 | \n",
"
\n",
" \n",
" | 2019-04-12 06:25:00+02:00 | \n",
" 49.62 | \n",
" 44.94 | \n",
" 44.94 | \n",
" 10.475 | \n",
" -2.327 | \n",
" 10.475 | \n",
" 4.502 | \n",
" 0.000 | \n",
" 25.00 | \n",
"
\n",
" \n",
" | 2019-03-31 13:45:00+02:00 | \n",
" 30.80 | \n",
" -15.23 | \n",
" -15.23 | \n",
" 27.780 | \n",
" -5.027 | \n",
" 27.780 | \n",
" 5.526 | \n",
" 3.220 | \n",
" 3.22 | \n",
"
\n",
" \n",
" | 2019-12-04 07:04:00+01:00 | \n",
" 53.40 | \n",
" -116.60 | \n",
" -116.60 | \n",
" 27.546 | \n",
" -5.380 | \n",
" 30.158 | \n",
" 5.606 | \n",
" 3.454 | \n",
" 3.00 | \n",
"
\n",
" \n",
" | 2019-03-08 23:15:00+01:00 | \n",
" 36.30 | \n",
" 40.10 | \n",
" 40.10 | \n",
" 27.610 | \n",
" -5.236 | \n",
" 27.610 | \n",
" 5.273 | \n",
" 0.000 | \n",
" 0.00 | \n",
"
\n",
" \n",
" | 2019-05-13 00:52:00+02:00 | \n",
" 44.94 | \n",
" 7.56 | \n",
" 7.56 | \n",
" 22.910 | \n",
" -4.688 | \n",
" 31.000 | \n",
" 6.612 | \n",
" 8.090 | \n",
" 0.00 | \n",
"
\n",
" \n",
" | 2019-03-06 16:49:00+01:00 | \n",
" 46.85 | \n",
" 88.86 | \n",
" 88.86 | \n",
" 22.859 | \n",
" -4.079 | \n",
" 22.859 | \n",
" 5.604 | \n",
" 0.000 | \n",
" 0.00 | \n",
"
\n",
" \n",
" | 2019-07-07 23:56:00+02:00 | \n",
" 33.02 | \n",
" 10.78 | \n",
" 10.78 | \n",
" 22.718 | \n",
" -4.867 | \n",
" 31.000 | \n",
" 6.370 | \n",
" 8.282 | \n",
" 0.00 | \n",
"
\n",
" \n",
" | 2019-05-14 19:37:00+02:00 | \n",
" 47.91 | \n",
" 32.50 | \n",
" 32.50 | \n",
" 28.311 | \n",
" -5.242 | \n",
" 28.311 | \n",
" 5.401 | \n",
" 0.000 | \n",
" 0.00 | \n",
"
\n",
" \n",
" | 2019-02-24 08:41:00+01:00 | \n",
" 39.11 | \n",
" 36.60 | \n",
" 36.60 | \n",
" 28.802 | \n",
" -5.284 | \n",
" 28.802 | \n",
" 5.450 | \n",
" 0.000 | \n",
" 0.00 | \n",
"
\n",
" \n",
" | 2019-04-02 11:50:00+02:00 | \n",
" 39.97 | \n",
" 20.23 | \n",
" 20.23 | \n",
" 27.650 | \n",
" -5.240 | \n",
" 27.650 | \n",
" 5.277 | \n",
" 0.000 | \n",
" 0.00 | \n",
"
\n",
" \n",
"
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" DAM | \n",
" POS | \n",
" NEG | \n",
" RS | \n",
" ForePos | \n",
" ForeNeg | \n",
" ForePos_nextQ | \n",
" ForeNeg_nextQ | \n",
" Gas prices (€/MWh) | \n",
" CO2 prices (€/ton) | \n",
" ... | \n",
" MW (VDG) | \n",
" Tsource (NDG) | \n",
" Tsink (NDG) | \n",
" MW (NDG) | \n",
" Total demand | \n",
" hp_output_MW | \n",
" hp_input_MW | \n",
" cop | \n",
" hp_output_MWh | \n",
" hp_input_MWh | \n",
"
\n",
" \n",
" \n",
" \n",
" | 2019-01-01 00:00:00+01:00 | \n",
" 68.92 | \n",
" 34.85 | \n",
" 58.01 | \n",
" 2.0 | \n",
" 46.83 | \n",
" 52.70 | \n",
" NaN | \n",
" NaN | \n",
" 22.38 | \n",
" 24.98 | \n",
" ... | \n",
" 0.0 | \n",
" 20.510 | \n",
" 147.620 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" NaN | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-01-01 00:01:00+01:00 | \n",
" 68.92 | \n",
" 34.85 | \n",
" 58.01 | \n",
" 2.0 | \n",
" 32.12 | \n",
" 54.45 | \n",
" NaN | \n",
" NaN | \n",
" 22.38 | \n",
" 24.98 | \n",
" ... | \n",
" 0.0 | \n",
" 20.387 | \n",
" 147.642 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" NaN | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-01-01 00:02:00+01:00 | \n",
" 68.92 | \n",
" 34.85 | \n",
" 58.01 | \n",
" 2.0 | \n",
" 30.97 | \n",
" 48.64 | \n",
" NaN | \n",
" NaN | \n",
" 22.38 | \n",
" 24.98 | \n",
" ... | \n",
" 0.0 | \n",
" 20.264 | \n",
" 147.664 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" NaN | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-01-01 00:03:00+01:00 | \n",
" 68.92 | \n",
" 34.85 | \n",
" 58.01 | \n",
" 2.0 | \n",
" 51.13 | \n",
" 48.35 | \n",
" 57.71 | \n",
" 73.05 | \n",
" 22.38 | \n",
" 24.98 | \n",
" ... | \n",
" 0.0 | \n",
" 20.141 | \n",
" 147.686 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" NaN | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
" | 2019-01-01 00:04:00+01:00 | \n",
" 68.92 | \n",
" 34.85 | \n",
" 58.01 | \n",
" 2.0 | \n",
" 48.04 | \n",
" 52.01 | \n",
" 63.60 | \n",
" 79.07 | \n",
" 22.38 | \n",
" 24.98 | \n",
" ... | \n",
" 0.0 | \n",
" 20.018 | \n",
" 147.708 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" 0.0 | \n",
" NaN | \n",
" 0.0 | \n",
" 0.0 | \n",
"
\n",
" \n",
"
\n",
"
5 rows × 23 columns
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" Heatpump only | \n",
" Heatpump + Storage | \n",
"
\n",
" \n",
" \n",
" \n",
" | Total net volume (MWh) | \n",
" -37,696 | \n",
" -38,174 | \n",
"
\n",
" \n",
" | Total exported to grid (MWh) | \n",
" - | \n",
" - | \n",
"
\n",
" \n",
" | Total consumed from grid (MWh) | \n",
" 37,696 | \n",
" 38,174 | \n",
"
\n",
" \n",
" | Total nominated volume (MWh) | \n",
" -37,696 | \n",
" -37,696 | \n",
"
\n",
" \n",
" | Absolute imbalance volume (MWh) | \n",
" - | \n",
" 692 | \n",
"
\n",
" \n",
" | Mean selling price (€/MWh) | \n",
" - | \n",
" - | \n",
"
\n",
" \n",
" | Mean buying price (€/MWh) | \n",
" 41 | \n",
" 41 | \n",
"
\n",
" \n",
" | Total day-ahead result (€) | \n",
" -1,553,699 | \n",
" -1,553,699 | \n",
"
\n",
" \n",
" | Total POS result (€) | \n",
" - | \n",
" 8,588 | \n",
"
\n",
" \n",
" | Total NEG result (€) | \n",
" - | \n",
" -4,839 | \n",
"
\n",
" \n",
" | Total imbalance result (€) | \n",
" - | \n",
" 3,749 | \n",
"
\n",
" \n",
" | Total combined result (€) | \n",
" -1,553,699 | \n",
" -1,549,950 | \n",
"
\n",
" \n",
"
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" Heatpump only | \n",
" Heatpump + Storage | \n",
"
\n",
" \n",
" \n",
" \n",
" | Gasboiler OPEX (€) | \n",
" - | \n",
" - | \n",
"
\n",
" \n",
" | Gas consumption costs (€) | \n",
" 3,089,622 | \n",
" 3,089,622 | \n",
"
\n",
" \n",
" | CO2 emission costs (€) | \n",
" 1,095,004 | \n",
" 1,095,004 | \n",
"
\n",
" \n",
" | Gas taxes (€) | \n",
" 790,305 | \n",
" 790,305 | \n",
"
\n",
" \n",
" | Heatpump VDG OPEX (€) | \n",
" -46,600 | \n",
" -46,600 | \n",
"
\n",
" \n",
" | Heatpump NDG OPEX (€) | \n",
" -15,400 | \n",
" -15,400 | \n",
"
\n",
" \n",
" | Result on electricity market (€) | \n",
" -1,553,699 | \n",
" -1,549,950 | \n",
"
\n",
" \n",
" | Electricity taxes (€) | \n",
" -35,811 | \n",
" -36,265 | \n",
"
\n",
" \n",
