285 lines
16 KiB
Python
285 lines
16 KiB
Python
"""
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LifeCycleCosts calculates the life cycle costs of one building
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SPDX - License - Identifier: LGPL - 3.0 - or -later
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Copyright © 2022 Project Author Pilar Monsalvete Alvarez de Uribarri pilar_monsalvete@concordia.ca
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Project contributor © 2023 Author Oriol Gavaldà Torrellas oriol.gavalda@concordia.ca
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"""
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import math
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import pandas as pd
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import numpy as np
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from datetime import date
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import hub.helpers.constants as cte
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class LifeCycleCosts:
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def __init__(self, building, archetype, number_of_years, consumer_price_index, electricity_peak_index,
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electricity_price_index, gas_price_index, discount_rate,
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retrofitting_scenario):
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self._building = building
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self._number_of_years = number_of_years
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self._consumer_price_index = consumer_price_index
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self._electricity_peak_index = electricity_peak_index
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self._electricity_price_index = electricity_price_index
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self._gas_price_index = gas_price_index
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self._discount_rate = discount_rate
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self._archetype = archetype
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self._end_of_life_cost = 0
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self._capital_costs_at_year_0 = 0
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self._items = 0
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self._fuels = 0
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self._concepts = 0
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self._retrofitting_scenario = retrofitting_scenario
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self._total_floor_area = 0
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for internal_zone in building.internal_zones:
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for thermal_zone in internal_zone.thermal_zones:
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self._total_floor_area += thermal_zone.total_floor_area
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#todo: revise if it works
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rng = range(number_of_years)
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self._yearly_capital_costs = pd.DataFrame(index=rng, columns=['B2010_opaque_walls', 'B2020_transparent',
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'B3010_opaque_roof','B10_superstructure',
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'D301010_photovoltaic_system','D3020_heat_generating_systems',
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'D3030_cooling_generation_systems','D3040_distribution_systems',
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'D3080_other_hvac_ahu','D5020_lighting_and_branch_wiring'],
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dtype='float')
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self._yearly_capital_costs.replace(np.nan, 0)
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self._yearly_end_of_life_costs = pd.DataFrame(index=rng, columns=['End_of_life_costs'], dtype='float')
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self._yearly_end_of_life_costs.replace(np.nan, 0)
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self._yearly_operational_costs = pd.DataFrame(index=rng, columns=['Fixed_costs_electricity_peak',
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'Fixed_costs_electricity_monthly',
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'Variable_costs_electricity','Fixed_costs_gas',
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'Variable_costs_gas','Heating_maintenance',
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'Cooling_maintenance','PV_maintenance'],
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dtype='float')
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self._yearly_operational_costs.replace(np.nan, 0)
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self._yearly_operational_incomes = pd.DataFrame(index=rng, columns=['Incomes electricity'],dtype='float')
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self._yearly_operational_incomes.replace(np.nan, 0)
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def calculate_capital_costs(self):
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building = self._building
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archetype = self._archetype
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surface_opaque = 0
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surface_transparent = 0
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surface_roof = 0
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surface_ground = 0
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total_floor_area = self._total_floor_area
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for internal_zone in building.internal_zones:
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for thermal_zone in internal_zone.thermal_zones:
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for thermal_boundary in thermal_zone.thermal_boundaries:
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if thermal_boundary.type == 'Ground':
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surface_ground += thermal_boundary.opaque_area
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elif thermal_boundary.type == 'Roof':
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surface_roof += thermal_boundary.opaque_area
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elif thermal_boundary.type == 'Wall':
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surface_opaque += thermal_boundary.opaque_area * (1-thermal_boundary.window_ratio)
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surface_transparent += thermal_boundary.opaque_area * thermal_boundary.window_ratio
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chapters = archetype.capital_cost
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capital_cost_skin = 0
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capital_cost_services = 0
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capital_cost_pv = 0
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peak_heating = building.heating_peak_load[cte.YEAR].values[0]
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peak_cooling = building.cooling_peak_load[cte.YEAR].values[0]
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#todo: put the value of area_pv when it exists
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surface_pv = 10 #building.area_pv
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if self._retrofitting_scenario == 1 or self._retrofitting_scenario == 3:
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chapter = chapters.chapter('B_shell')
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capital_cost_opaque = surface_opaque * chapter.item('B2010_opaque_walls').refurbishment[0]
