370 lines
20 KiB
Python
370 lines
20 KiB
Python
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"""
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LifeCycleCosts module 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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Code contributor Oriol Gavalda 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_financial as npf
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import hub.helpers.constants as cte
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from costs import SKIN_RETROFIT, SYSTEM_RETROFIT_AND_PV, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV, PERCENTAGE_CREDIT,INTEREST_RATE,CREDIT_YEARS
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class LifeCycleCosts:
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"""
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Life cycle cost class
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"""
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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, fuel_type):
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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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self._fuel_type = fuel_type
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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',
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'D3020_heat_generating_systems',
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'D3030_cooling_generation_systems',
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'D3040_distribution_systems',
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'D3080_other_hvac_ahu',
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'D5020_lighting_and_branch_wiring'],
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dtype='float')
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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_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'],
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dtype='float')
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self._yearly_maintenance_costs = pd.DataFrame(index=rng, columns=['Heating_maintenance', 'Cooling_maintenance',
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'PV_maintenance'], dtype='float')
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self._yearly_operational_incomes = pd.DataFrame(index=rng, columns=['Incomes electricity'], dtype='float')
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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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: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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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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capital_cost_pv = 0
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capital_cost_opaque = 0
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capital_cost_ground = 0
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capital_cost_transparent = 0
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capital_cost_roof = 0
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capital_cost_heating_equipment = 0
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capital_cost_cooling_equipment = 0
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capital_cost_distribution_equipment = 0
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capital_cost_other_hvac_ahu = 0
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capital_cost_lighting = 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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peak_heating = building.heating_peak_load[cte.YEAR].values[0]/1000
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peak_cooling = building.cooling_peak_load[cte.YEAR].values[0]/1000
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# todo: change area pv when the variable exists
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roof_area = 0
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for roof in building.roofs:
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roof_area += roof.solid_polygon.area
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surface_pv = roof_area * 0.5
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self._yearly_capital_costs.loc[0, 'B2010_opaque_walls'] = 0
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self._yearly_capital_costs.loc[0]['B2020_transparent'] = 0
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self._yearly_capital_costs.loc[0, 'B3010_opaque_roof'] = 0
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self._yearly_capital_costs.loc[0]['B10_superstructure'] = 0
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self._yearly_capital_costs.loc[0, 'D3020_heat_generating_systems'] = 0
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self._yearly_capital_costs.loc[0, 'D3030_cooling_generation_systems'] = 0
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self._yearly_capital_costs.loc[0, 'D3040_distribution_systems'] = 0
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self._yearly_capital_costs.loc[0, 'D3080_other_hvac_ahu'] = 0
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self._yearly_capital_costs.loc[0, 'D5020_lighting_and_branch_wiring'] = 0
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self._yearly_capital_incomes.loc[0, 'Subsidies construction'] = 0
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self._yearly_capital_incomes.loc[0, 'Subsidies HVAC'] = 0
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self._yearly_capital_incomes.loc[0, 'Subsidies PV'] = 0
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self._yearly_capital_costs.fillna(0, inplace=True)
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if self._retrofitting_scenario in (SKIN_RETROFIT, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV):
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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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self._yearly_capital_costs.loc[0, 'B2010_opaque_walls'] = capital_cost_opaque * (1-PERCENTAGE_CREDIT)
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self._yearly_capital_costs.loc[0]['B2020_transparent'] = capital_cost_transparent * (1-PERCENTAGE_CREDIT)
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self._yearly_capital_costs.loc[0, 'B3010_opaque_roof'] = capital_cost_roof * (1-PERCENTAGE_CREDIT)
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self._yearly_capital_costs.loc[0]['B10_superstructure'] = capital_cost_ground * (1-PERCENTAGE_CREDIT)
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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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self._yearly_capital_costs.loc[0]['D301010_photovoltaic_system'] = capital_cost_pv
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capital_cost_heating_equipment = (
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peak_heating * chapter.item('D3020_heat_generating_systems').initial_investment[0]
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)
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capital_cost_cooling_equipment = (
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peak_cooling * chapter.item('D3030_cooling_generation_systems').initial_investment[0]
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)
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capital_cost_distribution_equipment = (
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peak_cooling * chapter.item('D3040_distribution_systems').initial_investment[0]
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)
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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 * chapter.item('D5020_lighting_and_branch_wiring').initial_investment[0]
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self._yearly_capital_costs.loc[0, 'D3020_heat_generating_systems'] = capital_cost_heating_equipment * (1-PERCENTAGE_CREDIT)
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self._yearly_capital_costs.loc[0, 'D3030_cooling_generation_systems'] = capital_cost_cooling_equipment * (1-PERCENTAGE_CREDIT)
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self._yearly_capital_costs.loc[0, 'D3040_distribution_systems'] = capital_cost_distribution_equipment * (1-PERCENTAGE_CREDIT)
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self._yearly_capital_costs.loc[0, 'D3080_other_hvac_ahu'] = capital_cost_other_hvac_ahu * (1-PERCENTAGE_CREDIT)