" | Grid transport costs (€) | \n",
" -273,944 | \n",
" -274,954 | \n",
"
\n",
" \n",
" | HotWaterStorage OPEX (€) | \n",
" - | \n",
" -8,500 | \n",
"
\n",
" \n",
" | EBITDA (€) | \n",
" 3,049,476 | \n",
" 3,043,260 | \n",
"
\n",
" \n",
"
\n",
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" Year 0 | \n",
" Year 1 | \n",
" Year 2 | \n",
" Year 3 | \n",
" Year 4 | \n",
" Year 5 | \n",
" Year 6 | \n",
" Year 7 | \n",
" Year 8 | \n",
" Year 9 | \n",
" Year 10 | \n",
" Year 11 | \n",
" Year 12 | \n",
"
\n",
" \n",
" \n",
" \n",
" | CAPEX (€) | \n",
" -6,231,000 | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
"
\n",
" \n",
" | Regular Earnings (€) | \n",
" | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
"
\n",
" \n",
" | Irregular Cashflows (€) | \n",
" | \n",
" - | \n",
" - | \n",
" - | \n",
" - | \n",
" - | \n",
" - | \n",
" - | \n",
" - | \n",
" - | \n",
" - | \n",
" - | \n",
" - | \n",
"
\n",
" \n",
" | EBITDA (€) | \n",
" | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
" 3,049,481 | \n",
"
\n",
" \n",
" | Depreciations (€) -/- | \n",
" | \n",
" -248,000 | \n",
" -248,000 | \n",
" -248,000 | \n",
" -248,000 | \n",
" -248,000 | \n",
" -248,000 | \n",
" -248,000 | \n",
" -248,000 | \n",
" -248,000 | \n",
" -248,000 | \n",
" -248,000 | \n",
" -248,000 | \n",
"
\n",
" \n",
" | EBIT (€) | \n",
" | \n",
" 2,801,481 | \n",
" 2,801,481 | \n",
" 2,801,481 | \n",
" 2,801,481 | \n",
" 2,801,481 | \n",
" 2,801,481 | \n",
" 2,801,481 | \n",
" 2,801,481 | \n",
" 2,801,481 | \n",
" 2,801,481 | \n",
" 2,801,481 | \n",
" 2,801,481 | \n",
"
\n",
" \n",
" | Income tax (Vpb.) (€) | \n",
" | \n",
" -687,120 | \n",
" -687,120 | \n",
" -687,120 | \n",
" -687,120 | \n",
" -687,120 | \n",
" -687,120 | \n",
" -687,120 | \n",
" -687,120 | \n",
" -687,120 | \n",
" -687,120 | \n",
" -687,120 | \n",
" -687,120 | \n",
"
\n",
" \n",
" | NOPLAT (€) | \n",
" | \n",
" 2,114,361 | \n",
" 2,114,361 | \n",
" 2,114,361 | \n",
" 2,114,361 | \n",
" 2,114,361 | \n",
" 2,114,361 | \n",
" 2,114,361 | \n",
" 2,114,361 | \n",
" 2,114,361 | \n",
" 2,114,361 | \n",
" 2,114,361 | \n",
" 2,114,361 | \n",
"
\n",
" \n",
" | Depreciations (€) +/+ | \n",
" | \n",
" 248,000 | \n",
" 248,000 | \n",
" 248,000 | \n",
" 248,000 | \n",
" 248,000 | \n",
" 248,000 | \n",
" 248,000 | \n",
" 248,000 | \n",
" 248,000 | \n",
" 248,000 | \n",
" 248,000 | \n",
" 248,000 | \n",
"
\n",
" \n",
" | Free Cash Flow (€) | \n",
" -6,231,000 | \n",
" 2,362,361 | \n",
" 2,362,361 | \n",
" 2,362,361 | \n",
" 2,362,361 | \n",
" 2,362,361 | \n",
" 2,362,361 | \n",
" 2,362,361 | \n",
" 2,362,361 | \n",
" 2,362,361 | \n",
" 2,362,361 | \n",
" 2,362,361 | \n",
" 2,362,361 | \n",
"
\n",
" \n",
" | Simple Payback Period | \n",
" 2.6 years | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
"
\n",
" \n",
" | IRR (%) | \n",
" 37% | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
"
\n",
" \n",
" | WACC (%) | \n",
" 10% | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
"
\n",
" \n",
" | NPV of explicit period (€) | \n",
" 8,968,545 | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
"
\n",
" \n",
" | Discounted residual value (€) | \n",
" 1,037,143 | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
"
\n",
" \n",
" | NPV (€) | \n",
" 10,005,689 | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
" | \n",
"
\n",
" \n",
"
\n",
"
\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[43mebitda_report\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mshow\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcomparison\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mrelative\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n",
"\u001b[1;31mTypeError\u001b[0m: show() got an unexpected keyword argument 'comparison'"
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}
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"source": [
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"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": 85,
"metadata": {
"tags": [
"exclude"
]
},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"marker": {
"color": "rgba(70, 165, 121, 0.6)",
"line": {
"color": "rgba(70, 165, 121, 1.0)",
"width": 1
}
},
"name": "NPV",
"orientation": "v",
"text": [
10.005688622020363,
9.687194002381743
],
"textposition": "outside",
"texttemplate": "%{text:.1f}M €",
"type": "bar",
"x": [
"Heatpump only",
"Heatpump + Storage"
],
"y": [
10005688.622020364,
9687194.002381742
]
}
],
"layout": {
"height": 400,
"legend": {
"bgcolor": "#F5F6F9",
"font": {
"color": "#4D5663"
}
},
"paper_bgcolor": "#F5F6F9",
"plot_bgcolor": "#F5F6F9",
"template": {
"data": {
"bar": [
{
"error_x": {
"color": "#2a3f5f"
},
"error_y": {
"color": "#2a3f5f"
},
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
},
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "bar"
}
],
"barpolar": [
{
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
},
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "barpolar"
}
],
"carpet": [
{
"aaxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"baxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"type": "carpet"
}
],
"choropleth": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "choropleth"
}
],
"contour": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "contour"
}
],
"contourcarpet": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "contourcarpet"
}
],
"heatmap": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "heatmap"
}
],
"heatmapgl": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "heatmapgl"
}
],
"histogram": [
{
"marker": {
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "histogram"
}
],
"histogram2d": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"_series = SingleFigureComparison(s.optcases, 'npv', label='NPV').report\n",
"\n",
"npv_graph = _series.iplot(\n",
" kind='bar',\n",
" title='NPV by Casestudy in €',\n",
" colors=recoygreen,\n",
" dimensions=(600, 400), \n",
" yTitle='NPV in €',\n",
" asFigure=True,\n",
" yrange=[0, _series.max() * 1.1]\n",
")\n",
"\n",
"npv_graph.update_traces(\n",
