feat: two new codes added to separate energy system retrofit and pv calculations
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energy_system_retrofit.py
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energy_system_retrofit.py
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from scripts.geojson_creator import process_geojson
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from pathlib import Path
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import subprocess
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from scripts.ep_run_enrich import energy_plus_workflow
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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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from hub.imports.results_factory import ResultFactory
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from scripts.energy_system_analysis_report import EnergySystemAnalysisReport
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from scripts import random_assignation
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from hub.imports.energy_systems_factory import EnergySystemsFactory
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from scripts.energy_system_sizing import SystemSizing
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from scripts.energy_system_retrofit_results import system_results, new_system_results
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from scripts.energy_system_sizing_and_simulation_factory import EnergySystemsSimulationFactory
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from scripts.costs.cost import Cost
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from scripts.costs.constants import SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV, SYSTEM_RETROFIT_AND_PV
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import hub.helpers.constants as cte
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from hub.exports.exports_factory import ExportsFactory
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# Specify the GeoJSON file path
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geojson_file = process_geojson(x=-73.5681295982132, y=45.49218262677643, diff=0.0001)
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file_path = (Path(__file__).parent / 'input_files' / 'output_buildings.geojson')
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# Specify the output path for the PDF file
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output_path = (Path(__file__).parent / 'out_files').resolve()
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# Create city object from GeoJSON file
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city = GeometryFactory('geojson',
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path=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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# 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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ExportsFactory('sra', city, output_path).export()
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sra_path = (output_path / f'{city.name}_sra.xml').resolve()
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subprocess.run(['sra', str(sra_path)])
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ResultFactory('sra', city, output_path).enrich()
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energy_plus_workflow(city)
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random_assignation.call_random(city.buildings, random_assignation.residential_systems_percentage)
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EnergySystemsFactory('montreal_custom', city).enrich()
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SystemSizing(city.buildings).montreal_custom()
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current_system = new_system_results(city.buildings)
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random_assignation.call_random(city.buildings, random_assignation.residential_new_systems_percentage)
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EnergySystemsFactory('montreal_future', city).enrich()
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for building in city.buildings:
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EnergySystemsSimulationFactory('archetype1', building=building, output_path=output_path).enrich()
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print(building.energy_consumption_breakdown[cte.ELECTRICITY][cte.COOLING] +
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building.energy_consumption_breakdown[cte.ELECTRICITY][cte.HEATING] +
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building.energy_consumption_breakdown[cte.ELECTRICITY][cte.DOMESTIC_HOT_WATER])
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new_system = new_system_results(city.buildings)
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# EnergySystemAnalysisReport(city, output_path).create_report(current_system, new_system)
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for building in city.buildings:
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costs = Cost(building=building, retrofit_scenario=SYSTEM_RETROFIT_AND_PV).life_cycle
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costs.to_csv(output_path / f'{building.name}_lcc.csv')
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(costs.loc['global_operational_costs', f'Scenario {SYSTEM_RETROFIT_AND_PV}'].
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to_csv(output_path / f'{building.name}_op.csv'))
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costs.loc['global_capital_costs', f'Scenario {SYSTEM_RETROFIT_AND_PV}'].to_csv(
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output_path / f'{building.name}_cc.csv')
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costs.loc['global_maintenance_costs', f'Scenario {SYSTEM_RETROFIT_AND_PV}'].to_csv(
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output_path / f'{building.name}_m.csv')
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62
main.py
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main.py
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@ -1,64 +1,4 @@
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from scripts.geojson_creator import process_geojson
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from pathlib import Path
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import subprocess
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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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from hub.imports.results_factory import ResultFactory
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from scripts.energy_system_analysis_report import EnergySystemAnalysisReport
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from scripts import random_assignation
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from hub.imports.energy_systems_factory import EnergySystemsFactory
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from scripts.energy_system_sizing import SystemSizing
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from scripts.energy_system_retrofit_results import system_results, new_system_results
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from scripts.energy_system_sizing_and_simulation_factory import EnergySystemsSimulationFactory
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from scripts.costs.cost import Cost
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from scripts.costs.constants import SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV, SYSTEM_RETROFIT_AND_PV
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import hub.helpers.constants as cte
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from hub.exports.exports_factory import ExportsFactory
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import csv
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from scripts.solar_angles import CitySolarAngles
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from scripts.radiation_tilted import RadiationTilted