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capital_cost_transparent = surface_transparent * chapter.item('B2020_transparent').refurbishment[0]
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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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capital_cost_skin = capital_cost_opaque+capital_cost_transparent+capital_cost_roof+capital_cost_ground
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self._yearly_capital_costs.loc[0]['B2010_opaque_walls'],self._yearly_capital_costs.loc[0]['B2020_transparent'], \
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self._yearly_capital_costs.loc[0]['B3010_opaque_roof'],self._yearly_capital_costs.loc[0]['B10_superstructure'],\
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self._yearly_capital_costs.loc[0]['B_Shell']\
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=[capital_cost_opaque , capital_cost_transparent , capital_cost_roof , capital_cost_ground , capital_cost_skin]
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if self._retrofitting_scenario == 2 or self._retrofitting_scenario == 3:
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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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self._yearly_capital_costs.loc[0]['D301010_photovoltaic_system'] = capital_cost_pv
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capital_cost_heating_equipment = peak_heating \
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* chapter.item('D3020_heat_generating_systems').initial_investment[0]
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capital_cost_cooling_equipment = peak_cooling \
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* chapter.item('D3030_cooling_generation_systems').initial_investment[0]
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capital_cost_distribution_equipment = peak_cooling \
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* chapter.item('D3040_distribution_systems').initial_investment[0]
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capital_cost_other_hvac_ahu = peak_cooling * chapter.item('D3080_other_hvac_ahu').initial_investment[0]
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capital_cost_lighting = total_floor_area * self._peak_lights \
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* chapter.item('D5020_lighting_and_branch_wiring').initial_investment[0]
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self._yearly_capital_costs.loc[0]['D3020_heat_generating_systems'], \
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self._yearly_capital_costs.loc[0]['D3030_cooling_generation_systems'], \
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self._yearly_capital_costs.loc[0]['D3040_distribution_systems'], \
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self._yearly_capital_costs.loc[0]['D3080_other_hvac_ahu'], \
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self._yearly_capital_costs.loc[0]['D5020_lighting_and_branch_wiring']\
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= [capital_cost_heating_equipment, capital_cost_cooling_equipment, capital_cost_distribution_equipment,
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capital_cost_other_hvac_ahu, capital_cost_lighting]
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reposition_cost_heating_equipment = 0
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reposition_cost_cooling_equipment = 0
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reposition_cost_lighting = 0
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reposition_cost_hvac_ahu = 0
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for year in range(1, self._number_of_years + 1):
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chapter = chapters.chapter('D_services')
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costs_increase = math.pow(1 + self._consumer_price_index, year) / math.pow(1 + self._discount_rate, year)
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if (year % chapter.item('D3020_heat_generating_systems').lifetime) == 0:
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reposition_cost_heating_equipment = peak_heating * chapter.item('D3020_heat_generating_systems').reposition[0] \
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* costs_increase
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self._yearly_capital_costs.loc[year]['D3020_heat_generating_systems'] = reposition_cost_heating_equipment
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if (year % chapter.item('D3030_cooling_generation_systems').lifetime) == 0:
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reposition_cost_cooling_equipment = peak_cooling \
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* chapter.item('D3030_cooling_generation_systems').reposition[0] \
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* costs_increase
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self._yearly_capital_costs.loc[year]['D3030_cooling_generation_systems'] = reposition_cost_cooling_equipment
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if (year % chapter.item('D3080_other_hvac_ahu').lifetime) == 0:
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reposition_cost_hvac_ahu = peak_cooling * chapter.item('D3080_other_hvac_ahu').reposition[0] * costs_increase
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self._yearly_capital_costs.loc[year]['D3080_other_hvac_ahu'] = reposition_cost_hvac_ahu
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if (year % chapter.item('D5020_lighting_and_branch_wiring').lifetime) == 0:
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reposition_cost_lighting = total_floor_area * chapter.item('D5020_lighting_and_branch_wiring').reposition[0] \
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* costs_increase
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self._yearly_capital_costs.loc[year]['D5020_lighting_and_branch_wiring'] = reposition_cost_lighting
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if self._retrofitting_scenario==2 or self._retrofitting_scenario==3 :
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if (year % chapter.item('D301010_photovoltaic_system').lifetime) == 0:
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self._yearly_capital_costs.loc[year]['D301010_photovoltaic_system'] = surface_pv\
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* chapter.item('D301010_photovoltaic_system').reposition[0] * costs_increase
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return self._yearly_capital_costs
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def calculate_end_of_life_costs(self):
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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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self._end_of_life_cost[year]['End_of_life_costs'] = total_floor_area * archetype.end_of_life_cost*price_increase
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return self._end_of_life_cost
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def calculate_total_operational_costs(self):
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building = self._building
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archetype = self._archetype
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total_operational_costs = 0
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peak_cost = 0
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monthly_cost = 0
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variable_cost = 0
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variable_incomes = 0
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total_floor_area = self._total_floor_area
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#todo: split the heating between fuels
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electricity_heating = building.heating_consumption[cte.YEAR][0] / (1000)