" text=_series.values/1000_000, \n",
" textposition='outside', \n",
" texttemplate=\"%{text:.1f}M €\", \n",
")\n",
"\n",
"npv_graph"
]
},
{
"cell_type": "code",
"execution_count": 86,
"metadata": {
"tags": [
"exclude"
]
},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"marker": {
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"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": 87,
"metadata": {
"tags": [
"exclude"
]
},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"marker": {
"color": "rgba(70, 165, 121, 0.6)",
"line": {
"color": "rgba(70, 165, 121, 1.0)",
"width": 1
}
},
"name": "Simple Payback Time",
"orientation": "v",
"text": [
2.6,
2.8
],
"textposition": "outside",
"texttemplate": "%{text:.1f} years",
"type": "bar",
"x": [
"Heatpump only",
"Heatpump + Storage"
],
"y": [
2.6,
2.8
]
}
],
"layout": {
"height": 400,
"legend": {
"bgcolor": "#F5F6F9",
"font": {
"color": "#4D5663"
}
},
"paper_bgcolor": "#F5F6F9",
"plot_bgcolor": "#F5F6F9",
"template": {
"data": {
"bar": [
{
"error_x": {
"color": "#2a3f5f"
},
"error_y": {
"color": "#2a3f5f"
},
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
},
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "bar"
}
],
"barpolar": [
{
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
},
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "barpolar"
}
],
"carpet": [
{
"aaxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"baxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"type": "carpet"
}
],
"choropleth": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "choropleth"
}
],
"contour": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"_series = (SingleFigureComparison(s.optcases, 'spp', label='Simple Payback Time').report)\n",
"spt_fig = _series.iplot(\n",
" kind='bar',\n",
" title='Simple Payback Time by Casestudy in Years',\n",
" colors=recoygreen,\n",
" dimensions=(600, 400),\n",
" yTitle='Years',\n",
" asFigure=True,\n",
" yrange=[0, _series.max() * 1.2]\n",
")\n",
"\n",
"spt_fig.update_traces(\n",
" text=_series.values, \n",
" textposition='outside', \n",
" texttemplate=\"%{text:.1f} years\", \n",
")\n",
"\n",
"spt_fig "
]
},
{
"cell_type": "code",
"execution_count": 88,
"metadata": {
"tags": [
"exclude"
]
},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"marker": {
"color": "rgba(70, 165, 121, 0.6)",
"line": {
"color": "rgba(70, 165, 121, 1.0)",
"width": 1
}
},
"name": "COP",
"orientation": "v",
"text": [
5.451794715081109,
5.582117337299301
],
"textposition": "outside",
"texttemplate": "%{text:.1f}",
"type": "bar",
"x": [
"Heatpump only",
"Heatpump + Storage"
],
"y": [
5.451794715081109,
5.582117337299301
]
}
],
"layout": {
"height": 400,
"legend": {
"bgcolor": "#F5F6F9",
"font": {
"color": "#4D5663"
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oj1o55yZAgAABAgQIECBAgAABAgQIECBAgACBIgIW5UUYBSFAgAABAgQIECBAgAABAgQIECBAgACBqAIW5VEr59wECBAgQIAAAQIECBAgQIAAAQIECBAgUETAorwIoyAECBAgQIAAAQIECBAgQIAAAQIECBAgEFXAojxq5ZybAAECBAgQIECAAAECBAgQIECAAAECBIoIWJQXYRSEAAECBAgQIECAAAECBAgQIECAAAECBKIKWJRHrZxzEyBAgAABAgQIECBAgAABAgQIECBAgEARAYvyIoyCECBAgAABAgQIECBAgAABAgQIECBAgEBUAYvyqJVzbgIECBAgQIAAAQIECBAgQIAAAQIECBAoImBRXoRREAIECBAgQIAAAQIECBAgQIAAAQIECBCIKmBRHrVyzk2AAAECBAgQIECAAAECBAgQIECAAAECRQQsyoswCkKAAAECBAgQIECAAAECBAgQIECAAAECUQUsyqNWzrkJECBAgAABAgQIECBAgAABAgQIECBAoIiARXkRRkEIECBAgAABAgQIECBAgAABAgQIECBAIKqARXnUyjk3AQIECBAgQIAAAQIECBAgQIAAAQIECBQRsCgvwigIAQIECBAgQIAAAQIECBAgQIAAAQIECEQVsCiPWjnnJkCAAAECBAgQIECAAAECBAgQIECAAIEiAhblRRgFIUCAAAECBAgQIECAAAECBAgQIECAAIGoAhblUSvn3AQIECBAgAABAgQIECBAgAABAgQIECBQRMCivAijIAQIECBAgAABAgQIECBAgAABAgQIECAQVcCiPGrlnJsAAQIECBAgQIAAAQIECBAgQIAAAQIEighYlBdhFIQAAQIECBAgQIAAAQIECBAgQIAAAQIEogpYlEetnHMTIECAAAECBAgQIECAAAECBAgQIECAQBEBi/IijIIQIECAAAECBAgQIECAAAECBAgQIECAQFQBi/KolXNuAgQIECBAgAABAgQIECBAgAABAgQIECgiYFFehFEQAgQIECBAgAABAgQIECBAgAABAgQIEIgqYFEetXLOTYAAAQIECBAgQIAAAQIECBAgQIAAAQJFBCzKizAKQoAAAQIECBAgQIAAAQIECBAgQIAAAQJRBSzKo1bOuQkQIECAAAECBAgQIECAAAECBAgQIECgiIBFeRFGQQgQIECAAAECBAgQIECAAAECBAgQIEAgqoBFedTKOTcBAgQIECBAgAABAgQIECBAgAABAgQIFBGwKC/CKAgBAgQIrBP487vuHb7+rNMBESBAgAABAgQIEDhlAT3lKdP5IAECBAhsKGBRviGUywgQIEDg1AQMNafm5lMECBAgQIAAAQL3C+gpPQ0ECBAgUFvAory2sPgECBDoXMBQ0/kDIH0CBAgQIECAQAEBPWUBRCEIECBAYF8Bi3IPCAECBAhUFTDUVOUVnAABAgQIECDQhYCesosyS5IAAQI7FbAo3ym/mxMgQCC/gKEmf41lSIAAAQIECBCoLaCnrC0sPgECBAhYlHsGCBAgQKCqgKGmKq/gBAgQIECAAIEuBPSUXZRZkgQIENipgEX5TvndnAABAvkFDDX5ayxDAgQIECBAgEBtAT1lbWHxCRAgQMCi3DNAgAABAlUFDDVVeQUnQIAAAQIECHQhoKfsosySJECAwE4FLMp3yu/mBAgQyC9gqMlfYxkSIECAAAECBGoL6ClrC4tPgAABAhblngECBAgQqCpgqKnKKzgBAgQIECBAoAsBPWUXZZYkAQIEdipgUb5TfjcnQIBAfgFDTf4ay5AAAQIECBAgUFtAT1lbWHwCBAgQsCj3DBAgQIBAVQFDTVVewQkQIECAAAECXQjoKbsosyQJECCwUwGL8p3yuzkBAgTyCxhq8tdYhgQIECBAgACB2gJ6ytrC4hMgQICARblngAABAgSqChhqqvIKToAAAQIECBDoQkBP2UWZJUmAAIGdCliU75TfzQkQIJBfwFCTv8YyJECAAAECBAjUFtBT1hYWnwABAgQsyj0DBAgQIFBVwFBTlVdwAgQIECBAgEAXAnrKLsosSQIECOxUwKJ8p/xuToAAgfwChpr8NZYhAQIECBAgQKC2gJ6ytrD4BAgQIGBR7hkgQIAAgaoChpqqvIITIECAAAECBLoQ0FN2UWZJEiBAYKcCFuUb8l98yeV7V170zGcMFz/nWRt+0mUECBDoW8BQ03f9ZU+AAAECBAgQKCGgpyyhKAYBAgQI7CdgUX7A8/GR224fXnHsNYPluP+QCBAgcGoChppTc/MpAgQIECBAgACB+wX0lJ4GAgQIEKgtYFF+gPCxV189POqsM4crXnhJ7VqIT4AAgZQChpqUZZUUAQIECBAgQKCowE//u9cNv/GOP3hAzD/8zV8+8e/W9ZTf/oM/vveZf/Yj/2C47MeeXfRcghEgQIBAPwIW5QfUenzlytedfvrwmXvv3bvylUdfOjzhcef285TIlAABAocQsCg/BJ6PEiBAgAABAgQ6ERgX5bd8+BPDf7vuZ1ZmvNxT/q8/vX245EU/N1iOd/KASJMAAQIzCFiU74M8vXblshc8f7jwgvNPXHnNdceHd7/3puGG49ee+Oe//OznZyiTWxAgQCCuwOc+/8XhEQ9/aNwEnJwAAQIECBAgQKC6wKv+w38ebr3tk8Pxq69cea/lnvLFP/OLw9c/6ozhyn/1Y9XP5gYECBCIIvC1j3x4lKM2eU6L8n3KMi3Kl79BPn7LfFqef+6vvthkYR2KAAECrQj85ec+P3ztI/wf61bq4RwECBAgQIAAgRYF/s2//5Xh7e+8ae9oZ55x+vCW4/9275+Xe8oL/uG/GMZr7v70/X/7+7qrXjp8yxMf22J6zkSAAIFZBB7xNb6kdhhoi/ID9BaX4tOlq/7dYYrgswQIEIgssO37JA+6PrKFsxMgQIAAAQIECJQR+Ecv/JkTgaZXsSy+emV67cpPv/iS4Ye+76//9vfUY07vNC9zClEIECBAoCcBi/IDqj3+MM8/++Sdw/XXXHXiyvHVKx/80M17/9zTwyJXAgQIrBLY9n2SB11PmQABAgQIECBAgMCv//Z7hn/988eHVT/Mc1qUH7/6J4e/9c33//yw8Qd7Li7PKRIgQIAAgW0ELMo30BqX5TffcuuJK8cf7DktzTf4qEsIECCQXuCgxffyD1466Pr0YBIkQIAAAQIECBA4UGC/Rfn44VVLcYvyA1ldQIAAAQL7CFiUezwIECBA4FACy69SOeur74r8rRt+fi/mqkX5b7