style correction
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3a7ecb2472
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5
__init__.py
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5
__init__.py
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"""
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Cost workflow initialization
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"""
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@ -1,7 +1,8 @@
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"""
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Costs Workflow
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SPDX - License - Identifier: LGPL - 3.0 - or -later
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Copyright © 2022 Project Author Pilar Monsalvete Álvarez de Uribarri pilar.monsalvete@concordia.ca
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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 glob
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@ -28,6 +29,7 @@ def _npv_from_list(npv_discount_rate, list_cashflow):
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lcc_value = npf.npv(npv_discount_rate, list_cashflow)
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return lcc_value
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def _search_archetype(costs_catalog, building_function):
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costs_archetypes = costs_catalog.entries('archetypes').archetypes
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for building_archetype in costs_archetypes:
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@ -35,7 +37,8 @@ def _search_archetype(costs_catalog, building_function):
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return building_archetype
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raise KeyError('archetype not found')
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file_path = (Path(__file__).parent.parent/'costs_workflow'/'input_files'/'selected_building_2864.geojson')
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file_path = (Path(__file__).parent.parent / 'costs_workflow' / 'input_files' / 'selected_building_2864.geojson')
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climate_reference_city = 'Montreal'
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weather_file = 'CAN_PQ_Montreal.Intl.AP.716270_CWEC.epw'
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weather_format = 'epw'
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@ -44,7 +47,7 @@ usage_format = 'comnet'
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energy_systems_format = 'montreal_custom'
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attic_heated_case = 0
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basement_heated_case = 1
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tmp_folder = (Path(__file__).parent.parent/'monthly_energy_balance_workflow'/'tmp')
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tmp_folder = (Path(__file__).parent.parent / 'monthly_energy_balance_workflow' / 'tmp')
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out_path = (Path(__file__).parent.parent / 'costs_workflow' / 'out_files')
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files = glob.glob(f'{out_path}/*')
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@ -58,7 +61,7 @@ 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_of_construction =2020
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retrofitting_year_of_construction = 2020
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retrofitting_scenarios = [0, 1, 2, 3]
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life_cycle_results = pd.DataFrame()
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@ -96,10 +99,10 @@ for building in city.buildings:
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for retrofitting_scenario in retrofitting_scenarios:
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if retrofitting_scenario == 1 or retrofitting_scenario == 3:
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for building in city.buildings:
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building.year_of_construction=2020
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ConstructionFactory(construction_format, city).enrich()
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print('enrich retrofitted constructions... done')
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for building in city.buildings:
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building.year_of_construction = 2020
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ConstructionFactory(construction_format, city).enrich()
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print('enrich retrofitted constructions... done')
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if retrofitting_scenario == 2 or retrofitting_scenario == 3:
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for building in city.buildings:
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@ -114,50 +117,49 @@ for retrofitting_scenario in retrofitting_scenarios:
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print(f'beginning costing scenario {retrofitting_scenario} systems... done')
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for building in city.buildings:
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#try:
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function = Dictionaries().hub_function_to_montreal_custom_costs_function[building.function]
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archetype = _search_archetype(catalog, function)
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#except KeyError:
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# logger.error(f'Building {building.name} has unknown costs archetype for building function: '
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# f'{building.function}\n')
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# sys.stderr.write(f'Building {building.name} has unknown costs archetype for building function: '
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# f'{building.function}\n')
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#continue
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print('lcc for first building started')
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if "gas" in building.energy_systems_archetype_name:
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#0 to electricity, 1 to gas
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fuel_type = 1
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else:
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fuel_type = 0
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print(f'fuel type {fuel_type}')
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lcc = LifeCycleCosts(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)
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electricity_price_index, gas_price_index, discount_rate, retrofitting_scenario, fuel_type)
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global_capital_costs = 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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df_capital_costs_skin = global_capital_costs['B2010_opaque_walls']+\
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global_capital_costs['B2020_transparent']+\
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global_capital_costs['B3010_opaque_roof']+\
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global_capital_costs['B10_superstructure']
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df_capital_costs_systems = 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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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 = 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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df_maintenance_costs = 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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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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life_cycle_costs_capital_skin = _npv_from_list(discount_rate, df_capital_costs_skin.values.tolist())
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@ -167,12 +169,17 @@ for retrofitting_scenario in retrofitting_scenarios:
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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_costs = life_cycle_costs_capital_skin + life_cycle_costs_capital_systems + \
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life_cycle_costs_end_of_life_costs + life_cycle_operational_costs + \
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life_cycle_maintenance_costs - life_cycle_operational_incomes
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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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)
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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_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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@ -185,6 +192,3 @@ for retrofitting_scenario in retrofitting_scenarios:
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print(life_cycle_results)
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print(f'Scenario {retrofitting_scenario} {life_cycle_costs}')
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@ -2,18 +2,23 @@
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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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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 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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CURRENT_STATUS = 0
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SKIN_RETROFIT = 1
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SYSTEM_RETROFIT_AND_PV = 2
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SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV = 3
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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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@ -80,61 +85,62 @@ class LifeCycleCosts:
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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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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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= [0, 0, 0, 0, 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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= [0, 0, 0, 0, 0]
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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, 'B_Shell'] = 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_costs.fillna(0, inplace=True)
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if self._retrofitting_scenario == 1 or self._retrofitting_scenario == 3:
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if self._retrofitting_scenario in (self.SKIN_RETROFIT, self.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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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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self._yearly_capital_costs.loc[0, 'B2010_opaque_walls'] = capital_cost_opaque
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self._yearly_capital_costs.loc[0]['B2020_transparent'] = capital_cost_transparent
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self._yearly_capital_costs.loc[0, 'B3010_opaque_roof'] = capital_cost_roof
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self._yearly_capital_costs.loc[0]['B10_superstructure'] = capital_cost_ground
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self._yearly_capital_costs.loc[0, 'B_Shell'] = capital_cost_skin
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if self._retrofitting_scenario == 2 or self._retrofitting_scenario == 3:
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if self._retrofitting_scenario in (self.SYSTEM_RETROFIT_AND_PV , self.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 = 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_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
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self._yearly_capital_costs.loc[0, 'D3030_cooling_generation_systems'] = capital_cost_cooling_equipment
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self._yearly_capital_costs.loc[0, 'D3040_distribution_systems'] = capital_cost_distribution_equipment
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self._yearly_capital_costs.loc[0, 'D3080_other_hvac_ahu'] = capital_cost_other_hvac_ahu
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self._yearly_capital_costs.loc[0, 'D5020_lighting_and_branch_wiring'] = capital_cost_lighting
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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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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) / math.pow(1 + self._discount_rate, year)
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@ -269,7 +275,7 @@ class LifeCycleCosts:
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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)
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self._yearly_maintenance_costs.loc[year, 'Heating_maintenance'] = maintenance_heating_0 * \
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