""" LifeCycleCosts calculates the life cycle costs of one building SPDX - License - Identifier: LGPL - 3.0 - or -later Copyright © 2022 Project Author Pilar Monsalvete Alvarez de Uribarri pilar_monsalvete@concordia.ca Project contributor © 2023 Author Oriol Gavaldà Torrellas oriol.gavalda@concordia.ca """ import math import pandas as pd import numpy as np from datetime import date import hub.helpers.constants as cte class LifeCycleCosts: def __init__(self, building, archetype, number_of_years, consumer_price_index, electricity_peak_index, electricity_price_index, gas_price_index, discount_rate, retrofitting_scenario,fuel_type): self._building = building self._number_of_years = number_of_years self._consumer_price_index = consumer_price_index self._electricity_peak_index = electricity_peak_index self._electricity_price_index = electricity_price_index self._gas_price_index = gas_price_index self._discount_rate = discount_rate self._archetype = archetype self._end_of_life_cost = 0 self._capital_costs_at_year_0 = 0 self._items = 0 self._fuels = 0 self._concepts = 0 self._retrofitting_scenario = retrofitting_scenario self._total_floor_area = 0 self._fuel_type = fuel_type for internal_zone in building.internal_zones: for thermal_zone in internal_zone.thermal_zones: self._total_floor_area += thermal_zone.total_floor_area #todo: revise if it works rng = range(number_of_years) self._yearly_capital_costs = pd.DataFrame(index=rng, columns=['B2010_opaque_walls', 'B2020_transparent', 'B3010_opaque_roof','B10_superstructure', 'D301010_photovoltaic_system','D3020_heat_generating_systems', 'D3030_cooling_generation_systems','D3040_distribution_systems', 'D3080_other_hvac_ahu','D5020_lighting_and_branch_wiring'], dtype='float') self._yearly_end_of_life_costs = pd.DataFrame(index=rng, columns=['End_of_life_costs'], dtype='float') self._yearly_operational_costs = pd.DataFrame(index=rng, columns=['Fixed_costs_electricity_peak', 'Fixed_costs_electricity_monthly', 'Variable_costs_electricity','Fixed_costs_gas', 'Variable_costs_gas'], dtype='float') self._yearly_maintenance_costs = pd.DataFrame(index=rng, columns=['Heating_maintenance','Cooling_maintenance', 'PV_maintenance'], dtype='float') self._yearly_operational_incomes = pd.DataFrame(index=rng, columns=['Incomes electricity'],dtype='float') def calculate_capital_costs(self): building = self._building archetype = self._archetype surface_opaque = 0 surface_transparent = 0 surface_roof = 0 surface_ground = 0 total_floor_area = self._total_floor_area for internal_zone in building.internal_zones: for thermal_zone in internal_zone.thermal_zones: for thermal_boundary in thermal_zone.thermal_boundaries: if thermal_boundary.type == 'Ground': surface_ground += thermal_boundary.opaque_area elif thermal_boundary.type == 'Roof': surface_roof += thermal_boundary.opaque_area elif thermal_boundary.type == 'Wall': surface_opaque += thermal_boundary.opaque_area * (1-thermal_boundary.window_ratio) surface_transparent += thermal_boundary.opaque_area * thermal_boundary.window_ratio chapters = archetype.capital_cost capital_cost_skin = 0 capital_cost_services = 0 capital_cost_pv = 0 peak_heating = building.heating_peak_load[cte.YEAR].values[0] peak_cooling = building.cooling_peak_load[cte.YEAR].values[0] #todo: put the value of area_pv when it exists surface_pv = 10 #building.area_pv self._yearly_capital_costs.loc[0, 'B2010_opaque_walls'], self._yearly_capital_costs.loc[0]['B2020_transparent'], \ self._yearly_capital_costs.loc[0, 'B3010_opaque_roof'], self._yearly_capital_costs.loc[0]['B10_superstructure'], \ self._yearly_capital_costs.loc[0, 'B_Shell'] \ = [0, 0, 0, 0, 0] self._yearly_capital_costs.loc[0, 'D3020_heat_generating_systems'], \ self._yearly_capital_costs.loc[0, 'D3030_cooling_generation_systems'], \ self._yearly_capital_costs.loc[0, 'D3040_distribution_systems'], \ self._yearly_capital_costs.loc[0, 'D3080_other_hvac_ahu'], \ self._yearly_capital_costs.loc[0, 'D5020_lighting_and_branch_wiring'] \ = [0, 0, 0, 0, 0] self._yearly_capital_costs.fillna(0,inplace=True) if self._retrofitting_scenario == 1 or self._retrofitting_scenario == 3: chapter = chapters.chapter('B_shell') capital_cost_opaque = surface_opaque * chapter.item('B2010_opaque_walls').refurbishment[0] capital_cost_transparent = surface_transparent * chapter.item('B2020_transparent').refurbishment[0] capital_cost_roof = surface_roof * chapter.item('B3010_opaque_roof').refurbishment[0] capital_cost_ground = surface_ground * chapter.item('B10_superstructure').refurbishment[0] capital_cost_skin = capital_cost_opaque+capital_cost_transparent+capital_cost_roof+capital_cost_ground self._yearly_capital_costs.loc[0,'B2010_opaque_walls'],self._yearly_capital_costs.loc[0]['B2020_transparent'], \ self._yearly_capital_costs.loc[0,'B3010_opaque_roof'],self._yearly_capital_costs.loc[0]['B10_superstructure'],\ self._yearly_capital_costs.loc[0,'B_Shell']\ =[capital_cost_opaque , capital_cost_transparent , capital_cost_roof , capital_cost_ground , capital_cost_skin] if self._retrofitting_scenario == 2 or self._retrofitting_scenario == 3: chapter = chapters.chapter('D_services') capital_cost_pv = surface_pv * chapter.item('D301010_photovoltaic_system').initial_investment[0] self._yearly_capital_costs.loc[0]['D301010_photovoltaic_system'] = capital_cost_pv capital_cost_heating_equipment = peak_heating \ * chapter.item('D3020_heat_generating_systems').initial_investment[0] capital_cost_cooling_equipment = peak_cooling \ * chapter.item('D3030_cooling_generation_systems').initial_investment[0] capital_cost_distribution_equipment = peak_cooling \ * chapter.item('D3040_distribution_systems').initial_investment[0] capital_cost_other_hvac_ahu = peak_cooling * chapter.item('D3080_other_hvac_ahu').initial_investment[0] capital_cost_lighting = total_floor_area * chapter.item('D5020_lighting_and_branch_wiring').initial_investment[0] self._yearly_capital_costs.loc[0,'D3020_heat_generating_systems'], \ self._yearly_capital_costs.loc[0,'D3030_cooling_generation_systems'], \ self._yearly_capital_costs.loc[0,'D3040_distribution_systems'], \ self._yearly_capital_costs.loc[0,'D3080_other_hvac_ahu'], \ self._yearly_capital_costs.loc[0,'D5020_lighting_and_branch_wiring']\ = [capital_cost_heating_equipment, capital_cost_cooling_equipment, capital_cost_distribution_equipment, capital_cost_other_hvac_ahu, capital_cost_lighting] for year in range(1, self._number_of_years): chapter = chapters.chapter('D_services') costs_increase = math.pow(1 + self._consumer_price_index, year) / math.pow(1 + self._discount_rate, year) if (year % chapter.item('D3020_heat_generating_systems').lifetime) == 0: reposition_cost_heating_equipment = peak_heating * chapter.item('D3020_heat_generating_systems').reposition[0] \ * costs_increase self._yearly_capital_costs.loc[year,'D3020_heat_generating_systems'] = reposition_cost_heating_equipment if (year % chapter.item('D3030_cooling_generation_systems').lifetime) == 0: reposition_cost_cooling_equipment = peak_cooling \ * chapter.item('D3030_cooling_generation_systems').reposition[0] \ * costs_increase self._yearly_capital_costs.loc[year,'D3030_cooling_generation_systems'] = reposition_cost_cooling_equipment if (year % chapter.item('D3080_other_hvac_ahu').lifetime) == 0: reposition_cost_hvac_ahu = peak_cooling * chapter.item('D3080_other_hvac_ahu').reposition[0] * costs_increase self._yearly_capital_costs.loc[year,'D3080_other_hvac_ahu'] = reposition_cost_hvac_ahu if (year % chapter.item('D5020_lighting_and_branch_wiring').lifetime) == 0: reposition_cost_lighting = total_floor_area * chapter.item('D5020_lighting_and_branch_wiring').reposition[0] \ * costs_increase self._yearly_capital_costs.loc[year,'D5020_lighting_and_branch_wiring'] = reposition_cost_lighting if self._retrofitting_scenario==2 or self._retrofitting_scenario==3 : if (year % chapter.item('D301010_photovoltaic_system').lifetime) == 0: self._yearly_capital_costs.loc[year]['D301010_photovoltaic_system'] = surface_pv \ * chapter.item('D301010_photovoltaic_system').reposition[0] * costs_increase return self._yearly_capital_costs def calculate_end_of_life_costs(self): archetype = self._archetype total_floor_area = self._total_floor_area price_increase = 0 for year in range(1, self._number_of_years + 1): price_increase += math.pow(1 + self._consumer_price_index, year) if year == self._number_of_years: self._yearly_end_of_life_costs.at[year,'End_of_life_costs'] = total_floor_area * archetype.end_of_life_cost*price_increase self._yearly_end_of_life_costs.fillna(0,inplace=True) return self._yearly_end_of_life_costs def calculate_total_operational_costs(self): building = self._building archetype = self._archetype total_floor_area = self._total_floor_area factor_residential = total_floor_area / 80 #todo: split the heating between fuels fixed_gas_cost_year_0 = 0 variable_gas_cost_year_0 = 0 electricity_heating = 0 domestic_hot_water_electricity = 0 if self._fuel_type == 1: fixed_gas_cost_year_0 = archetype.operational_cost.fuels[1].fixed_monthly variable_gas_cost_year_0 = (building.heating_consumption[cte.YEAR][0]+ building.domestic_hot_water_consumption[cte.YEAR][0]) / (1000) * \ archetype.operational_cost.fuels[1].variable[0] if self._fuel_type == 0: electricity_heating = building.heating_consumption[cte.YEAR][0] / (1000) domestic_hot_water_electricity = building.domestic_hot_water_consumption[cte.YEAR][0] / 1000 electricity_cooling = building.cooling_consumption[cte.YEAR][0] / (1000) electricity_lighting = building.lighting_electrical_demand[cte.YEAR]['insel meb']/1000 electricity_plug_loads = building.appliances_electrical_demand[cte.YEAR]['insel meb']/1000 electricity_distribution = 0 #building.distribution_systems_electrical_consumption[cte.YEAR][0]/1000 total_electricity_consumption = electricity_heating + electricity_cooling + electricity_lighting + \ domestic_hot_water_electricity + electricity_plug_loads + electricity_distribution #todo: change when peak electricity demand is coded. Careful with factor residential peak_electricity_demand = 100 #self._peak_electricity_demand variable_electricity_cost_year_0 = total_electricity_consumption * archetype.operational_cost.fuels[0].variable[0] peak_electricity_cost_year_0 = peak_electricity_demand * archetype.operational_cost.fuels[0].fixed_power * 12 monthly_electricity_cost_year_0 = archetype.operational_cost.fuels[0].fixed_monthly * 12 * factor_residential price_increase_electricity = 0 price_increase_peak_electricity = 0 price_increase_gas = 0 for year in range(1, self._number_of_years + 1): price_increase_electricity += math.pow(1 + self._electricity_price_index, year) price_increase_peak_electricity += math.pow(1 + self._electricity_peak_index, year) price_increase_gas += math.pow(1 + self._gas_price_index, year) self._yearly_operational_costs.at[year,'Fixed_costs_electricity_peak']=peak_electricity_cost_year_0*\ price_increase_peak_electricity self._yearly_operational_costs.at[year,'Fixed_costs_electricity_monthly'] = monthly_electricity_cost_year_0 * \ price_increase_peak_electricity self._yearly_operational_costs.at[year,'Variable_costs_electricity'] = variable_electricity_cost_year_0 * \ price_increase_electricity self._yearly_operational_costs.at[year,'Fixed_costs_gas'] = fixed_gas_cost_year_0 * \ price_increase_gas self._yearly_operational_costs.at[year,'Variable_costs_gas'] = variable_gas_cost_year_0* \ price_increase_peak_electricity self._yearly_operational_costs.at[year,'Variable_costs_gas'] = variable_gas_cost_year_0 * \ price_increase_peak_electricity self._yearly_operational_costs.fillna(0,inplace=True) return self._yearly_operational_costs def calculate_total_operational_incomes(self): building = self._building archetype = self._archetype if (building.onsite_electrical_production is None): onsite_electricity_production = 0 else: onsite_electricity_production= 100 #building.onsite_electrical_production[cte.YEAR]/1000 price_increase_electricity = 0 for year in range(1, self._number_of_years + 1): price_increase_electricity += math.pow(1 + self._electricity_price_index, year) self._yearly_operational_incomes.loc[year,'Incomes electricity']=onsite_electricity_production*\ price_increase_electricity self._yearly_operational_incomes.fillna(0,inplace=True) return self._yearly_operational_incomes def calculate_total_maintenance_costs(self): building = self._building archetype = self._archetype #todo: change area pv when the variable exists surface_pv = 10 #building.area_pv peak_heating = 100#building.heating_peak_load[cte.YEAR][0] peak_cooling = 100#building.cooling_peak_load[cte.YEAR][0] maintenance_heating_0 = peak_heating * archetype.operational_cost.maintenance_heating maintenance_cooling_0 = peak_cooling * archetype.operational_cost.maintenance_cooling maintenance_pv_0 = surface_pv * archetype.operational_cost.maintenance_pv print(f'peak_heating{peak_heating}') print(f'maintenance_cost{archetype.operational_cost.maintenance_heating}') for year in range(1, self._number_of_years + 1): costs_increase = math.pow(1 + self._consumer_price_index, year) self._yearly_maintenance_costs.loc[year,'Heating_maintenance'] = maintenance_heating_0 * \ costs_increase self._yearly_maintenance_costs.loc[year,'Cooling_maintenance'] = maintenance_cooling_0 * \ costs_increase self._yearly_maintenance_costs.loc[year,'PV_maintenance'] = maintenance_pv_0 * \ costs_increase self._yearly_maintenance_costs.fillna(0,inplace=True) return self._yearly_maintenance_costs