100 lines
5.7 KiB
Python
100 lines
5.7 KiB
Python
from pathlib import Path
|
|
import subprocess
|
|
from scripts.ep_run_enrich import energy_plus_workflow
|
|
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_retrofit_report import EnergySystemRetrofitReport
|
|
from scripts.geojson_creator import process_geojson
|
|
from scripts import random_assignation
|
|
from hub.imports.energy_systems_factory import EnergySystemsFactory
|
|
from scripts.energy_system_sizing import SystemSizing
|
|
from scripts.solar_angles import CitySolarAngles
|
|
from scripts.pv_sizing_and_simulation import PVSizingSimulation
|
|
from scripts.energy_system_retrofit_results import consumption_data, cost_data
|
|
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, CURRENT_STATUS
|
|
import hub.helpers.constants as cte
|
|
from hub.exports.exports_factory import ExportsFactory
|
|
from scripts.pv_feasibility import pv_feasibility
|
|
|
|
# Specify the GeoJSON file path
|
|
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=0.0001)
|
|
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)
|
|
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()
|
|
pv_feasibility(-73.5681295982132, 45.49218262677643, 0.0001, selected_buildings=city.buildings)
|
|
energy_plus_workflow(city, energy_plus_output_path)
|
|
solar_angles = CitySolarAngles(city.name,
|
|
city.latitude,
|
|
city.longitude,
|
|
tilt_angle=45,
|
|
surface_azimuth_angle=180).calculate
|
|
random_assignation.call_random(city.buildings, random_assignation.residential_systems_percentage)
|
|
EnergySystemsFactory('montreal_custom', city).enrich()
|
|
SystemSizing(city.buildings).montreal_custom()
|
|
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()
|
|
for building in city.buildings:
|
|
if 'PV' in building.energy_systems_archetype_name:
|
|
ghi = [x / cte.WATTS_HOUR_TO_JULES for x in building.roofs[0].global_irradiance[cte.HOUR]]
|
|
pv_sizing_simulation = PVSizingSimulation(building,
|
|
solar_angles,
|
|
tilt_angle=45,
|
|
module_height=1,
|
|
module_width=2,
|
|
ghi=ghi)
|
|
pv_sizing_simulation.pv_output()
|
|
if building.energy_systems_archetype_name == 'PV+4Pipe+DHW':
|
|
EnergySystemsSimulationFactory('archetype13', building=building, output_path=simulation_results_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()
|
|
|
|
|