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self._yearly_capital_costs.loc[0, 'D5020_lighting_and_branch_wiring'] = capital_cost_lighting * (1-PERCENTAGE_CREDIT)
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for year in range(1, self._number_of_years):
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chapter = chapters.chapter('D_services')
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costs_increase = math.pow(1 + self._consumer_price_index, year)
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self._yearly_capital_costs.loc[year, 'B2010_opaque_walls'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS,
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capital_cost_opaque * (PERCENTAGE_CREDIT))
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self._yearly_capital_costs.loc[year, 'B2020_transparent'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS,
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capital_cost_transparent * (PERCENTAGE_CREDIT)
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)
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self._yearly_capital_costs.loc[year, 'B3010_opaque_roof'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS,capital_cost_roof
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* (PERCENTAGE_CREDIT))
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self._yearly_capital_costs.loc[year, 'B10_superstructure'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS,
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capital_cost_ground * (PERCENTAGE_CREDIT))
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self._yearly_capital_costs.loc[year, 'D3020_heat_generating_systems'] = -npf.pmt(INTEREST_RATE,CREDIT_YEARS,
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capital_cost_heating_equipment
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* (PERCENTAGE_CREDIT))
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self._yearly_capital_costs.loc[year, 'D3030_cooling_generation_systems'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS,
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capital_cost_cooling_equipment
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* (PERCENTAGE_CREDIT))
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self._yearly_capital_costs.loc[year, 'D3040_distribution_systems'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS,
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capital_cost_distribution_equipment
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* (PERCENTAGE_CREDIT))
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self._yearly_capital_costs.loc[year, 'D3080_other_hvac_ahu'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS,
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capital_cost_other_hvac_ahu
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* (PERCENTAGE_CREDIT))
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self._yearly_capital_costs.loc[year, 'D5020_lighting_and_branch_wiring'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS,
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capital_cost_lighting
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* (PERCENTAGE_CREDIT))
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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 in (SYSTEM_RETROFIT_AND_PV, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV):
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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(
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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 = (
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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'] = (
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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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return self._yearly_capital_costs, self._yearly_capital_incomes
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def calculate_end_of_life_costs(self):
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"""
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Calculate end of life costs
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:return: pd.DataFrame
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"""
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archetype = self._archetype
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total_floor_area = self._total_floor_area
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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._yearly_end_of_life_costs.at[
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year, 'End_of_life_costs'] = total_floor_area * archetype.end_of_life_cost * price_increase
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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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: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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total_floor_area = self._total_floor_area
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factor_residential = total_floor_area / 80
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# todo: split the heating between fuels
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fixed_gas_cost_year_0 = 0
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variable_gas_cost_year_0 = 0
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electricity_heating = 0
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domestic_hot_water_electricity = 0
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if self._fuel_type == 1:
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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 = (
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(building.heating_consumption[cte.YEAR][0] + building.domestic_hot_water_consumption[cte.YEAR][0]) / 1000 *
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archetype.operational_cost.fuels[1].variable[0]
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)
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if self._fuel_type == 0:
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electricity_heating = building.heating_consumption[cte.YEAR][0] / 1000
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domestic_hot_water_electricity = building.domestic_hot_water_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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electricity_plug_loads = building.appliances_electrical_demand[cte.YEAR]['insel meb'] / 1000
|
||
|
|
electricity_distribution = 0
|
||
|
|
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
|
||
|
|
|
||
|
|
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'] = float(
|
||
|
|
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):
|
||
|
|
"""
|
||
|
|
Calculate total operational incomes
|
||
|
|
:return: pd.DataFrame
|
||
|
|
"""
|
||
|
|
building = self._building
|
||
|
|
if cte.YEAR not in building.onsite_electrical_production:
|
||
|
|
onsite_electricity_production = 0
|
||
|
|
else:
|
||
|
|
onsite_electricity_production = building.onsite_electrical_production[cte.YEAR][0]/1000
|
||
|
|
|
||
|
|
for year in range(1, self._number_of_years + 1):
|
||
|
|
price_increase_electricity = math.pow(1 + self._electricity_price_index, year)
|
||
|
|
# todo: check the adequate assignation of price. Pilar
|
||
|
|
price_export = 0.075 # archetype.income.electricity_export
|
||
|
|
self._yearly_operational_incomes.loc[year, 'Incomes electricity'] = (
|
||
|
|
onsite_electricity_production * price_export * price_increase_electricity
|
||
|
|
)
|
||
|
|
|
||
|
|
self._yearly_operational_incomes.fillna(0, inplace=True)
|
||
|
|
return self._yearly_operational_incomes
|
||
|
|
|
||
|
|
def calculate_total_maintenance_costs(self):
|
||
|
|
"""
|
||
|
|
Calculate total maintenance costs
|
||
|
|
:return: pd.DataFrame
|
||
|
|
"""
|
||
|
|
building = self._building
|
||
|
|
archetype = self._archetype
|
||
|
|
# todo: change area pv when the variable exists
|
||
|
|
roof_area = 0
|
||
|
|
for roof in building.roofs:
|
||
|
|
roof_area += roof.solid_polygon.area
|
||
|
|
surface_pv = roof_area * 0.5
|
||
|
|
|
||
|
|
peak_heating = building.heating_peak_load[cte.YEAR][cte.HEATING_PEAK_LOAD][0]
|
||
|
|
peak_cooling = building.cooling_peak_load[cte.YEAR][cte.COOLING_PEAK_LOAD][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
|
||
|
|
|
||
|
|
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
|