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Guille Gutierrez 2023-05-30 15:08:11 -04:00
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3 changed files with 100 additions and 85 deletions
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__init__.py Normal file
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"""
Cost workflow initialization
"""

66
main.py → __main__.py
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@ -1,7 +1,8 @@
""" """
Costs Workflow Costs Workflow
SPDX - License - Identifier: LGPL - 3.0 - or -later SPDX - License - Identifier: LGPL - 3.0 - or -later
Copyright © 2022 Project Author Pilar Monsalvete Álvarez de Uribarri pilar.monsalvete@concordia.ca Copyright © 2022 Project Author Pilar Monsalvete Alvarez de Uribarri pilar.monsalvete@concordia.ca
Code contributor Oriol Gavalda Torrellas oriol.gavalda@concordia.ca
""" """
import glob import glob
@ -28,6 +29,7 @@ def _npv_from_list(npv_discount_rate, list_cashflow):
lcc_value = npf.npv(npv_discount_rate, list_cashflow) lcc_value = npf.npv(npv_discount_rate, list_cashflow)
return lcc_value return lcc_value
def _search_archetype(costs_catalog, building_function): def _search_archetype(costs_catalog, building_function):
costs_archetypes = costs_catalog.entries('archetypes').archetypes costs_archetypes = costs_catalog.entries('archetypes').archetypes
for building_archetype in costs_archetypes: for building_archetype in costs_archetypes:
@ -35,6 +37,7 @@ def _search_archetype(costs_catalog, building_function):
return building_archetype return building_archetype
raise KeyError('archetype not found') raise KeyError('archetype not found')
file_path = (Path(__file__).parent.parent / 'costs_workflow' / 'input_files' / 'selected_building_2864.geojson') file_path = (Path(__file__).parent.parent / 'costs_workflow' / 'input_files' / 'selected_building_2864.geojson')
climate_reference_city = 'Montreal' climate_reference_city = 'Montreal'
weather_file = 'CAN_PQ_Montreal.Intl.AP.716270_CWEC.epw' weather_file = 'CAN_PQ_Montreal.Intl.AP.716270_CWEC.epw'
@ -114,18 +117,11 @@ for retrofitting_scenario in retrofitting_scenarios:
print(f'beginning costing scenario {retrofitting_scenario} systems... done') print(f'beginning costing scenario {retrofitting_scenario} systems... done')
for building in city.buildings: for building in city.buildings:
#try:
function = Dictionaries().hub_function_to_montreal_custom_costs_function[building.function] function = Dictionaries().hub_function_to_montreal_custom_costs_function[building.function]
archetype = _search_archetype(catalog, function) archetype = _search_archetype(catalog, function)
#except KeyError:
# logger.error(f'Building {building.name} has unknown costs archetype for building function: '
# f'{building.function}\n')
# sys.stderr.write(f'Building {building.name} has unknown costs archetype for building function: '
# f'{building.function}\n')
#continue
print('lcc for first building started') print('lcc for first building started')
if "gas" in building.energy_systems_archetype_name: if "gas" in building.energy_systems_archetype_name:
#0 to electricity, 1 to gas
fuel_type = 1 fuel_type = 1
else: else:
fuel_type = 0 fuel_type = 0
@ -138,26 +134,32 @@ for retrofitting_scenario in retrofitting_scenarios:
global_operational_costs = lcc.calculate_total_operational_costs() global_operational_costs = lcc.calculate_total_operational_costs()
global_maintenance_costs = lcc.calculate_total_maintenance_costs() global_maintenance_costs = lcc.calculate_total_maintenance_costs()
global_operational_incomes = lcc.calculate_total_operational_incomes() global_operational_incomes = lcc.calculate_total_operational_incomes()
df_capital_costs_skin = global_capital_costs['B2010_opaque_walls']+\ df_capital_costs_skin = (