zjD/Z+f/n6Qx3GhwkQIECAAAECBEIKfP/FLz6phxz/+fHnnjP8x597yYl8fvjSo8ODH/SgvVex/POffO3w0dvv2PvM2JO+931/clKMkBAOTYAAAQI7E7Ao3xm9GxMgQCCnwH7vk1yV8fL1OVVkRYAAAQIECBAgsJ/A2BPe9ok79y75tqd+896SfNWifPx347L8fR/40xOf8eULzxcBAgQIHFbAovywgj5PgAABAicJHPTXZJe5lq/HSYAAAQIECBAgQGBZYPlvKRIiQIAAAQKlBSzKS4uKR4AAgc4FLMo7fwCkT4AAAQIECBCoIGBRXgFVSAIECBA4ScCi3ANBgAABAocS2PZ9kgddf6jD+DABAgQIECBAgEBKAYvylGWVFAECBJoSsChvqhwOQ4AAgXgC275P8qDr4wk4MQECBAgQIECAQG0Bi/LawuITIECAgEW5Z4AAAQIEqgoYaqryCk6AAAECBAgQ6EJAT9lFmSVJgACBnQpYlO+U380JECCQX8BQk7/GMiRAgAABAgQI1BbQU9YWFp8AAQIELMo9AwQIECBQVcBQU5VXcAIECBAgQIBAFwJ6yi7KLEkCBAjsVMCifKf8bk6AAIH8Aoaa/DWWIQECBEoI/I//c8vwK3/yW8N9991XIpwYBAgkE/jyl+8bHvzg05JlJR0CBEoInHbaacM/+dvfP3zn33xyiXBidCxgUd5x8aVOgACBOQQsyudQdg8CBAjEF/itj71vePOH3zM89sij4ycjAwIEigt8/gtfGh7+sIcUjysgAQLxBT52z6eGZz/x/OH7H/tt8ZORwU4FLMp3yu/mBAgQyC9gUZ6/xjIkQIBACYFxUf6bt71veNJZ31AinBgECCQT+KsvfHH4moc9NFlW0iFAoITArXd9cvjBx32bRXkJzM5jWJR3/gBInwABArUFLMprC4tPgACBHAIW5TnqKAsCtQQsymvJiksgvoBFefwatpKBRXkrlQh8jo/efefw+3/2x94nGbiGjk6gpsDnPv/F4REP9+2fmsZiE4gqML5P8ru/8e8Mjz/z7KgpOHdBAYvygphCEUgoYFGesKhSIlBIwKK8EKQwg0W5h+DQAuNQc8P/fufwNx551qFjCUCAQD6BL37py8NDH/LgfInJiACBQwv838/eNVz8LRf6a7KHlswRwKI8Rx1lQaCWgEV5LVlxCcQXsCiPX8NWMrAob6USgc9hqAlcPEcnMIOAoWYGZLcgEFTAUBO0cJWOraesBCssgSQCesokhZQGgQoCesoKqJ2GtCjvtPAl0zbUlNQUi0A+AUNNvprKiEApAUNNKckccfSUOeooCwK1BPSUtWTFJRBfQE8Zv4atZGBR3kolAp/DUBO4eI5OYAYBQ80MyG5BIKiAoSZo4SodW09ZCVZYAkkE9JRJCikNAhUE9JQVUDsNaVHeaeFLpm2oKakpFoF8AoaafDWVEYFSAoaaUpI54ugpc9RRFgRqCegpa8mKSyC+gJ4yfg1bycCivJVKBD6HoSZw8RydwAwChpoZkN2CQFABQ03QwlU6tp6yEqywBJII6CmTFFIaBCoI6CkroHYa0qK808KXTNtQU1JTLAL5BAw1+WoqIwKlBAw1pSRzxNFT5qijLAjUEtBT1pIVl0B8AT1l/Bq2koFFeSuVCHwOQ03g4jk6gRkEDDUzILsFgaAChpqghat0bD1lJVhhCSQR0FMmKaQ0CFQQ0FNWQO00pEV5p4UvmbahpqSmWATyCRhq8tVURgRKCRhqSknmiKOnzFFHWRCoJaCnrCUrLoH4AnrK+DVsJQOL8lYqEfgchprAxXN0AjMIGGpmQHYLAkEFDDVBC1fp2HrKSrDCEkgioKdMUkhpEKggoKesgNppSIvyTgtfMm1DTUlNsQjkEzDU5KupjAiUEjDUlJLMEUdPmaOOsiBQS0BPWUtWXALxBfSU8WvYSgYW5a1UIvA5DDWBi+foBGYQMNTMgOwWBIIKGGqCFq7SsfWUlWCFJZBEQE+ZpJDSIFBBQE9ZAbXTkBblnRa+ZNqGmpKaYhHIJ2CoyVdTGREoJWCoKSWZI46eMkcdZUGgloCespasuATiC+gp49ewlQwsylupROBzGGoCF8/RCcwgYKiZAdktCAQVMNQELVylY+spK8EKSyCJgJ4ySSGlQaCCgJ6yAmqnIS3KOy18ybQNNSU1xSKQT8BQk6+mMiJQSsBQU0oyRxw9ZY46yoJALQE9ZS1ZcQnEF9BTxq9hKxlYlLdSicDnMNQELp6jE5hBwFAzA7JbEAgqYKgJWrhKx9ZTVoIVlkASAT1lkkJKg0AFAT1lBdROQ1qUd1r4kmkbakpqikUgn4ChJl9NZUSglIChppRkjjh6yhx1lAWBWgJ6ylqy4hKIL6CnjF/DVjKwKG+lEoHPYagJXDxHJzCDgKFmBmS3IBBUwFATtHCVjq2nrAQrLIEkAnrKJIWUBoEKAnrKCqidhrQo77TwJdM21JTUFItAPgFDTb6ayohAKQFDTSnJHHH0lDnqKAsCtQT0lLVkxSUQX0BPGb+GrWRgUd5KJQKfw1ATuHiOTmAGAUPNDMhuQSCogKEmaOEqHVtPWQlWWAJJBPSUSQopDQIVBPSUFVA7DWlR3mnhS6ZtqCmpKRaBfAKGmnw1lRGBUgKGmlKSOeLoKXPUURYEagnoKWvJiksgvoCeMn4NW8nAoryVSgQ+h6EmcPEcncAMAoaaGfzOcaYAACAASURBVJDdgkBQAUNN0MJVOraeshKssASSCOgpkxRSGgQqCOgpK6B2GtKivNPCl0zbUFNSUywC+QQMNflqKiMCpQQMNaUkc8TRU+aooywI1BLQU9aSFZdAfAE9ZfwatpKBRXkrlQh8DkNN4OI5OoEZBAw1MyC7BYGgAoaaoIWrdGw9ZSVYYQkkEdBTJimkNAhUENBTVkDtNKRFeaeFL5m2oaakplgE8gkYavLVVEYESgkYakpJ5oijp8xRR1kQqCWgp6wlKy6B+AJ6yvg1bCUDi/JWKhH4HIaawMVzdAIzCBhqZkB2CwJBBQw1QQtX6dh6ykqwwhJIIqCnTFJIaRCoIKCnrIDaaUiL8k4LXzJtQ01JTbEI5BMw1OSrqYwIlBIw1JSSzBFHT5mjjrIgUEtAT1lLVlwC8QX0lPFr2EoGFuWtVCLwOQw1gYvn6ARmEDDUzIDsFgSCChhqghau0rH1lJVghSWQREBPmaSQ0iBQQUBPWQG105AW5Z0WvmTahpqSmmIRyCdgqMlXUxkRKCVgqCklmSOOnjJHHWVBoJaAnrKWrLgE4gvoKePXsJUMLMpbqUTgcxhqAhfP0QnMIGComQHZLQgEFTDUBC1cpWPrKSvBCksgiYCeMkkhpUGggoCesgJqpyEtyjstfMm0DTUlNcUikE/AUJOvpjIiUErAUFNKMkccPWWOOsqCQC0BPWUtWXEJxBfQU8avYSsZWJS3UonA5zDUBC6eoxOYQcBQMwOyWxAIKmCoCVq4SsfWU1aCFZZAEgE9ZZJCSoNABQE9ZQXUTkNalHda+JJpG2pKaopFIJ+AoSZfTWVEoJSAoaaUZI44esocdZQFgVoCespasuISiC+gp4xfw1YysChvpRKBz2GoCVw8Rycwg4ChZgZktyAQVMBQE7RwlY6tp6wEKyyBJAJ6yiSFlAaBCgJ6ygqonYa0KO+08CXTNtSU1BSLQD4BQ02+msqIQCkBQ00pyRxx9JQ56igLArUE9JS1ZMUlEF9ATxm/hq1kYFHeSiUCn8NQE7h4jk5gBgFDzQzIbkEgqIChJmjhKh1bT1kJVlgCSQT0lEkKKQ0CFQT0lBVQOw1pUd5p4UumbagpqSkWgXwChpp8NZURgVIChppSkjni6Clz1FEWBGoJ6ClryYpLIL6AnjJ+DVvJwKK8lUoEPoehJnDxHJ3ADAKGmhmQ3YJAUAFDTdDCVTq2nrISrLAEkgjoKZMUUhoEKgjoKSugdhrSorzTwpdM21BTUlMsAvkEDDX5aiojAqUEDDWlJHPE0VPmqKMsCNQS0FPWkhWXQHwBPWX8GraSgUV5K5UIfA5DTeDiOTqBGQQMNTMguwWBoAKGmqCFq3RsPWUlWGEJJBHQUyYppDQIVBDQU1ZA7TSkRXmnhS+ZtqGmpKZYBPIJGGry1VRGBEoJGGpKSeaIo6fMUUdZEKgloKesJSsugfgCesr4NWwlA4vyVioR+ByGmsDFc3QCMwgYamZAdgsCQQUMNUELV+nYespKsMISSCKgp0xSSGkQqCCgp6yA2mlIi/JOC18ybUNNSU2xCOQTMNTkq6mMCJQSMNSUkswRR0+Zo46yIFBLQE9ZS1ZcAvEF9JTxa9hKBhblW1Tihje9ZbjxrW8bLnvB84cLLzh/i0/mvtRQk7u+siNwWAFDzWEFfZ5AXgFDTd7ankpmespTUfMZAv0I6Cn7qbVMCWwroKfcVsz16wQsyjd8NsYl+Tt+793DZ+6916J8ycxQs+FD5DICnQoYajotvLQJbCBgqNkAqaNL9JQdFVuqBE5BQE95Cmg+QqATAT1lJ4WeIU2L8g2QpyX59ddcNVx8yeUW5RblGzw1LiFAYBIw1HgWCBBYJ2Co8WwsCliUex4IENhPQE/p+SBAQE/pGagtYFF+gPDikny81KL8gWCGmtr/mYpPILaAoSZ2/ZyeQE0Bi/KauvFi6ynj1cyJCcwpoKecU9u9CMQS0FPGqlfLp7Uo36c6y0vyVYvyuz792ZbrO8vZfv/ODwy/e8cHhsd93dmz3M9NCBCIJXDfcN9w2lf/n18ECBBYFrjtM3cOf++cpw7fffZT4RAY9JQeAgIE9hPQU3o+CBBYJ6CnvF/mrDMe6UE5hIBF+T54x1599XDzLbeuvOKiZz5juPg5zxq+/JWvHII/x0d/+2PvH97+1f898axzciQkCwIEigp8/gtfGh7+sIcUjSkYAQI5BD581x3DDzz2acP3ffV/fhHQU3oGCBDYT0BP6fkgQGCdgJ7yfpkHP+hBHpRDCFiUb4nn1SsPBPPXZLd8iFxOoDMBf022s4JLl8AWAv6a7BZYHVyqp+ygyFIkcAgBPeUh8HyUQHIBPWXyAs+YnkX5ltgW5RblWz4yLifQvYChpvtHAACBtQKGGg/HooBFueeBAIH9BPSUng8CBNYJ6Ck9G6UELMq3lLQotyjf8pFxOYHuBQw13T8CAAhYlHsGNhKwKN+IyUUEuhXQU3ZbeokTOFDAovxAIhdsKGBRviGUy9YLGGo8HQQI7CdgqPF8ECCwTsBQ49lYFNBTeh4IENBTegYIEDgVAT3lqaj5zCoBi3LPxaEFDDWHJhSAQGoBi/LU5ZUcgUMJGGoOxZfuw3rKdCWVEIGiAnrKopyCEUgloKdMVc6dJmNRvlP+HDc31OSooywI1BIw1NSSFZdAfAFDTfwalsxAT1lSUywC+QT0lPlqKiMCpQT0lKUkxWlyUX7s1VcPN99y64nqnPfkJw1HX/4ilWpYwFDTcHEcjUADAoaaBorgCAQaFTDUNFqYHR1LT7kjeLclEERATxmkUI5JYAcCesodoCe9ZXOL8muuOz588EM3D9dfc9UJ8pdceWw448gRy/KGH0BDTcPFcTQCDQgYahoogiMQaFTAUNNoYXZ0LD3ljuDdlkAQAT1lkEI5JoEdCOgpd4Ce9JbNLcovveJlw/d+z9OHi5/zrBPkH7nt9uEVx14z3HD82qQliJ+WoSZ+DWVAoKaAoaamrtgEYgsYamLXr/Tp9ZSlRcUjkEtAT5mrnrIhUFJAT1lSs+9YzS3KL77k8uGyFzx/uPCC8/cqs+rf9V22trI31LRVD6ch0JqAoaa1ijgPgXYEDDXt1KKFk+gpW6iCMxBoV0BP2W5tnIzArgX0lLuuQJ77W5TnqeXOMjHU7IzejQmEEDDUhCiTQxLYiYChZifszd5UT9lsaRyMQBMCesomyuAQBJoU0FM2WZaQh7IoD1m2tg5tqGmrHk5DoDUBQ01rFXEeAu0IGGraqUULJ9FTtlAFZyDQroCest3aOBmBXQvoKXddgTz3b3JRvgmvd5ZvojTPNYaaeZzdhUBUAUNN1Mo5N4H6Aoaa+saR7qCnjFQtZyUwv4Cecn5zdyQQRUBPGaVS7Z+zuUV5+2ROuCxgqPFMECCwn4ChxvNBgMA6AUONZ2NRQE/peSBAQE/pGSBA4FQE9JSnouYzqwQsyj0XhxYw1ByaUAACqQUsylOXV3IEDiVgqDkUX7oP6ynTlVRCBIoK6CmLcgpGIJWAnjJVOXeaTLOL8mOvvnq4+ZZbT8I578lPGo6+/EU7BXPzBwoYajwVBAjsJ2Co8XwQILBOwFDj2VgU0FN6HggQ0FN6BggQOBUBPeWpqPnMKoEmF+UXX3L5cM7Zjx5e+6qjJ535JVceG+6481OD95O39TAbatqqh9MQaE3Aory1ijgPgXYEDDXt1KKFk+gpW6iCMxBoV0BP2W5tnIzArgX0lLuuQJ77N7coH79J/ul77nnAknwiH5flZxw54pvlDT2DhpqGiuEoBBoUMNQ0WBRHItCIgKGmkUI0cgw9ZSOFcAwCjQroKRstjGMRaEBAT9lAEZIcoblF+aVXvGx43nMvGi684PyVxO9813uGN7zxxuH6a65KUoL4aRhq4tdQBgRqChhqauqKTSC2gKEmdv1Kn15PWVpUPAK5BPSUueopGwIlBfSUJTX7jtXconx87cplL3j+vovyX3rd671+paHn1lDTUDEchUCDAoaaBoviSAQaETDUNFKIRo6hp2ykEI5BoFEBPWWjhXEsAg0I6CkbKEKSIzS3KPeN8nhPlqEmXs2cmMCcAoaaObXdi0AsAUNNrHrVPq2esraw+ARiC+gpY9fP6QnUFNBT1tTtK3Zzi3LvKI/3ABpq4tXMiQnMKWComVPbvQjEEjDUxKpX7dPqKWsLi08gtoCeMnb9nJ5ATQE9ZU3dvmI3tygf+cfXr5xz9qMf8AM9xx/kecedn/LalcaeUUNNYwVxHAKNCRhqGiuI4xBoSMBQ01AxGjiKnrKBIjgCgYYF9JQNF8fRCOxYQE+54wIkun2Ti/LRd/xm+c233HoS9XlPftJw9OUvSsSfIxVDTY46yoJALQFDTS1ZcQnEFzDUxK9hyQz0lCU1xSKQT0BPma+mMiJQSkBPWUpSnGYX5UoTR8BQE6dWTkpgFwKGml2ouyeBGAKGmhh1muuUesq5pN2HQEwBPWXMujk1gTkE9JRzKPdxD4vyPupcNUtDTVVewQmEFzDUhC+hBAhUEzDUVKMNGVhPGbJsDk1gNgE95WzUbkQgnICeMlzJmj1wc4vyG970luHGt75tuOiZzxgufs6zToLb7/eaFe7gYIaaDoosRQKHEDDUHALPRwkkFzDUJC/wlunpKbcEczmBzgT0lJ0VXLoEthDQU26B5dJ9BZpblI8/sPOMI0fWvot8fHf5p++55wE/6FOddydgqNmdvTsTiCBgqIlQJWcksBsBQ81u3Fu9q56y1co4F4E2BPSUbdTBKQi0KKCnbLEqMc/U3KL84ksuHy57wfOHCy84f6XoO9/1nuGXXvf64Ybj18YUT3hqQ03CokqJQEEBQ01BTKEIJBMw1CQr6CHT0VMeEtDHCSQX0FMmL7D0CBxCQE95CDwfPUnAotwDcWgBQ82hCQUgkFrAUJO6vJIjcCgBQ82h+NJ9WE+ZrqQSIlBUQE9ZlFMwAqkE9JSpyrnTZJpblF96xcuG5z33on2/Uf6GN944XH/NVTuFc/P7BQw1ngYCBPYTMNR4PggQWCdgqPFsLAroKT0PBAjoKT0DBAicioCe8lTUfGaVQHOL8muuOz7c/vFPrH0H+UHvMFfm+QUMNfObuyOBSAIW5ZGq5awE5hUw1Mzr3frd9JStV8j5COxWQE+5W393J9CygJ6y5erEOltzi/KRb/xW+fhr+Vvj47//zL33ej95Y8+YoaaxgjgOgcYEDDWNFcRxCDQkYKhpqBgNHEVP2UARHIFAwwJ6yoaL42gEdiygp9xxARLdvslF+eg7frP83e+96STq8578pOHoy1+UiD9HKoaaHHWUBYFaAoaaWrLiEogvYKiJX8OSGegpS2qKRSCfgJ4yX01lRKCUgJ6ylKQ4zS7KlSaOgKEmTq2clMAuBAw1u1B3TwIxBAw1Meo01yn1lHNJuw+BmAJ6yph1c2oCcwjoKedQ7uMeFuV91LlqloaaqryCEwgvYKgJX0IJEKgmYKipRhsysJ4yZNkcmsBsAnrK2ajdiEA4AT1luJI1e2CL8mZLE+dghpo4tXJSArsQMNTsQt09CcQQMNTEqNNcp9RTziXtPgRiCugpY9bNqQnMIaCnnEO5j3tYlPdR56pZGmqq8gpOILyAoSZ8CSVAoJqAoaYabcjAesqQZXNoArMJ6Clno3YjAuEE9JThStbsgS3Kmy1NnIMZauLUykkJ7ELAULMLdfckEEPAUBOjTnOdUk85l7T7EIgpoKeMWTenJjCHgJ5yDuU+7mFR3kedq2ZpqKnKKziB8AKGmvAllACBagKGmmq0IQPrKUOWzaEJzCagp5yN2o0IhBPQU4YrWbMHtihvtjRxDmaoiVMrJyWwCwFDzS7U3ZNADAFDTYw6zXVKPeVc0u5DIKaAnjJm3ZyawBwCeso5lPu4h0V5H3WumqWhpiqv4ATCCxhqwpdQAgSqCRhqqtGGDKynDFk2hyYwm4CecjZqNyIQTkBPGa5kzR7YorzZ0sQ5mKEmTq2clMAuBAw1u1B3TwIxBAw1Meo01yn1lHNJuw+BmAJ6yph1c2oCcwjoKedQ7uMeFuV91LlqloaaqryCEwgvYKgJX0IJEKgmYKipRhsysJ4yZNkcmsBsAnrK2ajdiEA4AT1luJI1e2CL8mZLE+dghpo4tXJSArsQMNTsQt09CcQQMNTEqNNcp9RTziXtPgRiCugpY9bNqQnMIaCnnEO5j3tYlPdR56pZGmqq8gpOILyAoSZ8CSVAoJqAoaYabcjAesqQZXNoArMJ6Clno3YjAuEE9JThStbsgS3Kmy1NnIMZauLUykkJ7ELAULMLdfckEEPAUBOjTnOdUk85l7T7EIgpoKeMWTenJjCHgJ5yDuU+7mFR3kedq2ZpqKnKKziB8AKGmvAllACBagKGmmq0IQPrKUOWzaEJzCagp5yN2o0IhBPQU4YrWbMHtihvtjRxDmaoiVMrJyWwCwFDzS7U3ZNADAFDTYw6zXVKPeVc0u5DIKaAnjJm3ZyawBwCeso5lPu4h0V5H3WumqWhpiqv4ATCCxhqwpdQAgSqCRhqqtGGDKynDFk2hyYwm4CecjZqNyIQTkBPGa5kzR7YorzZ0sQ5mKEmTq2clMAuBAw1u1B3TwIxBAw1Meo01yn1lHNJuw+BmAJ6yph1c2oCcwjoKedQ7uMeFuV91LlqloaaqryCEwgvYKgJX0IJEKgmYKipRhsysJ4yZNkcmsBsAnrK2ajdiEA4AT1luJI1e2CL8mZLE+dghpo4tXJSArsQMNTsQt09CcQQMNTEqNNcp9RTziXtPgRiCugpY9bNqQnMIaCnnEO5j3tYlPdR56pZGmqq8gpOILyAoSZ8CSVAoJqAoaYabcjAesqQZXNoArMJ6Clno3YjAuEE9JThStbsgS3Kmy1NnIMZauLUykkJ7ELAULMLdfckEEPAUBOjTnOdUk85l7T7EIgpoKeMWTenJjCHgJ5yDuU+7mFR3kedq2ZpqKnKKziB8AKGmvAllACBagKGmmq0IQPrKUOWzaEJzCagp5yN2o0IhBPQU4YrWbMHtihvtjRxDmaoiVMrJyWwCwFDzS7U3ZNADAFDTYw6zXVKPeVc0u5DIKaAnjJm3ZyawBwCeso5lPu4h0V5H3WumqWhpiqv4ATCCxhqwpdQAgSqCRhqqtGGDKynDFk2hyYwm4CecjZqNyIQTkBPGa5kzR7YorzZ0sQ5mKEmTq2clMAuBAw1u1B3TwIxBAw1Meo01yn1lHNJuw+BmAJ6yph1c2oCcwjoKedQ7uMeFuV91LlqloaaqryCEwgvYKgJX0IJEKgmYKipRhsysJ4yZNkcmsBsAnrK2ajdiEA4AT1luJI1e2CL8gNKc+zVVw8333Lr3lXnnP3o4bWvOtpsQXdxMEPNLtTdk0AcAUNNnFo5KYG5BQw1c4u3fT89Zdv1cToCuxbQU+66Au5PoF0BPWW7tYl2MovyAyp26RUvG66/5qq9q8Z/fsq3njdc8cJLotW62nkNNdVoBSaQQsBQk6KMkiBQRcBQU4U1bFA9ZdjSOTiBWQT0lLMwuwmBkAJ6ypBla/LQFuVbluWa644Pt3/8E75VvuBmqNnyIXI5gc4EDDWdFVy6BLYQMNRsgdXBpXrKDoosRQKHENBTHgLPRwkkF9BTJi/wjOlZlG+J/ZIrjw3nPuab9r5R/qUvf2XLCPku/52Pv39428fePzzxzHPyJScjAgQOLfCFL35peNhDH3LoOAIQIJBP4MN33zE847FPG/7+Y56WLzkZbS2gp9yazAcIdCWgp+yq3JIlsJWAnvJ+roc8+EFb2bn4ZAGL8i2eiPHb5O9+703DDcev3fvU3fd8dosIOS995x0fGH73q/97/JGzcyYoKwIEDiXwlfvuGx502mmHiuHDBAjkFPjoPXcOf++cpw4XfvV/fhHQU3oGCBDYT0BP6fkgQGCdgJ7yfpkzjzzSg3IIAYvyDfFueNNbhhvf+rbhlUdfOjzhcedu+Kk+LvPXZPuosywJnKqAvyZ7qnI+RyC/gL8mm7/G22Sop9xGy7UE+hPQU/ZXcxkT2FRAT7mplOsOErAoP0joq7+/6pvkG3ysm0sMNd2UWqIETknAUHNKbD5EoAsBQ00XZd44ST3lxlQuJNClgJ6yy7JLmsBGAnrKjZhctIGARfkBSOM7ycdfr33V0Q04+7zEUNNn3WVNYFMBQ82mUq4j0J+Aoaa/mu+XsZ7S80CAwH4CekrPBwEC6wT0lJ6NUgIW5ftIfuS224dXHHvNyisue8HzhwsvOL9UHULHMdSELp/DE6guYKipTuwGBMIKGGrClq7KwfWUVVgFJZBGQE+ZppQSIVBcQE9ZnLTbgBbl3Za+XOKGmnKWIhHIKGCoyVhVOREoI2CoKeOYJYqeMksl5UGgjoCeso6rqAQyCOgpM1SxjRwsytuoQ+hTGGpCl8/hCVQXMNRUJ3YDAmEFDDVhS1fl4HrKKqyCEkgjoKdMU0qJECguoKcsTtptQIvybktfLnFDTTlLkQhkFDDUZKyqnAiUETDUlHHMEkVPmaWS8iBQR0BPWcdVVAIZBPSUGarYRg4W5W3UIfQpDDWhy+fwBKoLGGqqE7sBgbAChpqwpatycD1lFVZBCaQR0FOmKaVECBQX0FMWJ+02oEV5t6Uvl7ihppylSAQyChhqMlZVTgTKCBhqyjhmiaKnzFJJeRCoI6CnrOMqKoEMAnrKDFVsIweL8jbqEPoUhprQ5XN4AtUFDDXVid2AQFgBQ03Y0lU5uJ6yCqugBNII6CnTlFIiBIoL6CmLk3Yb0KK829KXS9xQU85SJAIZBQw1GasqJwJlBAw1ZRyzRNFTZqmkPAjUEdBT1nEVlUAGAT1lhiq2kYNFeRt1CH0KQ03o8jk8geoChprqxG5AIKyAoSZs6aocXE9ZhVVQAmkE9JRpSikRAsUF9JTFSbsNaFHebenLJW6oKWcpEoGMAoaajFWVE4EyAoaaMo5Zougps1RSHgTqCOgp67iKSiCDgJ4yQxXbyMGivI06hD6FoSZ0+RyeQHUBQ011YjcgEFbAUBO2dFUOrqeswioogTQCeso0pZQIgeICesripN0GtCjvtvTlEjfUlLMUiUBGAUNNxqrKiUAZAUNNGccsUfSUWSopDwJ1BPSUdVxFJZBBQE+ZoYpt5GBR3kYdQp/CUBO6fA5PoLqAoaY6sRsQCCtgqAlbuioH11NWYRWUQBoBPWWaUkqEQHEBPWVx0m4DWpR3W/pyiRtqylmKRCCjgKEmY1XlRKCMgKGmjGOWKHrKLJWUB4E6AnrKOq6iEsggoKfMUMU2crAob6MOoU9hqAldPocnUF3AUFOd2A0IhBUw1IQtXZWD6ymrsApKII2AnjJNKSVCoLiAnrI4abcBLcq7LX25