From 537809f3c84d42261f7332d98786606e79db8080 Mon Sep 17 00:00:00 2001 From: p_monsalvete Date: Wed, 7 Jun 2023 14:48:21 -0400 Subject: [PATCH] adjusting to changes in hub --- main.py | 13 ++++++------- results.py | 23 ++++++++++++----------- sra_engine.py | 5 ++--- 3 files changed, 20 insertions(+), 21 deletions(-) diff --git a/main.py b/main.py index be308e2..32fbc0b 100644 --- a/main.py +++ b/main.py @@ -13,9 +13,8 @@ from sra_engine import SraEngine try: - file_path = (Path(__file__).parent / 'data' / 'selected_building.geojson') + file_path = (Path(__file__).parent / 'input_files' / 'selected_building_warehouse.geojson') climate_reference_city = 'Montreal' - weather_file = 'CAN_PQ_Montreal.Intl.AP.716270_CWEC.epw' weather_format = 'epw' construction_format = 'nrcan' usage_format = 'nrcan' @@ -23,7 +22,7 @@ try: attic_heated_case = 0 basement_heated_case = 1 - out_path = (Path(__file__).parent / 'outputs') + out_path = (Path(__file__).parent / 'output_files') tmp_folder = (Path(__file__).parent / 'tmp') print('[simulation start]') @@ -36,7 +35,7 @@ try: city.climate_reference_city = climate_reference_city city.climate_file = (tmp_folder / f'{climate_reference_city}.cli').resolve() print(f'city created from {file_path}') - WeatherFactory(weather_format, city, file_name=weather_file).enrich() + WeatherFactory(weather_format, city).enrich() print('enrich weather... done') ConstructionFactory(construction_format, city).enrich() print('enrich constructions... done') @@ -49,7 +48,7 @@ try: print('exporting:') sra_file = (tmp_folder / f'{city.name}_sra.xml').resolve() - SraEngine(city, sra_file, tmp_folder, weather_file) + SraEngine(city, sra_file, tmp_folder) print(' sra processed...') MonthlyEnergyBalanceEngine(city, tmp_folder) @@ -58,9 +57,9 @@ try: for building in city.buildings: for energy_system in building.energy_systems: if cte.HEATING in energy_system.demand_types: - energy_system.generation_system.heat_power = building.heating_peak_load[cte.YEAR][cte.HEATING_PEAK_LOAD][0] + energy_system.generation_system.heat_power = building.heating_peak_load[cte.YEAR][0] if cte.COOLING in energy_system.demand_types: - energy_system.generation_system.cooling_power = building.cooling_peak_load[cte.YEAR][cte.COOLING_PEAK_LOAD][0] + energy_system.generation_system.cooling_power = building.cooling_peak_load[cte.YEAR][0] print('importing results:') results = Results(city, out_path) diff --git a/results.py b/results.py index 41c2300..af3eaf7 100644 --- a/results.py +++ b/results.py @@ -13,12 +13,12 @@ class Results: file = 'city name: ' + self._city.name + '\n' array = [None] * 12 for building in self._city.buildings: - if cte.MONTH in building.heating.keys(): - heating_results = building.heating[cte.MONTH].rename(columns={cte.INSEL_MEB: f'{building.name} heating Wh'}) + if cte.MONTH in building.heating_demand.keys(): + heating_results = building.heating_demand[cte.MONTH].rename(columns={cte.INSEL_MEB: f'{building.name} heating Wh'}) else: heating_results = pd.DataFrame(array, columns=[f'{building.name} heating demand Wh']) - if cte.MONTH in building.cooling.keys(): - cooling_results = building.cooling[cte.MONTH].rename(columns={cte.INSEL_MEB: f'{building.name} cooling Wh'}) + if cte.MONTH in building.cooling_demand.keys(): + cooling_results = building.cooling_demand[cte.MONTH].rename(columns={cte.INSEL_MEB: f'{building.name} cooling Wh'}) else: cooling_results = pd.DataFrame(array, columns=[f'{building.name} cooling demand Wh']) if cte.MONTH in building.lighting_electrical_demand.keys(): @@ -54,11 +54,13 @@ class Results: dhw_consumption_results = pd.DataFrame(array, columns=[f'{building.name} domestic hot water consumption Wh']) if cte.MONTH in building.heating_peak_load.keys(): - heating_peak_load_results = building.heating_peak_load[cte.MONTH] + heating_peak_load_results = pd.DataFrame(building.heating_peak_load[cte.MONTH], + columns=[f'{building.name} heating peak load W']) else: heating_peak_load_results = pd.DataFrame(array, columns=[f'{building.name} heating peak load W']) if cte.MONTH in building.cooling_peak_load.keys(): - cooling_peak_load_results = building.cooling_peak_load[cte.MONTH] + cooling_peak_load_results = pd.DataFrame(building.cooling_peak_load[cte.MONTH], + columns=[f'{building.name} cooling peak load W']) else: cooling_peak_load_results = pd.DataFrame(array, columns=[f'{building.name} cooling peak load W']) @@ -92,12 +94,11 @@ class Results: if value * appliances.density * thermal_zone.total_floor_area > peak_appliances: peak_appliances = value * appliances.density * thermal_zone.total_floor_area - #todo:check with Pilar. Peak cannot be multiplied by 12. I deleted it. Is el. peak not saved in building? - monthly_electricity_peak = [0.9 * peak_lighting + 0.7 * peak_appliances] + monthly_electricity_peak = [0.9 * peak_lighting + 0.7 * peak_appliances] * 12 conditioning_peak = [] - for i, value in enumerate(building.heating_peak_load[cte.MONTH][cte.HEATING_PEAK_LOAD]): - if cooling * building.cooling_peak_load[cte.MONTH][cte.COOLING_PEAK_LOAD][i] > heating * value: - conditioning_peak.append(cooling * building.cooling_peak_load[cte.MONTH][cte.COOLING_PEAK_LOAD][i]) + for i, value in enumerate(building.heating_peak_load[cte.MONTH]): + if cooling * building.cooling_peak_load[cte.MONTH][i] > heating * value: + conditioning_peak.append(cooling * building.cooling_peak_load[cte.MONTH][i]) else: conditioning_peak.append(heating * value) monthly_electricity_peak[i] += 0.8 * conditioning_peak[i] diff --git a/sra_engine.py b/sra_engine.py index e8618f8..dc08498 100644 --- a/sra_engine.py +++ b/sra_engine.py @@ -7,7 +7,7 @@ from hub.imports.results_factory import ResultFactory class SraEngine: - def __init__(self, city, file_path, output_file_path, weather_file): + def __init__(self, city, file_path, output_file_path): """ SRA class :param file_path: _sra.xml file path @@ -16,12 +16,11 @@ class SraEngine: self._city = city self._file_path = file_path self._output_file_path = output_file_path - self._weather_file = weather_file if platform.system() == 'Linux': self._executable = 'sra' elif platform.system() == 'Windows': self._executable = 'shortwave_integer' - ExportsFactory('sra', self._city, output_file_path, weather_file=self._weather_file, weather_format='epw').export() + ExportsFactory('sra', self._city, output_file_path).export() self._run() ResultFactory('sra', self._city, output_file_path).enrich()