68 lines
4.2 KiB
Python
68 lines
4.2 KiB
Python
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from hub.imports.energy_systems_factory import EnergySystemsFactory
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from hub.imports.results_factory import ResultFactory
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from pathlib import Path
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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 json
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import hub.helpers.constants as cte
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from scripts.energy_system_sizing_and_simulation_factory import EnergySystemsSimulationFactory
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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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geojson_file_path = input_files_path / 'omhm_selected_buildings.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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ep_output_path = output_path / 'ep_outputs'
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ep_output_path.mkdir(parents=True, exist_ok=True)
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# Create city object from GeoJSON file
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city = GeometryFactory('geojson',
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path=geojson_file_path,
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height_field='Hieght_LiD',
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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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# Enrich city data
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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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ResultFactory('energy_plus_multiple_buildings', city, ep_output_path).enrich()
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for building in city.buildings:
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building.energy_systems_archetype_name = 'system 1 gas'
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EnergySystemsFactory('montreal_custom', city).enrich()
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# for building in city.buildings:
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# building.energy_systems_archetype_name = 'PV+4Pipe+DHW'
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# EnergySystemsFactory('montreal_future', city).enrich()
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# for building in city.buildings:
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# EnergySystemsSimulationFactory('archetype13', building=building, output_path=output_path).enrich()
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month_names = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']
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building_data = {}
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for building in city.buildings:
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building_data[f'building_{building.name}'] = {'id': building.name,
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'total_floor_area':
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building.thermal_zones_from_internal_zones[0].total_floor_area,
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'yearly_heating_consumption_kWh':
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building.heating_consumption[cte.YEAR][0] / 3.6e6,
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'yearly_cooling_consumption_kWh':
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building.cooling_consumption[cte.YEAR][0] / 3.6e6,
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'yearly_dhw_consumption_kWh':
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building.domestic_hot_water_consumption[cte.YEAR][0] / 3.6e6,
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'heating_peak_load_kW': max(
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building.heating_consumption[cte.HOUR]) / 3.6e6,
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'cooling_peak_load_kW': max(
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building.cooling_consumption[cte.HOUR]) / 3.6e6,
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'monthly_heating_consumption_kWh':
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{month_name: building.heating_consumption[cte.MONTH][i] / 3.6e6
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for (i, month_name) in enumerate(month_names)},
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'monthly_cooling_consumption_kWh':
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{month_name: building.cooling_consumption[cte.MONTH][i] / 3.6e6
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for (i, month_name) in enumerate(month_names)},
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'monthly_dhw_consumption_kWh':
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{month_name: building.domestic_hot_water_consumption[cte.MONTH][i] /
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3.6e6 for (i, month_name) in enumerate(month_names)}}
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with open(output_path / "base_case_buildings_data.json", "w") as json_file:
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json.dump(building_data, json_file, indent=4)
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