from pathlib import Path import subprocess from building_modelling.ep_run_enrich import energy_plus_workflow from energy_system_modelling_package.energy_system_modelling_factories.montreal_energy_system_archetype_modelling_factory import \ MontrealEnergySystemArchetypesSimulationFactory from energy_system_modelling_package.energy_system_modelling_factories.pv_assessment.pv_system_assessment import \ PvSystemAssessment from energy_system_modelling_package.energy_system_modelling_factories.pv_assessment.solar_calculator import \ SolarCalculator from hub.imports.geometry_factory import GeometryFactory from hub.helpers.dictionaries import Dictionaries from hub.imports.construction_factory import ConstructionFactory from hub.imports.usage_factory import UsageFactory from hub.imports.weather_factory import WeatherFactory from hub.imports.results_factory import ResultFactory from energy_system_modelling_package.energy_system_retrofit.energy_system_retrofit_report import EnergySystemRetrofitReport from building_modelling.geojson_creator import process_geojson from energy_system_modelling_package import random_assignation from hub.imports.energy_systems_factory import EnergySystemsFactory from energy_system_modelling_package.energy_system_modelling_factories.energy_system_sizing_factory import EnergySystemsSizingFactory from energy_system_modelling_package.energy_system_retrofit.energy_system_retrofit_results import consumption_data, cost_data from costing_package.cost import Cost from costing_package.constants import SYSTEM_RETROFIT_AND_PV, CURRENT_STATUS from hub.exports.exports_factory import ExportsFactory # Specify the GeoJSON file path main_path = Path(__file__).parent.resolve() input_files_path = (Path(__file__).parent / 'input_files') input_files_path.mkdir(parents=True, exist_ok=True) geojson_file = process_geojson(x=-73.5681295982132, y=45.49218262677643, diff=0.00006, path=main_path) geojson_file_path = input_files_path / 'output_buildings.geojson' output_path = (Path(__file__).parent / 'out_files').resolve() output_path.mkdir(parents=True, exist_ok=True) energy_plus_output_path = output_path / 'energy_plus_outputs' energy_plus_output_path.mkdir(parents=True, exist_ok=True) simulation_results_path = (Path(__file__).parent / 'out_files' / 'simulation_results').resolve() simulation_results_path.mkdir(parents=True, exist_ok=True) sra_output_path = output_path / 'sra_outputs' sra_output_path.mkdir(parents=True, exist_ok=True) pv_assessment_path = output_path / 'pv_outputs' pv_assessment_path.mkdir(parents=True, exist_ok=True) cost_analysis_output_path = output_path / 'cost_analysis' cost_analysis_output_path.mkdir(parents=True, exist_ok=True) city = GeometryFactory(file_type='geojson', path=geojson_file_path, height_field='height', year_of_construction_field='year_of_construction', function_field='function', function_to_hub=Dictionaries().montreal_function_to_hub_function).city ConstructionFactory('nrcan', city).enrich() UsageFactory('nrcan', city).enrich() WeatherFactory('epw', city).enrich() ExportsFactory('sra', city, sra_output_path).export() sra_path = (sra_output_path / f'{city.name}_sra.xml').resolve() subprocess.run(['sra', str(sra_path)]) ResultFactory('sra', city, sra_output_path).enrich() energy_plus_workflow(city, energy_plus_output_path) random_assignation.call_random(city.buildings, random_assignation.residential_systems_percentage) EnergySystemsFactory('montreal_custom', city).enrich() EnergySystemsSizingFactory('peak_load_sizing', city).enrich() current_status_energy_consumption = consumption_data(city) current_status_life_cycle_cost = {} for building in city.buildings: cost_retrofit_scenario = CURRENT_STATUS lcc_dataframe = Cost(building=building, retrofit_scenario=cost_retrofit_scenario, fuel_tariffs=['Electricity-D', 'Gas-Energir']).life_cycle lcc_dataframe.to_csv(cost_analysis_output_path / f'{building.name}_current_status_lcc.csv') current_status_life_cycle_cost[f'{building.name}'] = cost_data(building, lcc_dataframe, cost_retrofit_scenario) random_assignation.call_random(city.buildings, random_assignation.residential_new_systems_percentage) EnergySystemsFactory('montreal_future', city).enrich() EnergySystemsSizingFactory('peak_load_sizing', city).enrich() # # Initialize solar calculation parameters (e.g., azimuth, altitude) and compute irradiance and solar angles tilt_angle = 37 solar_parameters = SolarCalculator(city=city, surface_azimuth_angle=180, tilt_angle=tilt_angle, standard_meridian=-75) solar_angles = solar_parameters.solar_angles # Obtain solar angles for further analysis solar_parameters.tilted_irradiance_calculator() # Calculate the solar radiation on a tilted surface for building in city.buildings: MontrealEnergySystemArchetypesSimulationFactory(f'archetype_cluster_{building.energy_systems_archetype_cluster_id}', building, simulation_results_path).enrich() if 'PV' in building.energy_systems_archetype_name: PvSystemAssessment(building=building, pv_system=None, battery=None, electricity_demand=None, tilt_angle=tilt_angle, solar_angles=solar_angles, pv_installation_type='rooftop', simulation_model_type='explicit', module_model_name=None, inverter_efficiency=0.95, system_catalogue_handler=None, roof_percentage_coverage=0.75, facade_coverage_percentage=0, csv_output=False, output_path=pv_assessment_path).enrich() retrofitted_energy_consumption = consumption_data(city) retrofitted_life_cycle_cost = {} for building in city.buildings: cost_retrofit_scenario = SYSTEM_RETROFIT_AND_PV lcc_dataframe = Cost(building=building, retrofit_scenario=cost_retrofit_scenario, fuel_tariffs=['Electricity-D', 'Gas-Energir']).life_cycle lcc_dataframe.to_csv(cost_analysis_output_path / f'{building.name}_retrofitted_lcc.csv') retrofitted_life_cycle_cost[f'{building.name}'] = cost_data(building, lcc_dataframe, cost_retrofit_scenario) EnergySystemRetrofitReport(city, output_path, 'PV Implementation and System Retrofit', current_status_energy_consumption, retrofitted_energy_consumption, current_status_life_cycle_cost, retrofitted_life_cycle_cost).create_report()