global_capital_costs['B2020_transparent']+\ global_capital_costs['B2010_opaque_walls'] + global_capital_costs['B2020_transparent'] +
global_capital_costs['B3010_opaque_roof']+\ global_capital_costs['B3010_opaque_roof'] + global_capital_costs['B10_superstructure']
global_capital_costs['B10_superstructure'] )
df_capital_costs_systems = global_capital_costs['D3020_heat_generating_systems']+\ df_capital_costs_systems = (
global_capital_costs['D3030_cooling_generation_systems']+\ global_capital_costs['D3020_heat_generating_systems'] +
global_capital_costs['D3080_other_hvac_ahu']+\ global_capital_costs['D3030_cooling_generation_systems'] +
global_capital_costs['D5020_lighting_and_branch_wiring']+\ global_capital_costs['D3080_other_hvac_ahu'] +
global_capital_costs['D5020_lighting_and_branch_wiring'] +
global_capital_costs['D301010_photovoltaic_system'] global_capital_costs['D301010_photovoltaic_system']
)
df_end_of_life_costs = global_end_of_life_costs['End_of_life_costs'] df_end_of_life_costs = global_end_of_life_costs['End_of_life_costs']
df_operational_costs = global_operational_costs['Fixed_costs_electricity_peak']+\ df_operational_costs = (
global_operational_costs['Fixed_costs_electricity_monthly']+\ global_operational_costs['Fixed_costs_electricity_peak'] +
global_operational_costs['Fixed_costs_electricity_peak']+\ global_operational_costs['Fixed_costs_electricity_monthly'] +
global_operational_costs['Fixed_costs_electricity_monthly']+\ global_operational_costs['Fixed_costs_electricity_peak'] +
global_operational_costs['Variable_costs_electricity']+ \ global_operational_costs['Fixed_costs_electricity_monthly'] +
global_operational_costs['Fixed_costs_gas']+ \ global_operational_costs['Variable_costs_electricity'] +
global_operational_costs['Fixed_costs_gas'] +
global_operational_costs['Variable_costs_gas'] global_operational_costs['Variable_costs_gas']
df_maintenance_costs = global_maintenance_costs['Heating_maintenance']+\ )
global_maintenance_costs['Cooling_maintenance']+\ df_maintenance_costs = (
global_maintenance_costs['Heating_maintenance'] +
global_maintenance_costs['Cooling_maintenance'] +
global_maintenance_costs['PV_maintenance'] global_maintenance_costs['PV_maintenance']
)
df_operational_incomes = global_operational_incomes['Incomes electricity'] df_operational_incomes = global_operational_incomes['Incomes electricity']
life_cycle_costs_capital_skin = _npv_from_list(discount_rate, df_capital_costs_skin.values.tolist()) life_cycle_costs_capital_skin = _npv_from_list(discount_rate, df_capital_costs_skin.values.tolist())
@ -167,9 +169,14 @@ for retrofitting_scenario in retrofitting_scenarios:
life_cycle_maintenance_costs = _npv_from_list(discount_rate, df_maintenance_costs.values.tolist()) life_cycle_maintenance_costs = _npv_from_list(discount_rate, df_maintenance_costs.values.tolist())
life_cycle_operational_incomes = _npv_from_list(discount_rate, df_operational_incomes.values.tolist()) life_cycle_operational_incomes = _npv_from_list(discount_rate, df_operational_incomes.values.tolist())
life_cycle_costs = life_cycle_costs_capital_skin + life_cycle_costs_capital_systems + \ life_cycle_costs = (
life_cycle_costs_end_of_life_costs + life_cycle_operational_costs + \ life_cycle_costs_capital_skin +
life_cycle_maintenance_costs - life_cycle_operational_incomes life_cycle_costs_capital_systems +
life_cycle_costs_end_of_life_costs +
life_cycle_operational_costs +
life_cycle_maintenance_costs -
life_cycle_operational_incomes
)
life_cycle_results[f'Scenario {retrofitting_scenario}'] = [life_cycle_costs_capital_skin, life_cycle_results[f'Scenario {retrofitting_scenario}'] = [life_cycle_costs_capital_skin,
life_cycle_costs_capital_systems, life_cycle_costs_capital_systems,