xA015SxFIpBRwFCTsapyIlBGwFBTxjFLFD1llkrKg0AdAT1lHVdRCWQQ0FNmqGIbOViUt1GH0Kcw1IQun8MTqC5gqKlO7AYEwgoYasKWrsrB9ZRVWAUlkEZAT5mmlBIhUFxAT1mctNuAFuXdlr5c4oaacpYiEcgoYKjJWFU5ESgjYKgp45glip4ySyXlQaCOgJ6yjquoBDII6CkzVLGNHCzK26hD6FMYakKXz+EJVBcw1FQndgMCYQUMNWFLV+XgesoqrIISSCOgp0xTSokQKC6gpyxO2m1Ai/JuS18ucUNNOUuRCGQUMNRkrKqcCJQRMNSUccwSRU+ZpZLyIFBHQE9Zx1VUAhkE9JQZqthGDhblbdQh9CkMNaHL5/AEqgsYaqoTuwGBsAKGmrClq3JwPWUVVkEJpBHQU6YppUQIFBfQUxYn7TagRXm3pS+XuKGmnKVIBDIKGGoyVlVOBMoIGGrKOGaJoqfMUkl5EKgjoKes4yoqgQwCesoMVWwjB4vyNuoQ+hSGmtDlc3gC1QUMNdWJ3YBAWAFDTdjSVTm4nrIKq6AE0gjoKdOUUiIEigvoKYuTdhvQorzb0pdL3FBTzlIkAhkFDDUZqyonAmUEDDVlHLNE0VNmqaQ8CNQR0FPWcRWVQAYBPWWGKraRg0V5G3UIfQpDTejyOTyB6gKGmurEbkAgrIChJmzpqhxcT1mFVVACaQT0lGlKKRECxQX0lMVJuw1oUd5t6cslbqgpZykSgYwChpqMVZUTgTIChpoyjlmi6CmzVFIeBOoI6CnruIpKIIOAnjJDFdvIwaK8jTqEPoWhJnT5HJ5AdQFDTXViNyAQVsBQE7Z0VQ6up6zCKiiBNAJ6yjSllAiB4gJ6yuKk3Qa0KO+29OUSN9SUsxSJQEYBQ03GqsqJQBkBQ00ZxyxR9JRZKikPAnUE9JR1XEUlkEFAT5mhim3kYFHeRh1Cn8JQE7p8Dk+guoChpjqxGxAIK2CoCVu6KgfXU1ZhFZRAGgE9ZZpSSoRAcQE9ZXHSbgNalHdb+nKJG2rKWYpEIKOAoSZjVeVEoIyAoaaMY5YoesoslZQHgToCeso6rqISyCCgp8xQxTZysChvow6hT2GoCV0+hydQXcBQU53YDQiEFTDUhC1dlYPrKauwCkogjYCeMk0pJUKguICesjhptwEtyrstfbnEDTXlLEUikFHAUJOxqnIiUEbAUFPGMUsUPWWWSsqDQB0BPWUdV1EJZBDQU2aoYhs5WJS3UYfQpzDUhC6fwxOoLmCoqU7sBgTCChhqwpauysH1lFVYBSWQRkBPmaaUEiFQXEBPWZy024AW5d2WvlzihppyliIRyChgqMlYVTkRKCNgqCnjmCWKnjJLJeVBoI6AnrKOq6gEMgjoKTNUsY0cLMrbqEPoUxhqQpfP4QlUFzDUVCd2AwJhBQw1YUtX5eB6yiqsghJII6CnTFNKiRAoLqCnLE7abUCL8m5LXy5xQ005S5EIZBQw1GSsqpwIlBEw1JRxzBJFT5mlkvIgUEdAT1nHVVQCGQT0lBmq2EYOFuVt1CH0KQw12b/XGwAAE5NJREFUocvn8ASqCxhqqhO7AYGwAoaasKWrcnA9ZRVWQQmkEdBTpimlRAgUF9BTFiftNqBFebelL5e4oaacpUgEMgoYajJWVU4EyggYaso4Zomip8xSSXkQqCOgp6zjKiqBDAJ6ygxVbCMHi/I26hD6FIaa0OVzeALVBQw11YndgEBYAUNN2NJVObiesgqroATSCOgp05RSIgSKC+gpi5N2G9CivNvSl0vcUFPOUiQCGQUMNRmrKicCZQQMNWUcs0TRU2appDwI1BHQU9ZxFZVABgE9ZYYqtpGDRXkbdQh9CkNN6PI5PIHqAoaa6sRuQCCsgKEmbOmqHFxPWYVVUAJpBPSUaUopEQLFBfSUxUm7DWhR3m3pyyVuqClnKRKBjAKGmoxVlROBMgKGmjKOWaLoKbNUUh4E6gjoKeu4ikogg4CeMkMV28jBoryNOoQ+haEmdPkcnkB1AUNNdWI3IBBWwFATtnRVDq6nrMIqKIE0AnrKNKWUCIHiAnrK4qTdBrQo77b05RI31JSzFIlARgFDTcaqyolAGQFDTRnHLFH0lFkqKQ8CdQT0lHVcRSWQQUBPmaGKbeRgUd5GHUKfwlATunwOT6C6gKGmOrEbEAgrYKgJW7oqB9dTVmEVlEAaAT1lmlJKhEBxAT1lcdJuA1qUd1v6cokbaspZikQgo4ChJmNV5USgjIChpoxjlih6yiyVlAeBOgJ6yjquohLIIKCnzFDFNnKwKG+jDqFPYagJXT6HJ1BdwFBTndgNCIQVMNSELV2Vg+spq7AKSiCNgJ4yTSklQqC4gJ6yOGm3AS3Kuy19ucQNNeUsRSKQUcBQk7GqciJQRsBQU8YxSxQ9ZZZKyoNAHQE9ZR1XUQlkENBTZqhiGzlYlLdRh9CnMNSELp/DE6guYKipTuwGBMIKGGrClq7KwfWUVVgFJZBGQE+ZppQSIVBcQE9ZnLTbgBbl3Za+XOKGmnKWIhHIKGCoyVhVOREoI2CoKeOYJYqeMksl5UGgjoCeso6rqAQyCOgpM1SxjRwsytuoQ+hTGGpCl8/hCVQXMNRUJ3YDAmEFDDVhS1fl4HrKKqyCEkgjoKdMU0qJECguoKcsTtptQIvybktfLnFDTTlLkQhkFDDUZKyqnAiUETDUlHHMEkVPmaWS8iBQR0BPWcdVVAIZBPSUGarYRg4W5W3UIfQpDDWhy+fwBKoLGGqqE7sBgbAChpqwpatycD1lFVZBCaQR0FOmKaVECBQX0FMWJ+02oEV5t6Uvl7ihppylSAQyChhqMlZVTgTKCBhqyjhmiaKnzFJJeRCoI6CnrOMqKoEMAnrKDFVsIweL8jbqEPoUhprQ5XN4AtUFDDXVid2AQFgBQ03Y0lU5uJ6yCqugBNII6CnTlFIiBIoL6CmLk3Yb0KK829KXS9xQU85SJAIZBQw1GasqJwJlBAw1ZRyzRNFTZqmkPAjUEdBT1nEVlUAGAT1lhiq2kYNFeRt1CH0KQ03o8jk8geoChprqxG5AIKyAoSZs6aocXE9ZhVVQAmkE9JRpSikRAsUF9JTFSbsNaFG+QelfcuWx4Y47P3XiynPOfvTw2lcd3eBT/VxiqOmn1jIlcCoChppTUfMZAn0IGGr6qPOmWeopN5VyHYE+BfSUfdZd1gQ2EdBTbqLkmk0ELMoPUDr26quHT99zz95yfFyan3HkyHD05S/axLeLaww1XZRZkgROWcBQc8p0PkggvYChJn2Jt0pQT7kVl4sJdCegp+yu5BImsLGAnnJjKhceIGBRfgDQpVe8bHjecy8aLrzg/BNXvvNd7xne8MYbh+uvucrD9f8FDDUeBQIE9hMw1Hg+CBBYJ2Co8WwsCugpPQ8ECOgpPQMECJyKgJ7yVNR8ZpWARfk+z8VHbrt9eMWx1wyvPPrS4QmPO/fElav+Xe+PlqGm9ydA/gT2F7Ao94QQIGBR7hnYREBPuYmSawj0K6Cn7Lf2MidwkIBF+UFCfn9TAYvyQy7K//yueze1Tnvdu+784PCWj79nOPNhp6fNUWIECBAgQIBAeYG7v3Dv8KzHnD9ccPZTygcXMZyAnjJcyRyYAAECBAg0IaCnvL8MX3+W3dxhHkqLcovywzw/PkuAAAECBAgQIECAAAECBAgQIECAQAMCFuWHK4JF+QF+3lF+uAfMpwkQIECAAAECBAgQIECAAAECBAgQINC6gEX5ARU69uqrh0/fc8/w2lcdPXHlS648Npxx5Mhw9OUvar22zkeAAAECBAgQIECAAAECBAgQIECAAAECGwhYlG+ANC7H77jzUyeuPOfsR+8tzTf4qEsIECBAoFGBd77rPcMvve71ww3Hr230hI5FgAABAgQIECBAgAABAgQIzCVgUT6XtPsQIEDgkALjq6Ce8q3nDVe88JK9SNdcd3y4/eOfKPYHeOM9vvd7nj5c/JxnHfK07X/corz9GjkhAQIECBAgcL+AXrDc03DxJZefFGzxC3E99cPlREUiQIBADgGL8hx1lAUBAh0IGI7KFtmivKynaAQIECBAgEBdAb1gGd9VjuPfIp9et2pRXsZZFAIECEQUsCiPWDVnJkCgS4FNh6PxW+bvfu9Ne0avPPrS4QmPO/fEP9/wprcMN771bXu/93Wnnz5cf81VJ/55/JkMN99y697vTd+sme67GPOyFzx/uPCC809cuzxMjPd4x++9ey/u+I2d8578pL3YT/+u7xj+4q679/55Odb4rfl191pV+MXXYy3ms3i2xZwnj8VF+Wj2wQ/dvHfm8bNj3HMf800nfYO/ywdP0gQIECBAgEATAnrB/csw9pwHvVLvI7fdPrzi2GuGxf54Meq6fnjqDadXsi73nOO9L3rmM/b67DH++/7nh9b23dM9F/vY8d8tx92vr2/ioXQIAgQIJBOwKE9WUOkQIJBXYJPhaHnhu7y0Hpv/xR9GPMb8xm84e+/frfoGzfjvxl/TQn1q2KdBZNNF+XjfaVE/LsvHV8gs/8Dkg+61XN3lz4///GefvHPvrGO8z9x7797QtHj98jfKxwFnWtpPQ9RBw1bep01mBAgQIECAQGsCesHDL8rHCKPjkSOnr3114ap++KCec+wjl5fcB/XdyzGX+/aD+vrWnk/nIUCAQAYBi/IMVZQDAQJdCExL3+Vkl9+p+LznXrT3be/x2sUF8PJnl99xvm5Rvvze8sWYmyzKlxfQ07d4lgeCVfff7/zLv7f8LaH9zra8KB+HlfHXuNBf/P938XBJkgABAgQIEGheQC/413+bcd2vTb5RPn12+R3l47fBp5/Rs0k/utxz7tevTvdc7ruXP7OqL96mr2/+AXZAAgQIBBCwKA9QJEckQIDAKLDJt4iWm/5Jbvn1JuO3rKdfB/3wooOGhV0tytf91dlNl/jLi/LFb5FvMux4KgkQIECAAAECcwroBU9elE+927oaLPa/+9Vp+huP0/XLve0mPee63nH5DzemvntVzFWvL1x17k3zmvPZdC8CBAhkEbAoz1JJeRAgkF5g0+Fov+Z5OYZvlL/+pHdZju+JnH5NP9Ap/YMlQQIECBAgQCCEgF6w3DfKlwu+uBw/6Esi42c3+Ub5QX33Qd8o98WNEP9ZOiQBAskELMqTFVQ6BAjkFdhkOFp+R/eoMf67H33us0/8QM/lhntaDE9L4fGfzzhy5AHvMV989cryPZY/s/ye8VXv/t701Sur8lms8EHvi9zm1Stj3OkbRYt//TbvEyUzAgQIECBAIJKAXnD/am3y6pXxbxS+9W2/c9L7yaf+b/rZNKv64YN6zlVL7W377vG+99xz797P2jmor4/07DorAQIEoghYlEeplHMSINC9wCbD0Yg0/bDNCWzxBwtNg8D0e+Nf/xx/TYvy6XUk47+b/mro8l8ZXf5BRct/7XX8QZ0f/NDNe03+tovyxdfCLN9r1UMwDhV33PmpE7+1fP22i3I/xLP7/8wAECBAgACBZgX0gvuXZpNF+RhhsXecIi7+APdV/fDy55Z7zlWL8oP67jHm4msTz3vyk4ZP33PPSUv8/fr6Zh9UByNAgEBgAYvywMVzdAIECMwhsOqvn9a675z3WpXD+M2dR5115nDFCy+plaK4BAgQIECAAIFQAnP2Z3Peq7Ui6ENbq4jzECDQo4BFeY9VlzMBAgS2EJhzYJnzXssE635Q0xZULiVAgAABAgQIpBOYsz+b8167LtTyt8Wnv82563O5PwECBHoWsCjvufpyJ0CAAAECBAgQIECAAAECBAgQIECAAIHBotxDQIAAAQIECBAgQIAAAQIECBAgQIAAAQJdC1iUd11+yRMgQIAAAQIECBAgQIAAAQIECBAgQICARblngAABAgQIECBAgAABAgQIECBAgAABAgS6FrAo77r8kidAgAABAgQIECBAgAABAgQIECBAgAABi3LPAAECBAgQIECAAAECBAgQIECAAAECBAh0LWBR3nX5JU+AAAECBAgQIECAAAECBAgQIECAAAECFuWeAQIECBAgQIAAAQIECBAgQIAAAQIECBDoWsCivOvyS54AAQIECBAgQIAAAQIECBAgQIAAAQIELMo9AwQIECBAgAABAgQIECBAgAABAgQIECDQtYBFedfllzwBAgQIECBAgAABAgQIECBAgAABAgQIWJR7BggQIECAAAECBAgQIECAAAECBAgQIECgawGL8q7LL3kCBAgQIECAAAECBAgQIECAAAECBAgQsCj3DBAgQIAAAQIECBAgQIAAAQIECBAgQIBA1wIW5V2XX/IECBAgQIAAAQIECBAgQIAAAQIECBAgYFHuGSBAgAABAgQIECBAgAABAgQIECBAgACBrgUsyrsuv+QJECBAgAABAgQIECBAgAABAgQIECBAwKLcM0CAAAECBAgQIECAAAECBAgQIECAAAECXQtYlHddfskTIECAAAECBAgQIECAAAECBAgQIECAgEW5Z4AAAQIECBAgQIAAAQIECBAgQIAAAQIEuhawKO+6/JInQIAAAQIECBAgQIAAAQIECBAgQIAAAYtyzwABAgQIECBAgAABAgQIECBAgAABAgQIdC1gUd51+SVPgAABAgQIECBAgAABAgQIECBAgAABAhblngECBAgQIECAAAECBAgQIECAAAECBAgQ6FrAorzr8kueAAECBAgQIECAAAECBAgQIECAAAECBCzKPQMECBAgQIAAAQIECBAgQIAAAQIECBAg0LWARXnX5Zc8AQIECBAgQIAAAQIECBAgQIAAAQIECFiUewYIECBAgAABAgQIECBAgAABAgQIECBAoGsBi/Kuyy95AgQIECBAgAABAgQIECBAgAABAgQIELAo9wwQIECAAAECBAgQIECAAAECBAgQIECAQNcCFuVdl1/yBAgQIECAAAECBAgQIECAAAECBAgQIGBR7hkgQIAAAQIECBAgQIAAAQIECBAgQIAAga4FLMq7Lr/kCRAgQIAAAQIECBAgQIAAAQIECBAgQMCi3DNAgAABAgQIECBAgAABAgQIECBAgAABAl0LWJR3XX7JEyBAgAABAgQIECBAgAABAgQIECBAgIBFuWeAAAECBAgQIECAAAECBAgQIECAAAECBLoWsCjvuvySJ0CAAAECBAgQIECAAAECBAgQIECAAAGLcs8AAQIECBAgQIAAAQIECBAgQIAAAQIECHQtYFHedfklT4AAAQIECBAgQIAAAQIECBAgQIAAAQIW5Z4BAgQIECBAgAABAgQIECBAgAABAgQIEOhawKK86/JLngABAgQIECBAgAABAgQIECBAgAABAgQsyj0DBAgQIECAAAECBAgQIECAAAECBAgQINC1gEV51+WXPAECBAgQIECAAAECBAgQIECAAAECBAhYlHsGCBAgQIAAAQIECBAgQIAAAQIECBAgQKBrAYvyrssveQIECBAgQIAAAQIECBAgQIAAAQIECBCwKPcMECBAgAABAgQIECBAgAABAgQIECBAgEDXAhblXZdf8gQIECBAgAABAgQIECBAgAABAgQIECBgUe4ZIECAAAECBAgQIECAAAECBAgQIECAAIGuBSzKuy6/5AkQIECAAAECBAgQIECAAAECBAgQIEDAotwzQIAAAQIECBAgQIAAAQIECBAgQIAAAQJdC1iUd11+yRMgQIAAAQIECBAgQIAAAQIECBAgQICARblngAABAgQIECBAgAABAgQIECBAgAABAgS6FrAo77r8kidAgAABAgQIECBAgAABAgQIECBAgAABi3LPAAECBAgQIECAAAECBAgQIECAAAECBAh0LWBR3nX5JU+AAAECBAgQIECAAAECBAgQIECAAAECFuWeAQIECBAgQIAAAQIECBAgQIAAAQIECBDoWsCivOvyS54AAQIECBAgQIAAAQIECBAgQIAAAQIELMo9AwQIECBAgAABAgQIECBAgAABAgQIECDQtYBFedfllzwBAgQIECBAgAABAgQIECBAgAABAgQIWJR7BggQIECAAAECBAgQIECAAAECBAgQIECgawGL8q7LL3kCBAgQIECAAAECBAgQIECAAAECBAgQsCj3DBAgQIAAAQIECBAgQIAAAQIECBAgQIBA1wIW5V2XX/IECBAgQIAAAQIECBAgQIAAAQIECBAgYFHuGSBAgAABAgQIECBAgAABAgQIECBAgACBrgUsyrsuv+QJECBAgAABAgQIECBAgAABAgQIECBA4P8BPq8vinNpwt0AAAAASUVORK5CYII=",
"text/html": [
""
]
},
"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": 89,
"metadata": {
"tags": [
"exclude"
]
},
"outputs": [],
"source": [
"def setup():\n",
" _c = Config()\n",
" s = setup_model(c=_c)\n",
" return s\n",
"\n",
"def routine(c, s):\n",
" s = load_data(c=c, s=s)\n",
" s = create_and_assign_assets(c=c, s=s)\n",
" #s = preprocessing(c=c, s=s)\n",
" s = run_optimisation(c=c, s=s)\n",
" #s = postprocessing(c=c, s=s)\n",
" s = collect_cashflows(c=c, s=s)\n",
" s = calculate_financials(c=c, s=s)\n",
" return s"
]
},
{
"cell_type": "code",
"execution_count": 90,
"metadata": {
"tags": [
"exclude"
]
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"c:\\users\\mekre\\recoy\\recoy - documents\\03 - libraries\\29 - pyrecoy modelling framework\\v1.2\\pyrecoy\\pyrecoy\\framework.py:40: UserWarning:\n",
"\n",
"The chosen timeperiod spans 365.99930555555557 days, which is not a full year. Beware that certain functions that use yearly rates might return incorrect values.\n",
"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: total: 11.9 s\n",
"Wall time: 12.3 s\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\mekre\\AppData\\Local\\Temp\\ipykernel_19048\\332434720.py:3: FutureWarning:\n",
"\n",
"Argument `closed` is deprecated in favor of `inclusive`.\n",
"\n"
]
}
],
"source": [
"%time _s = setup()"
]
},
{
"cell_type": "code",
"execution_count": 91,
"metadata": {
"tags": [
"exclude"
]
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: total: 1min 12s\n",
"Wall time: 1min 15s\n"
]
},
{
"data": {
"text/plain": [
"10005688.622020364"
]
},
"execution_count": 91,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%time result = routine(c, _s)\n",
"npv = result.hpcase.npv\n",
"npv"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Sensitivity: Water storage volume"
]
},
{
"cell_type": "code",
"execution_count": 97,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[0.0, 0.0, 0.0]"
]
},
"execution_count": 97,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"(_s.demand['MW (VDG)'] + _s.demand['MW (NDG)']).to_list()[:3]"
]
},
{
"cell_type": "code",
"execution_count": 102,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"c:\\users\\mekre\\recoy\\recoy - documents\\03 - libraries\\29 - pyrecoy modelling framework\\v1.2\\pyrecoy\\pyrecoy\\framework.py:40: UserWarning:\n",
"\n",
"The chosen timeperiod spans 365.99930555555557 days, which is not a full year. Beware that certain functions that use yearly rates might return incorrect values.\n",
"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: total: 14.3 s\n",
"Wall time: 14.8 s\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\mekre\\AppData\\Local\\Temp\\ipykernel_19048\\332434720.py:3: FutureWarning:\n",
"\n",
"Argument `closed` is deprecated in favor of `inclusive`.\n",
"\n"
]
}
],
"source": [
"%time _s = setup()"
]
},
{
"cell_type": "code",
"execution_count": 103,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "237043cda7f84a908718b385a7846533",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/4 [00:00 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"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",
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"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"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": 107,
"metadata": {},
"outputs": [
{
"data": {
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"config": {
"linkText": "Export to plot.ly",
"plotlyServerURL": "https://plot.ly",
"showLink": true
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"dash": "solid",
"shape": "linear",
"width": 1.3
},
"marker": {
"size": 10,
"symbol": "circle-dot"
},
"mode": "lines+markers",
"name": "Heatpump only",
"text": "",
"type": "scatter",
"x": [
100,
200,
300,
400
],
"y": [
2.6,
2.6,
2.6,