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# Specify the GeoJSON file path
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geojson_file = process_geojson(x=-73.5681295982132, y=45.49218262677643, diff=0.001)
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file_path = (Path(__file__).parent / 'input_files' / 'output_buildings.geojson')
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# Specify the output path for the PDF file
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output_path = (Path(__file__).parent / 'out_files').resolve()
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# Create city object from GeoJSON file
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city = GeometryFactory('geojson',
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path=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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# # 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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energy_plus_workflow(city)
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random_assignation.call_random(city.buildings, random_assignation.residential_systems_percentage)
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EnergySystemsFactory('montreal_custom', city).enrich()
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SystemSizing(city.buildings).montreal_custom()
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current_system = new_system_results(city.buildings)
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random_assignation.call_random(city.buildings, random_assignation.residential_new_systems_percentage)
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EnergySystemsFactory('montreal_future', city).enrich()
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for building in city.buildings:
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EnergySystemsSimulationFactory('archetype1', building=building, output_path=output_path).enrich()
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print(building.energy_consumption_breakdown[cte.ELECTRICITY][cte.COOLING] +
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building.energy_consumption_breakdown[cte.ELECTRICITY][cte.HEATING] +
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building.energy_consumption_breakdown[cte.ELECTRICITY][cte.DOMESTIC_HOT_WATER])
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new_system = new_system_results(city.buildings)
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# EnergySystemAnalysisReport(city, output_path).create_report(current_system, new_system)
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for building in city.buildings:
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costs = Cost(building=building, retrofit_scenario=SYSTEM_RETROFIT_AND_PV).life_cycle
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costs.to_csv(output_path / f'{building.name}_lcc.csv')
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(costs.loc['global_operational_costs', f'Scenario {SYSTEM_RETROFIT_AND_PV}'].
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to_csv(output_path / f'{building.name}_op.csv'))
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costs.loc['global_capital_costs', f'Scenario {SYSTEM_RETROFIT_AND_PV}'].to_csv(
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output_path / f'{building.name}_cc.csv')
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costs.loc['global_maintenance_costs', f'Scenario {SYSTEM_RETROFIT_AND_PV}'].to_csv(
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output_path / f'{building.name}_m.csv')
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39
pv_assessment.py
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39
pv_assessment.py
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from scripts.geojson_creator import process_geojson
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from pathlib import Path
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import subprocess
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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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from hub.imports.results_factory import ResultFactory
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from scripts.solar_angles import CitySolarAngles
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from scripts.radiation_tilted import RadiationTilted
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import hub.helpers.constants as cte
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from hub.exports.exports_factory import ExportsFactory
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# Specify the GeoJSON file path
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geojson_file = process_geojson(x=-73.5681295982132, y=45.49218262677643, diff=0.0001)
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file_path = (Path(__file__).parent / 'input_files' / 'output_buildings.geojson')
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# Specify the output path for the PDF file
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output_path = (Path(__file__).parent / 'out_files').resolve()
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# Create city object from GeoJSON file
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city = GeometryFactory('geojson',
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path=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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# 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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ExportsFactory('sra', city, output_path).export()
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sra_path = (output_path / f'{city.name}_sra.xml').resolve()
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subprocess.run(['sra', str(sra_path)])
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ResultFactory('sra', city, output_path).enrich()
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for building in city.buildings:
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roof_horizontal = [x / cte.WATTS_HOUR_TO_JULES for x in building.roofs[0].global_irradiance[cte.HOUR]]
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solar_angles = (
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CitySolarAngles(city.name, city.latitude, city.longitude, tilt_angle=45, surface_azimuth_angle=180).calculate)
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RadiationTilted(building, solar_angles, tilt_angle=45, ghi=roof_horizontal).enrich()
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@ -95,7 +95,6 @@ class RadiationTilted:
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def enrich(self):
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tilted_radiation = self.total_radiation_tilted
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print(len(tilted_radiation))
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self.building.roofs[0].global_irradiance_tilted[cte.HOUR] = [x * cte.WATTS_HOUR_TO_JULES for x in
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tilted_radiation]
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self.building.roofs[0].global_irradiance_tilted[cte.HOUR] = [x * cte.WATTS_HOUR_TO_JULES for x in
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@ -103,7 +102,7 @@ class RadiationTilted:
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self.building.roofs[0].global_irradiance_tilted[cte.MONTH] = (
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MonthlyValues.get_total_month(self.building.roofs[0].global_irradiance_tilted[cte.HOUR]))
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self.building.roofs[0].global_irradiance_tilted[cte.YEAR] = \
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[sum(self.building.roofs[0].global_irradiance_tilted[cte.MONTH])]
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[sum(self.building.roofs[0].global_irradiance_tilted[cte.MONTH])]
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