Complete basic clean up and warning removal
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@ -5,18 +5,13 @@ import glob
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import os
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from pathlib import Path
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CLIMATE_REFERENCE_CITY = 'Montreal'
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WEATHER_FILE = 'CAN_PQ_Montreal.Intl.AP.716270_CWEC.epw'
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WEATHER_FORMAT = 'epw'
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# configurable parameters
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file_path = Path('./data/selected_building_2864.geojson').resolve()
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CONSTRUCTION_FORMAT = 'nrcan'
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USAGE_FORMAT = 'comnet'
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ENERGY_SYSTEM_FORMAT = 'montreal_custom'
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ATTIC_HEATED_CASE = 0
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BASEMENT_HEATED_CASE = 1
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CURRENT_STATUS = 0
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SKIN_RETROFIT = 1
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SYSTEM_RETROFIT_AND_PV = 2
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SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV = 3
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NUMBER_OF_YEARS = 31
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CONSUMER_PRICE_INDEX = 0.04
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ELECTRICITY_PEAK_INDEX = 0.05
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@ -24,13 +19,20 @@ ELECTRICITY_PRICE_INDEX = 0.05
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GAS_PRICE_INDEX = 0.05
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DISCOUNT_RATE = 0.03
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RETROFITTING_YEAR_CONSTRUCTION = 2020
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CLIMATE_REFERENCE_CITY = 'Montreal'
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WEATHER_FILE = 'CAN_PQ_Montreal.Intl.AP.716270_CWEC.epw'
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WEATHER_FORMAT = 'epw'
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CURRENT_STATUS = 0
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SKIN_RETROFIT = 1
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SYSTEM_RETROFIT_AND_PV = 2
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SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV = 3
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RETROFITTING_SCENARIOS = [
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CURRENT_STATUS,
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SKIN_RETROFIT,
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SYSTEM_RETROFIT_AND_PV,
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SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV
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]
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file_path = Path('./data/selected_building_2864.geojson').resolve()
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tmp_folder = Path('./tmp').resolve()
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out_path = Path('./outputs').resolve()
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files = glob.glob(f'{out_path}/*')
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@ -23,10 +23,11 @@ from sra_engine import SraEngine
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from life_cycle_costs import LifeCycleCosts
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# import constants
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from costs import CLIMATE_REFERENCE_CITY, WEATHER_FILE, WEATHER_FORMAT, CONSTRUCTION_FORMAT, USAGE_FORMAT, RETROFITTING_YEAR_CONSTRUCTION
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from costs import CLIMATE_REFERENCE_CITY, WEATHER_FILE, WEATHER_FORMAT, CONSTRUCTION_FORMAT, USAGE_FORMAT
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from costs import ENERGY_SYSTEM_FORMAT, ATTIC_HEATED_CASE, BASEMENT_HEATED_CASE, RETROFITTING_SCENARIOS, NUMBER_OF_YEARS
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from costs import CONSUMER_PRICE_INDEX, ELECTRICITY_PEAK_INDEX, ELECTRICITY_PRICE_INDEX, GAS_PRICE_INDEX, DISCOUNT_RATE
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from costs import SKIN_RETROFIT, SYSTEM_RETROFIT_AND_PV, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV
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from costs import RETROFITTING_YEAR_CONSTRUCTION
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# import paths
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from costs import file_path, tmp_folder, out_path
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@ -111,7 +112,7 @@ for retrofitting_scenario in RETROFITTING_SCENARIOS:
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ELECTRICITY_PRICE_INDEX, GAS_PRICE_INDEX, DISCOUNT_RATE, retrofitting_scenario, FUEL_TYPE)
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global_capital_costs, global_capital_incomes = lcc.calculate_capital_costs()
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global_end_of_life_costs = lcc.calculate_end_of_life_costs()
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global_operational_costs = lcc.calculate_total_operational_costs()
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global_operational_costs = lcc.calculate_total_operational_costs
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global_maintenance_costs = lcc.calculate_total_maintenance_costs()
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global_operational_incomes = lcc.calculate_total_operational_incomes()
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full_path_output = Path(out_path / f'output {retrofitting_scenario} {building.name}.xlsx').resolve()
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@ -151,8 +152,11 @@ for retrofitting_scenario in RETROFITTING_SCENARIOS:
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)
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df_operational_incomes = global_operational_incomes['Incomes electricity']
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df_capital_incomes = global_capital_incomes['Subsidies construction'] + global_capital_incomes['Subsidies HVAC'] + \
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global_capital_incomes['Subsidies PV']
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df_capital_incomes = (
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global_capital_incomes['Subsidies construction'] +
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global_capital_incomes['Subsidies HVAC'] +
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global_capital_incomes['Subsidies PV']
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)
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life_cycle_costs_capital_skin = _npv_from_list(DISCOUNT_RATE, df_capital_costs_skin.values.tolist())
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life_cycle_costs_capital_systems = _npv_from_list(DISCOUNT_RATE, df_capital_costs_systems.values.tolist())
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@ -181,9 +185,12 @@ for retrofitting_scenario in RETROFITTING_SCENARIOS:
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life_cycle_capital_incomes]
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life_cycle_results.index = ['total_capital_costs_skin',
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f'total_capital_costs_systems','end_of_life_costs',
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'total_operational_costs', 'total_maintenance_costs',
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'operational_incomes', 'capital_incomes']
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'total_capital_costs_systems',
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'end_of_life_costs',
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'total_operational_costs',