2.6
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},
{
"line": {
"color": "rgba(31, 131, 118, 1.0)",
"dash": "solid",
"shape": "linear",
"width": 1.3
},
"marker": {
"size": 10,
"symbol": "circle-dot"
},
"mode": "lines+markers",
"name": "Heatpump + Storage",
"text": "",
"type": "scatter",
"x": [
100,
200,
300,
400
],
"y": [
2.7,
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2.7,
2.8
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}
],
"layout": {
"height": 400,
"legend": {
"bgcolor": "#F5F6F9",
"font": {
"color": "#4D5663"
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},
"paper_bgcolor": "#F5F6F9",
"plot_bgcolor": "#F5F6F9",
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"pattern": {
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"solidity": 0.2
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},
"type": "bar"
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"barpolar": [
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"type": "barpolar"
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"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": 108,
"metadata": {},
"outputs": [
{
"ename": "KeyError",
"evalue": "'mean_cop'",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mKeyError\u001b[0m Traceback (most recent call last)",
"Input \u001b[1;32mIn [108]\u001b[0m, in \u001b[0;36m| \u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m output \u001b[38;5;241m=\u001b[39m \u001b[43msens\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msingle_kpi_overview\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mmean_cop\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcase_names\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[43mcase\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mname\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mcase\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43ms\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcases\u001b[49m\u001b[43m]\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 2\u001b[0m output\u001b[38;5;241m.\u001b[39miplot(\n\u001b[0;32m 3\u001b[0m mode\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mlines+markers\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m 4\u001b[0m symbol\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mcircle-dot\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 11\u001b[0m dimensions\u001b[38;5;241m=\u001b[39m(\u001b[38;5;241m600\u001b[39m, \u001b[38;5;241m400\u001b[39m),\n\u001b[0;32m 12\u001b[0m )\n",
"File \u001b[1;32mc:\\users\\mekre\\recoy\\recoy - documents\\03 - libraries\\29 - pyrecoy modelling framework\\v1.2\\pyrecoy\\pyrecoy\\sensitivity.py:62\u001b[0m, in \u001b[0;36mSensitivityAnalysis.single_kpi_overview\u001b[1;34m(self, kpi, case_names)\u001b[0m\n\u001b[0;32m 59\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m case_names:\n\u001b[0;32m 60\u001b[0m case_names \u001b[38;5;241m=\u001b[39m CaseStudy\u001b[38;5;241m.\u001b[39minstances\u001b[38;5;241m.\u001b[39mkeys()\n\u001b[1;32m---> 62\u001b[0m kpi_values \u001b[38;5;241m=\u001b[39m {\n\u001b[0;32m 63\u001b[0m name: {case: \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mkpis[name][kpi][case] \u001b[38;5;28;01mfor\u001b[39;00m case \u001b[38;5;129;01min\u001b[39;00m case_names}\n\u001b[0;32m 64\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m name \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mkpis\u001b[38;5;241m.\u001b[39mkeys()\n\u001b[0;32m 65\u001b[0m }\n\u001b[0;32m 67\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m pd\u001b[38;5;241m.\u001b[39mDataFrame(kpi_values)\u001b[38;5;241m.\u001b[39mT\n",
"File \u001b[1;32mc:\\users\\mekre\\recoy\\recoy - documents\\03 - libraries\\29 - pyrecoy modelling framework\\v1.2\\pyrecoy\\pyrecoy\\sensitivity.py:63\u001b[0m, in \u001b[0;36m\u001b[1;34m(.0)\u001b[0m\n\u001b[0;32m 59\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m case_names:\n\u001b[0;32m 60\u001b[0m case_names \u001b[38;5;241m=\u001b[39m CaseStudy\u001b[38;5;241m.\u001b[39minstances\u001b[38;5;241m.\u001b[39mkeys()\n\u001b[0;32m 62\u001b[0m kpi_values \u001b[38;5;241m=\u001b[39m {\n\u001b[1;32m---> 63\u001b[0m name: {case: \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mkpis[name][kpi][case] \u001b[38;5;28;01mfor\u001b[39;00m case \u001b[38;5;129;01min\u001b[39;00m case_names}\n\u001b[0;32m 64\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m name \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mkpis\u001b[38;5;241m.\u001b[39mkeys()\n\u001b[0;32m 65\u001b[0m }\n\u001b[0;32m 67\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m pd\u001b[38;5;241m.\u001b[39mDataFrame(kpi_values)\u001b[38;5;241m.\u001b[39mT\n",
"File \u001b[1;32mc:\\users\\mekre\\recoy\\recoy - documents\\03 - libraries\\29 - pyrecoy modelling framework\\v1.2\\pyrecoy\\pyrecoy\\sensitivity.py:63\u001b[0m, in \u001b[0;36m\u001b[1;34m(.0)\u001b[0m\n\u001b[0;32m 59\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m case_names:\n\u001b[0;32m 60\u001b[0m case_names \u001b[38;5;241m=\u001b[39m CaseStudy\u001b[38;5;241m.\u001b[39minstances\u001b[38;5;241m.\u001b[39mkeys()\n\u001b[0;32m 62\u001b[0m kpi_values \u001b[38;5;241m=\u001b[39m {\n\u001b[1;32m---> 63\u001b[0m name: {case: \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mkpis\u001b[49m\u001b[43m[\u001b[49m\u001b[43mname\u001b[49m\u001b[43m]\u001b[49m\u001b[43m[\u001b[49m\u001b[43mkpi\u001b[49m\u001b[43m]\u001b[49m[case] \u001b[38;5;28;01mfor\u001b[39;00m case \u001b[38;5;129;01min\u001b[39;00m case_names}\n\u001b[0;32m 64\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m name \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mkpis\u001b[38;5;241m.\u001b[39mkeys()\n\u001b[0;32m 65\u001b[0m }\n\u001b[0;32m 67\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m pd\u001b[38;5;241m.\u001b[39mDataFrame(kpi_values)\u001b[38;5;241m.\u001b[39mT\n",
"\u001b[1;31mKeyError\u001b[0m: 'mean_cop'"
]
}
],
"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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