163 lines
7.9 KiB
Python
163 lines
7.9 KiB
Python
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"""
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Cost module
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"""
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import pandas as pd
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from hub.city_model_structure.city import City
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from configuration import Configuration
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from life_cycle_costs import LifeCycleCosts
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class Cost:
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"""
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Cost class
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"""
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def __init__(self,
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city: City,
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number_of_years=31,
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percentage_credit=0,
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interest_rate=0.04,
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credit_years=15,
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consumer_price_index=0.04,
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electricity_peak_index=0.05,
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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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factories_handler='montreal_custom'):
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self._city = city
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self._configuration = Configuration(number_of_years,
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percentage_credit,
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interest_rate, credit_years,
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consumer_price_index,
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electricity_peak_index,
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electricity_price_index,
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gas_price_index,
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discount_rate,
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retrofitting_year_construction,
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factories_handler)
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@property
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def life_cycle(self) -> pd.DataFrame:
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"""
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Get complete life cycle costs
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:return: DataFrame
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"""
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results = pd.DataFrame()
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for building in self._city.buildings:
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lcc = LifeCycleCosts(building, self._configuration)
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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_maintenance_costs = lcc.calculate_total_maintenance_costs()
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global_operational_incomes = lcc.calculate_total_operational_incomes()
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results[f'Scenario {retrofitting_scenario}'] = [life_cycle_costs_capital_skin,
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life_cycle_costs_capital_systems,
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life_cycle_costs_end_of_life_costs,
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life_cycle_operational_costs,
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life_cycle_maintenance_costs,
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life_cycle_operational_incomes,
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life_cycle_capital_incomes]
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life_cycle_results.index = ['total_capital_costs_skin',
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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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return results
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"""
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if "gas" in building.energy_systems_archetype_name:
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FUEL_TYPE = 1
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else:
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FUEL_TYPE = 0
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full_path_output = Path(out_path / f'output {retrofitting_scenario} {building.name}.xlsx').resolve()
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with pd.ExcelWriter(full_path_output) as writer:
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global_capital_costs.to_excel(writer, sheet_name='global_capital_costs')
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global_end_of_life_costs.to_excel(writer, sheet_name='global_end_of_life_costs')
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global_operational_costs.to_excel(writer, sheet_name='global_operational_costs')
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global_maintenance_costs.to_excel(writer, sheet_name='global_maintenance_costs')
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global_operational_incomes.to_excel(writer, sheet_name='global_operational_incomes')
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global_capital_incomes.to_excel(writer, sheet_name='global_capital_incomes')
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df_capital_costs_skin = (
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global_capital_costs['B2010_opaque_walls'] + global_capital_costs['B2020_transparent'] +
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global_capital_costs['B3010_opaque_roof'] + global_capital_costs['B10_superstructure']
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)
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df_capital_costs_systems = (
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global_capital_costs['D3020_heat_generating_systems'] +
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global_capital_costs['D3030_cooling_generation_systems'] +
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global_capital_costs['D3080_other_hvac_ahu'] +
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global_capital_costs['D5020_lighting_and_branch_wiring'] +
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global_capital_costs['D301010_photovoltaic_system']
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)
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df_end_of_life_costs = global_end_of_life_costs['End_of_life_costs']
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df_operational_costs = (
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global_operational_costs['Fixed_costs_electricity_peak'] +
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global_operational_costs['Fixed_costs_electricity_monthly'] +
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global_operational_costs['Fixed_costs_electricity_peak'] +
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global_operational_costs['Fixed_costs_electricity_monthly'] +
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global_operational_costs['Variable_costs_electricity'] +
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global_operational_costs['Fixed_costs_gas'] +
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global_operational_costs['Variable_costs_gas']
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)
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df_maintenance_costs = (
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global_maintenance_costs['Heating_maintenance'] +
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global_maintenance_costs['Cooling_maintenance'] +
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global_maintenance_costs['PV_maintenance']
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)
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df_operational_incomes = global_operational_incomes['Incomes electricity']
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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 = npf.npv(self._discount_rate, list_cashflow)_npv_from_list(, 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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life_cycle_costs_end_of_life_costs = _npv_from_list(DISCOUNT_RATE, df_end_of_life_costs.values.tolist())
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life_cycle_operational_costs = _npv_from_list(DISCOUNT_RATE, df_operational_costs.values.tolist())
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life_cycle_maintenance_costs = _npv_from_list(DISCOUNT_RATE, df_maintenance_costs.values.tolist())
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life_cycle_operational_incomes = _npv_from_list(DISCOUNT_RATE, df_operational_incomes.values.tolist())
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life_cycle_capital_incomes = _npv_from_list(DISCOUNT_RATE, df_capital_incomes.values.tolist())
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life_cycle_costs = (
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life_cycle_costs_capital_skin +
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life_cycle_costs_capital_systems +
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life_cycle_costs_end_of_life_costs +
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life_cycle_operational_costs +
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life_cycle_maintenance_costs -
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life_cycle_operational_incomes -
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life_cycle_capital_incomes
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)
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life_cycle_results[f'Scenario {retrofitting_scenario}'] = [life_cycle_costs_capital_skin,
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life_cycle_costs_capital_systems,
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life_cycle_costs_end_of_life_costs,
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life_cycle_operational_costs,
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life_cycle_maintenance_costs,
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life_cycle_operational_incomes,
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life_cycle_capital_incomes]
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life_cycle_results.index = ['total_capital_costs_skin',
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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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return results
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"""
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