costs_workflow/life_cycle_costs.py

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"""
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
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Code contributor Oriol Gavalda Torrellas oriol.gavalda@concordia.ca
"""
import math
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import pandas as pd
import hub.helpers.constants as cte
class LifeCycleCosts:
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CURRENT_STATUS = 0
SKIN_RETROFIT = 1
SYSTEM_RETROFIT_AND_PV = 2
SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV = 3
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,
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:
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for thermal_zone in internal_zone.thermal_zones:
self._total_floor_area += thermal_zone.total_floor_area
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# todo: revise if it works
rng = range(number_of_years)
self._yearly_capital_costs = pd.DataFrame(index=rng, columns=['B2010_opaque_walls', 'B2020_transparent',
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'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',
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'Variable_costs_electricity', 'Fixed_costs_gas',
'Variable_costs_gas'],
dtype='float')
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self._yearly_maintenance_costs = pd.DataFrame(index=rng, columns=['Heating_maintenance', 'Cooling_maintenance',
'PV_maintenance'], dtype='float')
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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:
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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
peak_heating = building.heating_peak_load[cte.YEAR].values[0]
peak_cooling = building.cooling_peak_load[cte.YEAR].values[0]
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# 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
self._yearly_capital_costs.loc[0, 'B2010_opaque_walls'] = 0
self._yearly_capital_costs.loc[0]['B2020_transparent'] = 0
self._yearly_capital_costs.loc[0, 'B3010_opaque_roof'] = 0
self._yearly_capital_costs.loc[0]['B10_superstructure'] = 0
self._yearly_capital_costs.loc[0, 'B_Shell'] = 0
self._yearly_capital_costs.loc[0, 'D3020_heat_generating_systems'] = 0
self._yearly_capital_costs.loc[0, 'D3030_cooling_generation_systems'] = 0
self._yearly_capital_costs.loc[0, 'D3040_distribution_systems'] = 0
self._yearly_capital_costs.loc[0, 'D3080_other_hvac_ahu'] = 0
self._yearly_capital_costs.loc[0, 'D5020_lighting_and_branch_wiring'] = 0
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self._yearly_capital_costs.fillna(0, inplace=True)
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if self._retrofitting_scenario in (self.SKIN_RETROFIT, self.SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV):
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]
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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'] = capital_cost_opaque
self._yearly_capital_costs.loc[0]['B2020_transparent'] = capital_cost_transparent
self._yearly_capital_costs.loc[0, 'B3010_opaque_roof'] = capital_cost_roof
self._yearly_capital_costs.loc[0]['B10_superstructure'] = capital_cost_ground
self._yearly_capital_costs.loc[0, 'B_Shell'] = capital_cost_skin
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if self._retrofitting_scenario in (self.SYSTEM_RETROFIT_AND_PV , self.SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV):
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
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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]
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self._yearly_capital_costs.loc[0, 'D3020_heat_generating_systems'], = capital_cost_heating_equipment
self._yearly_capital_costs.loc[0, 'D3030_cooling_generation_systems'] = capital_cost_cooling_equipment
self._yearly_capital_costs.loc[0, 'D3040_distribution_systems'] = capital_cost_distribution_equipment
self._yearly_capital_costs.loc[0, 'D3080_other_hvac_ahu'] = capital_cost_other_hvac_ahu
self._yearly_capital_costs.loc[0, 'D5020_lighting_and_branch_wiring'] = 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)
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
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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
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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
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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
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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:
if (year % chapter.item('D301010_photovoltaic_system').lifetime) == 0:
self._yearly_capital_costs.loc[year]['D301010_photovoltaic_system'] = surface_pv \
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* 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:
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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
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# 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 * 12 * factor_residential
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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)
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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
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# todo: change when peak electricity demand is coded. Careful with factor residential
peak_electricity_demand = 100 # self._peak_electricity_demand
print(f'total_electricity_cooling {electricity_cooling}')
print(f'total_electricity_lighting {electricity_lighting}')
print(f'total_electricity_plug_loads {electricity_plug_loads}')
print(f'total_electricity_consumption {total_electricity_consumption}')
print(f'price_electricity {archetype.operational_cost.fuels[0].variable[0]}')
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)
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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):
building = self._building
archetype = self._archetype
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if cte.YEAR not in building.onsite_electrical_production:
onsite_electricity_production = 0
else:
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onsite_electricity_production = building.onsite_electrical_production[cte.YEAR][0]/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)
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self._yearly_operational_incomes.loc[year, 'Incomes electricity'] = onsite_electricity_production * \
price_increase_electricity
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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
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# 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
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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
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for year in range(1, self._number_of_years + 1):
costs_increase = math.pow(1 + self._consumer_price_index, year)
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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