@ -185,6 +192,3 @@ for retrofitting_scenario in retrofitting_scenarios:
print(life_cycle_results) print(life_cycle_results)
print(f'Scenario {retrofitting_scenario} {life_cycle_costs}') print(f'Scenario {retrofitting_scenario} {life_cycle_costs}')

88
life_cycle_costs.py
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@ -2,18 +2,23 @@
LifeCycleCosts calculates the life cycle costs of one building LifeCycleCosts calculates the life cycle costs of one building
SPDX - License - Identifier: LGPL - 3.0 - or -later SPDX - License - Identifier: LGPL - 3.0 - or -later
Copyright © 2022 Project Author Pilar Monsalvete Alvarez de Uribarri pilar_monsalvete@concordia.ca Copyright © 2022 Project Author Pilar Monsalvete Alvarez de Uribarri pilar_monsalvete@concordia.ca
Project contributor © 2023 Author Oriol Gavaldà Torrellas oriol.gavalda@concordia.ca Code contributor Oriol Gavalda Torrellas oriol.gavalda@concordia.ca
""" """
import math import math
import pandas as pd import pandas as pd
import numpy as np
from datetime import date
import hub.helpers.constants as cte import hub.helpers.constants as cte
class LifeCycleCosts: class LifeCycleCosts:
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, def __init__(self, building, archetype, number_of_years, consumer_price_index, electricity_peak_index,
electricity_price_index, gas_price_index, discount_rate, electricity_price_index, gas_price_index, discount_rate,
retrofitting_scenario, fuel_type): retrofitting_scenario, fuel_type):
@ -80,61 +85,62 @@ class LifeCycleCosts:
surface_transparent += thermal_boundary.opaque_area * thermal_boundary.window_ratio surface_transparent += thermal_boundary.opaque_area * thermal_boundary.window_ratio
chapters = archetype.capital_cost chapters = archetype.capital_cost
capital_cost_skin = 0
capital_cost_services = 0
capital_cost_pv = 0
peak_heating = building.heating_peak_load[cte.YEAR].values[0] peak_heating = building.heating_peak_load[cte.YEAR].values[0]
peak_cooling = building.cooling_peak_load[cte.YEAR].values[0] peak_cooling = building.cooling_peak_load[cte.YEAR].values[0]
# todo: put the value of area_pv when it exists # todo: change area pv when the variable exists
surface_pv = 10 # building.area_pv roof_area = 0
self._yearly_capital_costs.loc[0, 'B2010_opaque_walls'], self._yearly_capital_costs.loc[0]['B2020_transparent'], \ for roof in building.roofs:
self._yearly_capital_costs.loc[0, 'B3010_opaque_roof'], self._yearly_capital_costs.loc[0]['B10_superstructure'], \ roof_area += roof.solid_polygon.area
self._yearly_capital_costs.loc[0, 'B_Shell'] \ surface_pv = roof_area * 0.5
= [0, 0, 0, 0, 0]
self._yearly_capital_costs.loc[0, 'D3020_heat_generating_systems'], \ self._yearly_capital_costs.loc[0, 'B2010_opaque_walls'] = 0
self._yearly_capital_costs.loc[0, 'D3030_cooling_generation_systems'], \ self._yearly_capital_costs.loc[0]['B2020_transparent'] = 0
self._yearly_capital_costs.loc[0, 'D3040_distribution_systems'], \ self._yearly_capital_costs.loc[0, 'B3010_opaque_roof'] = 0
self._yearly_capital_costs.loc[0, 'D3080_other_hvac_ahu'], \ self._yearly_capital_costs.loc[0]['B10_superstructure'] = 0
self._yearly_capital_costs.loc[0, 'D5020_lighting_and_branch_wiring'] \ self._yearly_capital_costs.loc[0, 'B_Shell'] = 0
= [0, 0, 0, 0, 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
self._yearly_capital_costs.fillna(0, inplace=True) self._yearly_capital_costs.fillna(0, inplace=True)
if self._retrofitting_scenario == 1 or self._retrofitting_scenario == 3: if self._retrofitting_scenario in (self.SKIN_RETROFIT, self.SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV):
chapter = chapters.chapter('B_shell') chapter = chapters.chapter('B_shell')