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'total_maintenance_costs',
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'operational_incomes',
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'capital_incomes']
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print(life_cycle_results)
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print(f'Scenario {retrofitting_scenario} {life_cycle_costs}')
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@ -64,6 +64,7 @@ class LifeCycleCosts:
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self._yearly_capital_incomes = pd.DataFrame(index=rng, columns=['Subsidies construction',
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'Subsidies HVAC', 'Subsidies PV'], dtype='float')
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def calculate_capital_costs(self):
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"""
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Calculate capital cost
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@ -133,13 +134,11 @@ class LifeCycleCosts:
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capital_cost_roof = surface_roof * chapter.item('B3010_opaque_roof').refurbishment[0]
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capital_cost_ground = surface_ground * chapter.item('B10_superstructure').refurbishment[0]
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self._yearly_capital_costs.loc[0, 'B2010_opaque_walls'] = capital_cost_opaque
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self._yearly_capital_costs.loc[0]['B2020_transparent'] = capital_cost_transparent
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self._yearly_capital_costs.loc[0, 'B3010_opaque_roof'] = capital_cost_roof
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self._yearly_capital_costs.loc[0]['B10_superstructure'] = capital_cost_ground
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if self._retrofitting_scenario in (SYSTEM_RETROFIT_AND_PV, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV):
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chapter = chapters.chapter('D_services')
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capital_cost_pv = surface_pv * chapter.item('D301010_photovoltaic_system').initial_investment[0]
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@ -192,11 +191,16 @@ class LifeCycleCosts:
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* chapter.item(
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'D301010_photovoltaic_system').reposition[0] * costs_increase
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capital_cost_skin = capital_cost_opaque + capital_cost_ground + capital_cost_transparent + capital_cost_roof
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capital_cost_hvac = capital_cost_heating_equipment + capital_cost_cooling_equipment + \
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capital_cost_distribution_equipment + capital_cost_other_hvac_ahu + capital_cost_lighting
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capital_cost_hvac = (
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capital_cost_heating_equipment +
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capital_cost_cooling_equipment +
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capital_cost_distribution_equipment +
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capital_cost_other_hvac_ahu + capital_cost_lighting
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)
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self._yearly_capital_incomes.loc[0, 'Subsidies construction'] = capital_cost_skin * \
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archetype.income.construction_subsidy/100
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self._yearly_capital_incomes.loc[0, 'Subsidies construction'] = (
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capital_cost_skin * archetype.income.construction_subsidy/100
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)
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self._yearly_capital_incomes.loc[0, 'Subsidies HVAC'] = capital_cost_hvac * archetype.income.hvac_subsidy/100
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self._yearly_capital_incomes.loc[0, 'Subsidies PV'] = capital_cost_pv * archetype.income.photovoltaic_subsidy/100
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self._yearly_capital_incomes.fillna(0, inplace=True)
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@ -210,7 +214,6 @@ class LifeCycleCosts:
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archetype = self._archetype
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total_floor_area = self._total_floor_area
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price_increase = 0
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for year in range(1, self._number_of_years + 1):
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price_increase = math.pow(1 + self._consumer_price_index, year)
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if year == self._number_of_years:
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@ -219,6 +222,7 @@ class LifeCycleCosts:
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self._yearly_end_of_life_costs.fillna(0, inplace=True)
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return self._yearly_end_of_life_costs
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@property
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def calculate_total_operational_costs(self):
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"""
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Calculate total operational costs
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@ -289,21 +293,18 @@ class LifeCycleCosts:
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:return: pd.DataFrame
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"""
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building = self._building
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archetype = self._archetype
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if cte.YEAR not in building.onsite_electrical_production:
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onsite_electricity_production = 0
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else:
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onsite_electricity_production = building.onsite_electrical_production[cte.YEAR][0]/1000
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price_increase_electricity = 0
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for year in range(1, self._number_of_years + 1):
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price_increase_electricity = math.pow(1 + self._electricity_price_index, year)
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#todo: check the adequate assignation of price. Pilar
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price_export = 0.075 # archetype.income.electricity_export
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self._yearly_operational_incomes.loc[year, 'Incomes electricity'] = (onsite_electricity_production *
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price_export *
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price_increase_electricity
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)
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# todo: check the adequate assignation of price. Pilar
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price_export = 0.075 # archetype.income.electricity_export
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self._yearly_operational_incomes.loc[year, 'Incomes electricity'] = (
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onsite_electricity_production * price_export * price_increase_electricity
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)
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self._yearly_operational_incomes.fillna(0, inplace=True)
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return self._yearly_operational_incomes
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