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electricity_cooling = building.cooling_consumption[cte.YEAR][0] / (1000)
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electricity_lighting = building.lighting_electrical_demand[cte.YEAR]['insel meb']/1000
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domestic_hot_water_demand = building.domestic_hot_water_consumption[cte.YEAR][0]/1000
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electricity_plug_loads = building.appliances_electrical_demand[cte.YEAR]['insel meb']/1000
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if (building.onsite_electrical_production[cte.YEAR][0] is None):
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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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total_electricity_consumption = electricity_cooling + electricity_heating + electricity_lighting \
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+ domestic_hot_water_demand + electricity_plug_loads
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print(f'total electricity consumption: {total_electricity_consumption}')
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print(f'total electricity production: {onsite_electricity_production}')
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#todo: change when peak electricity demand is coded. Careful with factor residential
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peak_electricity_demand = 100 #self._peak_electricity_demand
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factor_residential= total_floor_area/80
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variable_electricity_cost_year_0 = total_electricity_consumption * archetype.operational_cost.fuels[0].variable[0]
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peak_electricity_cost_year_0 = peak_electricity_demand * archetype.operational_cost.fuels[0].fixed_power * 12
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monthly_electricity_cost_year_0 = archetype.operational_cost.fuels[0].fixed_monthly * 12 * factor_residential
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incomes_electricity_year_0 = onsite_electricity_production * archetype.operational_cost.fuels[0].variable[0]
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fixed_gas_cost_year_0 = archetype.operational_cost.fuels[1].fixed_monthly*12* factor_residential
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variable_gas_cost_year_0 = total_electricity_consumption * archetype.operational_cost.fuels[1].variable[0]
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price_increase_electricity = 0
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price_increase_peak_electricity = 0
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price_increase_gas = 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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price_increase_peak_electricity += math.pow(1 + self._electricity_peak_index, year)
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price_increase_gas += math.pow(1 + self._gas_price_index, year)
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self._yearly_operational_costs[year]['Fixed_costs_electricity_peak']=peak_electricity_cost_year_0*\
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price_increase_peak_electricity
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self._yearly_operational_costs[year]['Fixed_costs_electricity_monthly'] = monthly_electricity_cost_year_0 * \
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price_increase_peak_electricity
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self._yearly_operational_costs[year]['Variable_costs_electricity'] = variable_electricity_cost_year_0 * \
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price_increase_electricity
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self._yearly_operational_costs[year]['Fixed_costs_gas'] = fixed_gas_cost_year_0 * \
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price_increase_gas
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self._yearly_operational_costs[year]['Variable_costs_gas'] = variable_gas_cost_year_0* \
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price_increase_peak_electricity
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self._yearly_operational_costs[year]['Variable_costs_gas'] = variable_gas_cost_year_0 * \
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price_increase_peak_electricity
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return self._yearly_operational_costs
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def calculate_total_operational_incomes(self):
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building = self._building
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archetype = self._archetype
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variable_incomes = 0
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total_floor_area = self._total_floor_area
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if (building.onsite_electrical_production[cte.YEAR][0] is None):
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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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incomes_electricity_year_0 = onsite_electricity_production * archetype.operational_cost.fuels[0].variable[0]
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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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self._yearly_operational_incomes[year]['Incomes electricity']=onsite_electricity_production*\
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price_increase_electricity
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return self._yearly_operational_incomes
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def calculate_total_maintenance_costs(self):
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building = self._building
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archetype = self._archetype
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#todo: change area pv when the variable exists
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surface_pv = 10 #building.area_pv
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peak_heating = building.heating_peak_load
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peak_cooling = building.cooling_peak_load
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maintenance_heating_0 = peak_heating * archetype.operational_cost.maintenance_heating
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maintenance_cooling_0 = peak_cooling * archetype.operational_cost.maintenance_cooling
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maintenance_pv_0 = surface_pv * archetype.operational_cost.maintenance_pv
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for year in range(1, self._number_of_years + 1):
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costs_increase = math.pow(1 + self._consumer_price_index, year) / math.pow(1 + self._discount_rate, year)
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self._yearly_operational_costs[year]['Heating_maintenance'] = maintenance_heating_0 * \
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costs_increase
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self._yearly_operational_costs[year]['Cooling_maintenance'] = maintenance_cooling_0 * \
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costs_increase
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self._yearly_operational_costs[year]['PV_maintenance'] = maintenance_pv_0 * \
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costs_increase
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return self._yearly_operational_costs
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