capital_cost_opaque = surface_opaque * chapter.item('B2010_opaque_walls').refurbishment[0] 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_transparent = surface_transparent * chapter.item('B2020_transparent').refurbishment[0]
capital_cost_roof = surface_roof * chapter.item('B3010_opaque_roof').refurbishment[0] capital_cost_roof = surface_roof * chapter.item('B3010_opaque_roof').refurbishment[0]
capital_cost_ground = surface_ground * chapter.item('B10_superstructure').refurbishment[0] capital_cost_ground = surface_ground * chapter.item('B10_superstructure').refurbishment[0]
capital_cost_skin = capital_cost_opaque + capital_cost_transparent + capital_cost_roof + capital_cost_ground capital_cost_skin = capital_cost_opaque + capital_cost_transparent + capital_cost_roof + capital_cost_ground
self._yearly_capital_costs.loc[0, 'B2010_opaque_walls'], self._yearly_capital_costs.loc[0]['B2020_transparent'], \ self._yearly_capital_costs.loc[0, 'B2010_opaque_walls'] = capital_cost_opaque
self._yearly_capital_costs.loc[0, 'B3010_opaque_roof'], self._yearly_capital_costs.loc[0]['B10_superstructure'], \ self._yearly_capital_costs.loc[0]['B2020_transparent'] = capital_cost_transparent
self._yearly_capital_costs.loc[0, 'B_Shell'] \ self._yearly_capital_costs.loc[0, 'B3010_opaque_roof'] = capital_cost_roof
= [capital_cost_opaque, capital_cost_transparent, capital_cost_roof, capital_cost_ground, capital_cost_skin] self._yearly_capital_costs.loc[0]['B10_superstructure'] = capital_cost_ground
self._yearly_capital_costs.loc[0, 'B_Shell'] = capital_cost_skin
if self._retrofitting_scenario == 2 or self._retrofitting_scenario == 3: if self._retrofitting_scenario in (self.SYSTEM_RETROFIT_AND_PV , self.SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV):
chapter = chapters.chapter('D_services') chapter = chapters.chapter('D_services')
capital_cost_pv = surface_pv * chapter.item('D301010_photovoltaic_system').initial_investment[0] 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 self._yearly_capital_costs.loc[0]['D301010_photovoltaic_system'] = capital_cost_pv
capital_cost_heating_equipment = (
capital_cost_heating_equipment = peak_heating \ peak_heating * chapter.item('D3020_heat_generating_systems').initial_investment[0]
* chapter.item('D3020_heat_generating_systems').initial_investment[0] )
capital_cost_cooling_equipment = peak_cooling \ capital_cost_cooling_equipment = (
* chapter.item('D3030_cooling_generation_systems').initial_investment[0] 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_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_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] capital_cost_lighting = total_floor_area * chapter.item('D5020_lighting_and_branch_wiring').initial_investment[0]
self._yearly_capital_costs.loc[0, 'D3020_heat_generating_systems'], = 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
self._yearly_capital_costs.loc[0, 'D3020_heat_generating_systems'], \
self._yearly_capital_costs.loc[0, 'D3030_cooling_generation_systems'], \
self._yearly_capital_costs.loc[0, 'D3040_distribution_systems'], \
self._yearly_capital_costs.loc[0, 'D3080_other_hvac_ahu'], \
self._yearly_capital_costs.loc[0, 'D5020_lighting_and_branch_wiring'] \
= [capital_cost_heating_equipment, capital_cost_cooling_equipment, capital_cost_distribution_equipment,
capital_cost_other_hvac_ahu, capital_cost_lighting]
for year in range(1, self._number_of_years): for year in range(1, self._number_of_years):
chapter = chapters.chapter('D_services') chapter = chapters.chapter('D_services')
costs_increase = math.pow(1 + self._consumer_price_index, year) / math.pow(1 + self._discount_rate, year) costs_increase = math.pow(1 + self._consumer_price_index, year) / math.pow(1 + self._discount_rate, year)