s_ranjbar
dce5bb8c06
fix: SRA is fixed and finalized feat: A code is written to calculate solar angles and values are validated using PVLIB feat: solar radiation on tilted surface is calculated fix: Required attributes for PV calculations are added to CDM and surface class
67 lines
3.4 KiB
Python
67 lines
3.4 KiB
Python
from scripts.geojson_creator import process_geojson
|
|
from pathlib import Path
|
|
import subprocess
|
|
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 scripts.energy_system_analysis_report import EnergySystemAnalysisReport
|
|
from scripts import random_assignation
|
|
from hub.imports.energy_systems_factory import EnergySystemsFactory
|
|
from scripts.energy_system_sizing import SystemSizing
|
|
from scripts.energy_system_retrofit_results import system_results, new_system_results
|
|
from scripts.energy_system_sizing_and_simulation_factory import EnergySystemsSimulationFactory
|
|
from scripts.costs.cost import Cost
|
|
from scripts.costs.constants import SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV, SYSTEM_RETROFIT_AND_PV
|
|
import hub.helpers.constants as cte
|
|
from hub.exports.exports_factory import ExportsFactory
|
|
import csv
|
|
from scripts.solar_angles import CitySolarAngles
|
|
from scripts.radiation_tilted import RadiationTilted
|
|
# Specify the GeoJSON file path
|
|
geojson_file = process_geojson(x=-73.5681295982132, y=45.49218262677643, diff=0.001)
|
|
file_path = (Path(__file__).parent / 'input_files' / 'output_buildings.geojson')
|
|
# Specify the output path for the PDF file
|
|
output_path = (Path(__file__).parent / 'out_files').resolve()
|
|
# Create city object from GeoJSON file
|
|
city = GeometryFactory('geojson',
|
|
path=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
|
|
# # Enrich city data
|
|
ConstructionFactory('nrcan', city).enrich()
|
|
UsageFactory('nrcan', city).enrich()
|
|
WeatherFactory('epw', city).enrich()
|
|
energy_plus_workflow(city)
|
|
random_assignation.call_random(city.buildings, random_assignation.residential_systems_percentage)
|
|
EnergySystemsFactory('montreal_custom', city).enrich()
|
|
SystemSizing(city.buildings).montreal_custom()
|
|
current_system = new_system_results(city.buildings)
|
|
random_assignation.call_random(city.buildings, random_assignation.residential_new_systems_percentage)
|
|
EnergySystemsFactory('montreal_future', city).enrich()
|
|
for building in city.buildings:
|
|
EnergySystemsSimulationFactory('archetype1', building=building, output_path=output_path).enrich()
|
|
print(building.energy_consumption_breakdown[cte.ELECTRICITY][cte.COOLING] +
|
|
building.energy_consumption_breakdown[cte.ELECTRICITY][cte.HEATING] +
|
|
building.energy_consumption_breakdown[cte.ELECTRICITY][cte.DOMESTIC_HOT_WATER])
|
|
new_system = new_system_results(city.buildings)
|
|
# EnergySystemAnalysisReport(city, output_path).create_report(current_system, new_system)
|
|
for building in city.buildings:
|
|
costs = Cost(building=building, retrofit_scenario=SYSTEM_RETROFIT_AND_PV).life_cycle
|
|
costs.to_csv(output_path / f'{building.name}_lcc.csv')
|
|
(costs.loc['global_operational_costs', f'Scenario {SYSTEM_RETROFIT_AND_PV}'].
|
|
to_csv(output_path / f'{building.name}_op.csv'))
|
|
costs.loc['global_capital_costs', f'Scenario {SYSTEM_RETROFIT_AND_PV}'].to_csv(
|
|
output_path / f'{building.name}_cc.csv')
|
|
costs.loc['global_maintenance_costs', f'Scenario {SYSTEM_RETROFIT_AND_PV}'].to_csv(
|
|
output_path / f'{building.name}_m.csv')
|
|
|
|
|
|
|
|
|
|
|