adjusting to changes in hub
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9f8642d0b5
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13
main.py
13
main.py
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@ -13,9 +13,8 @@ from sra_engine import SraEngine
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try:
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file_path = (Path(__file__).parent / 'data' / 'selected_building.geojson')
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file_path = (Path(__file__).parent / 'input_files' / 'selected_building_warehouse.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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@ -23,7 +22,7 @@ try:
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attic_heated_case = 0
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basement_heated_case = 1
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out_path = (Path(__file__).parent / 'outputs')
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out_path = (Path(__file__).parent / 'output_files')
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tmp_folder = (Path(__file__).parent / 'tmp')
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print('[simulation start]')
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@ -36,7 +35,7 @@ try:
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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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WeatherFactory(weather_format, city).enrich()
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print('enrich weather... done')
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ConstructionFactory(construction_format, city).enrich()
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print('enrich constructions... done')
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@ -49,7 +48,7 @@ try:
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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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SraEngine(city, sra_file, tmp_folder)
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print(' sra processed...')
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MonthlyEnergyBalanceEngine(city, tmp_folder)
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@ -58,9 +57,9 @@ try:
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for building in city.buildings:
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for energy_system in building.energy_systems:
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if cte.HEATING in energy_system.demand_types:
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energy_system.generation_system.heat_power = building.heating_peak_load[cte.YEAR][cte.HEATING_PEAK_LOAD][0]
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energy_system.generation_system.heat_power = building.heating_peak_load[cte.YEAR][0]
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if cte.COOLING in energy_system.demand_types:
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energy_system.generation_system.cooling_power = building.cooling_peak_load[cte.YEAR][cte.COOLING_PEAK_LOAD][0]
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energy_system.generation_system.cooling_power = building.cooling_peak_load[cte.YEAR][0]
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print('importing results:')
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results = Results(city, out_path)
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23
results.py
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results.py
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@ -13,12 +13,12 @@ class Results:
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file = 'city name: ' + self._city.name + '\n'
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array = [None] * 12
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for building in self._city.buildings:
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if cte.MONTH in building.heating.keys():
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heating_results = building.heating[cte.MONTH].rename(columns={cte.INSEL_MEB: f'{building.name} heating Wh'})
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if cte.MONTH in building.heating_demand.keys():
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heating_results = building.heating_demand[cte.MONTH].rename(columns={cte.INSEL_MEB: f'{building.name} heating Wh'})
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else:
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heating_results = pd.DataFrame(array, columns=[f'{building.name} heating demand Wh'])
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if cte.MONTH in building.cooling.keys():
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cooling_results = building.cooling[cte.MONTH].rename(columns={cte.INSEL_MEB: f'{building.name} cooling Wh'})
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if cte.MONTH in building.cooling_demand.keys():
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cooling_results = building.cooling_demand[cte.MONTH].rename(columns={cte.INSEL_MEB: f'{building.name} cooling Wh'})
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else:
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cooling_results = pd.DataFrame(array, columns=[f'{building.name} cooling demand Wh'])
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if cte.MONTH in building.lighting_electrical_demand.keys():
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@ -54,11 +54,13 @@ class Results:
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dhw_consumption_results = pd.DataFrame(array, columns=[f'{building.name} domestic hot water consumption Wh'])
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if cte.MONTH in building.heating_peak_load.keys():
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heating_peak_load_results = building.heating_peak_load[cte.MONTH]
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heating_peak_load_results = pd.DataFrame(building.heating_peak_load[cte.MONTH],
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columns=[f'{building.name} heating peak load W'])
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else:
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heating_peak_load_results = pd.DataFrame(array, columns=[f'{building.name} heating peak load W'])
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if cte.MONTH in building.cooling_peak_load.keys():
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cooling_peak_load_results = building.cooling_peak_load[cte.MONTH]
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cooling_peak_load_results = pd.DataFrame(building.cooling_peak_load[cte.MONTH],
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columns=[f'{building.name} cooling peak load W'])
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else:
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cooling_peak_load_results = pd.DataFrame(array, columns=[f'{building.name} cooling peak load W'])
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@ -92,12 +94,11 @@ class Results:
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if value * appliances.density * thermal_zone.total_floor_area > peak_appliances:
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peak_appliances = value * appliances.density * thermal_zone.total_floor_area
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#todo:check with Pilar. Peak cannot be multiplied by 12. I deleted it. Is el. peak not saved in building?
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monthly_electricity_peak = [0.9 * peak_lighting + 0.7 * peak_appliances]
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monthly_electricity_peak = [0.9 * peak_lighting + 0.7 * peak_appliances] * 12
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conditioning_peak = []
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for i, value in enumerate(building.heating_peak_load[cte.MONTH][cte.HEATING_PEAK_LOAD]):
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if cooling * building.cooling_peak_load[cte.MONTH][cte.COOLING_PEAK_LOAD][i] > heating * value:
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conditioning_peak.append(cooling * building.cooling_peak_load[cte.MONTH][cte.COOLING_PEAK_LOAD][i])
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for i, value in enumerate(building.heating_peak_load[cte.MONTH]):
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if cooling * building.cooling_peak_load[cte.MONTH][i] > heating * value:
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conditioning_peak.append(cooling * building.cooling_peak_load[cte.MONTH][i])
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else:
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conditioning_peak.append(heating * value)
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monthly_electricity_peak[i] += 0.8 * conditioning_peak[i]
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@ -7,7 +7,7 @@ from hub.imports.results_factory import ResultFactory
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class SraEngine:
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def __init__(self, city, file_path, output_file_path, weather_file):
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def __init__(self, city, file_path, output_file_path):
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"""
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SRA class
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:param file_path: _sra.xml file path
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@ -16,12 +16,11 @@ class SraEngine:
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self._city = city
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self._file_path = file_path
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self._output_file_path = output_file_path
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self._weather_file = weather_file
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if platform.system() == 'Linux':
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self._executable = 'sra'
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elif platform.system() == 'Windows':
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self._executable = 'shortwave_integer'
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ExportsFactory('sra', self._city, output_file_path, weather_file=self._weather_file, weather_format='epw').export()
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ExportsFactory('sra', self._city, output_file_path).export()
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self._run()
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ResultFactory('sra', self._city, output_file_path).enrich()
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