59 lines
3.4 KiB
Python
59 lines
3.4 KiB
Python
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from pathlib import Path
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from energy_system_modelling_package.energy_system_modelling_factories.energy_system_sizing_factory import \
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EnergySystemsSizingFactory
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from energy_system_modelling_package.energy_system_modelling_factories.montreal_energy_system_archetype_modelling_factory import \
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MontrealEnergySystemArchetypesSimulationFactory
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from hub.imports.energy_systems_factory import EnergySystemsFactory
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from hub.imports.geometry_factory import GeometryFactory
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from hub.helpers.dictionaries import Dictionaries
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from hub.imports.construction_factory import ConstructionFactory
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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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import pandas as pd
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import hub.helpers.constants as cte
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from costing_package.constants import *
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from costing_package.cost import Cost
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# Specify the GeoJSON file path
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input_files_path = (Path(__file__).parent / 'input_files')
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input_files_path.mkdir(parents=True, exist_ok=True)
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geojson_file_path = input_files_path / 'rf_building.geojson'
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output_path = (Path(__file__).parent / 'out_files').resolve()
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output_path.mkdir(parents=True, exist_ok=True)
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simulation_results_path = (Path(__file__).parent / 'out_files' / 'simulation_results').resolve()
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simulation_results_path.mkdir(parents=True, exist_ok=True)
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cost_analysis_output_path = output_path / 'cost_analysis'
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cost_analysis_output_path.mkdir(parents=True, exist_ok=True)
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city = GeometryFactory(file_type='geojson',
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path=geojson_file_path,
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height_field='height',
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year_of_construction_field='year_of_construction',
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function_field='function',
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function_to_hub=Dictionaries().montreal_function_to_hub_function).city
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demands = pd.read_csv(input_files_path / 'cbt_data.csv')
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city.buildings[0].heating_demand[cte.HOUR] = [x * cte.WATTS_HOUR_TO_JULES * 1000 / 4 for x in demands['total'].to_list()]
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city.buildings[0].cooling_demand[cte.HOUR] = [0] * 8760
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city.buildings[0].domestic_hot_water_heat_demand[cte.HOUR] = [0] * 8760
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city.buildings[0].lighting_electrical_demand[cte.HOUR] = [0] * 8760
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city.buildings[0].lighting_electrical_demand[cte.YEAR] = [0]
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city.buildings[0].appliances_electrical_demand[cte.YEAR] = [0]
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city.buildings[0].appliances_electrical_demand[cte.HOUR] = [0] * 8760
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ConstructionFactory('nrcan', city).enrich()
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UsageFactory('nrcan', city).enrich()
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WeatherFactory('epw', city).enrich()
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for building in city.buildings:
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building.energy_systems_archetype_name = ('Central Hydronic Air and Electricity Source Heating System with Unitary '
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'Split and Air Source HP DHW')
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EnergySystemsFactory('montreal_future', city).enrich()
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EnergySystemsSizingFactory('peak_load_sizing', city).enrich()
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for building in city.buildings:
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MontrealEnergySystemArchetypesSimulationFactory(f'archetype_cluster_{building.energy_systems_archetype_cluster_id}',
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building,
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simulation_results_path).enrich()
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for building in city.buildings:
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cost_retrofit_scenario = SYSTEM_RETROFIT
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lcc_dataframe = Cost(building=building,
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retrofit_scenario=cost_retrofit_scenario,
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fuel_tariffs=['Electricity-D', 'Gas-Energir']).life_cycle
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lcc_dataframe.to_csv(cost_analysis_output_path / f'{building.name}_retrofitted_lcc.csv')
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print('test')
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