84 lines
4.0 KiB
Python
84 lines
4.0 KiB
Python
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
|
|
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
|
|
from scripts.district_heating_network.district_heating_factory import DistrictHeatingFactory
|
|
|
|
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')
|