139 lines
5.6 KiB
Python
139 lines
5.6 KiB
Python
"""
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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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"""
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import glob
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import os
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from pathlib import Path
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import sys
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import pandas as pd
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from hub.imports.construction_factory import ConstructionFactory
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from hub.helpers.dictionaries import Dictionaries
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from hub.hub_logger import logger
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from hub.imports.geometry_factory import GeometryFactory
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from hub.imports.usage_factory import UsageFactory
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from hub.imports.weather_factory import WeatherFactory
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from hub.catalog_factories.costs_catalog_factory import CostCatalogFactory
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import hub.helpers.constants as cte
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from monthly_energy_balance_engine import MonthlyEnergyBalanceEngine
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from sra_engine import SraEngine
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from life_cycle_costs import LifeCycleCosts
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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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if str(building_function) == str(building_archetype.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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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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construction_format = 'nrcan'
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usage_format = 'nrcan'
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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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out_path = (Path(__file__).parent.parent / 'costs_workflow' / 'out_files')
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files = glob.glob(f'{out_path}/*')
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retrofitting_year_of_construction = 2015
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for file in files:
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if file != '.gitignore':
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os.remove(file)
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number_of_years = 30
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consumer_price_index = 0.04
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discount_rate = 0.03
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peak_electricity_demand = 33
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factor_pv = 0.5
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factor_peak_lights = 0.07
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retrofitting_scenarios = [0, 1, 2, 3]
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life_cycle_results = pd.DataFrame()
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for retrofitting_scenario in retrofitting_scenarios:
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if retrofitting_scenario == 2 or retrofitting_scenario == 3:
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heating_scop = 3
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cooling_seer = 4.5
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else:
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heating_scop = 1
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cooling_seer = 2.8
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print('[simulation start]')
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city = GeometryFactory('geojson',
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path=file_path,
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height_field='heightmax',
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name_field='OBJECTID_12',
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year_of_construction_field='ANNEE_CONS',
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function_field='CODE_UTILI',
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function_to_hub=Dictionaries().montreal_function_to_hub_function).city
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print(f'city created from {file_path}')
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city.climate_reference_city = climate_reference_city
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city.climate_file = (tmp_folder / f'{climate_reference_city}.cli').resolve()
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print(f'city created from {file_path}')
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WeatherFactory(weather_format, city, file_name=weather_file).enrich()
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print('enrich weather... done')
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UsageFactory(usage_format, city).enrich()
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print('enrich usage... done')
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catalog = CostCatalogFactory('montreal_custom').catalog
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print('costs catalog access... done')
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if retrofitting_scenario == 0 or retrofitting_scenario == 2:
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for building in city.buildings:
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building.year_of_construction = retrofitting_year_of_construction
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ConstructionFactory(construction_format, city).enrich()
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print('enrich constructions... done')
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# sra + monthly running
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print('exporting:')
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sra_file = (tmp_folder / f'{city.name}_sra.xml').resolve()
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SraEngine(city, sra_file, tmp_folder, weather_file)
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# Assign radiation to the city
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print(' sra processed...')
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for building in city.buildings:
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building.attic_heated = attic_heated_case
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building.basement_heated = basement_heated_case
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MonthlyEnergyBalanceEngine(city, tmp_folder)
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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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lcc = LifeCycleCosts(building, archetype, number_of_years, consumer_price_index,
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discount_rate, retrofitting_scenario, heating_scop, cooling_seer,
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peak_electricity_demand, factor_pv,factor_peak_lights)
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total_capital_costs, yearly_capital_costs = lcc.calculate_capital_costs()
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end_of_life_costs = lcc.calculate_end_of_life_costs()
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total_operational_costs = lcc.calculate_total_operational_costs()
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total_maintenance_costs = lcc.calculate_total_maintenance_costs()
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life_cycle_costs = total_capital_costs + end_of_life_costs + total_operational_costs + total_maintenance_costs
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life_cycle_results[f'Scenario {retrofitting_scenario}'] = [total_capital_costs, end_of_life_costs,
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total_operational_costs, total_maintenance_costs,
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life_cycle_costs]
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life_cycle_results.index = ['total_capital_costs', 'end_of_life_costs', 'total_operational_costs',
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'total_maintenance_costs', 'life_cycle_costs']
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life_cycle_results.to_excel(Path(__file__).parent/'out_files'/'Results.xlsx', index=True)
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