from pathlib import Path from scripts.district_heating_network.directory_manager import DirectoryManager 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 import matplotlib.pyplot as plt from scripts.district_heating_network.district_heating_network_creator import DistrictHeatingNetworkCreator from scripts.district_heating_network.road_processor import road_processor base_path = Path(__file__).parent dir_manager = DirectoryManager(base_path) # Input files directory input_files_path = dir_manager.create_directory('input_files') geojson_file_path = input_files_path / 'output_buildings.geojson' # Output files directory output_path = dir_manager.create_directory('out_files') # Subdirectories for output files energy_plus_output_path = dir_manager.create_directory('out_files/energy_plus_outputs') simulation_results_path = dir_manager.create_directory('out_files/simulation_results') sra_output_path = dir_manager.create_directory('out_files/sra_outputs') cost_analysis_output_path = dir_manager.create_directory('out_files/cost_analysis') # Select city area location = [45.53067276979674, -73.70234652694087] process_geojson(x=location[1], y=location[0], diff=0.001) # Create city object 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() # energy_plus_workflow(city, energy_plus_output_path) # data[f'{city.buildings[0].function}'] = city.buildings[0].heating_demand[cte.YEAR][0] / 3.6e9 # city.buildings[0].function = cte.COMMERCIAL # ConstructionFactory('nrcan', city).enrich() # UsageFactory('nrcan', city).enrich() # energy_plus_workflow(city, energy_plus_output_path) # data[f'{city.buildings[0].function}'] = city.buildings[0].heating_demand[cte.YEAR][0] / 3.6e9 # city.buildings[0].function = cte.MEDIUM_OFFICE # ConstructionFactory('nrcan', city).enrich() # UsageFactory('nrcan', city).enrich() # energy_plus_workflow(city, energy_plus_output_path) # data[f'{city.buildings[0].function}'] = city.buildings[0].heating_demand[cte.YEAR][0] / 3.6e9 # categories = list(data.keys()) # values = list(data.values()) # # Plotting # fig, ax = plt.subplots(figsize=(10, 6), dpi=96) # fig.suptitle('Impact of different usages on yearly heating demand', fontsize=16, weight='bold', alpha=.8) # ax.bar(categories, values, color=['#2196f3', '#ff5a5f', '#4caf50'], width=0.6, zorder=2) # ax.grid(which="major", axis='x', color='#DAD8D7', alpha=0.5, zorder=1) # ax.grid(which="major", axis='y', color='#DAD8D7', alpha=0.5, zorder=1) # ax.set_xlabel('Building Type', fontsize=12, labelpad=10) # ax.set_ylabel('Energy Consumption (MWh)', fontsize=14, labelpad=10) # ax.yaxis.set_major_locator(plt.MaxNLocator(integer=True)) # ax.set_xticks(np.arange(len(categories))) # ax.set_xticklabels(categories, rotation=45, ha='right') # ax.bar_label(ax.containers[0], padding=3, color='black', fontsize=12, rotation=0) # ax.spines[['top', 'left', 'bottom']].set_visible(False) # ax.spines['right'].set_linewidth(1.1) # # Set a white background # fig.patch.set_facecolor('white') # # Adjust the margins around the plot area # plt.subplots_adjust(left=0.1, right=0.9, top=0.85, bottom=0.25) # # Save the plot # plt.savefig('plot_nrcan.png', bbox_inches='tight') # plt.close() print('test')