diff --git a/energy_system_modelling_package/random_assignation.py b/energy_system_modelling_package/random_assignation.py
index 16cb7745..196ead15 100644
--- a/energy_system_modelling_package/random_assignation.py
+++ b/energy_system_modelling_package/random_assignation.py
@@ -29,7 +29,7 @@ residential_systems_percentage = {'system 1 gas': 15,
'system 8 electricity': 35}
residential_new_systems_percentage = {
- 'Central Hydronic Air and Gas Source Heating System with Unitary Split Cooling and Air Source HP DHW and Grid Tied PV': 100,
+ 'Central Hydronic Air and Gas Source Heating System with Unitary Split Cooling and Air Source HP DHW and Grid Tied PV': 0,
'Central Hydronic Air and Electricity Source Heating System with Unitary Split Cooling and Air Source HP DHW and Grid Tied PV': 0,
'Central Hydronic Ground and Gas Source Heating System with Unitary Split Cooling and Air Source HP DHW and Grid Tied PV': 0,
'Central Hydronic Ground and Electricity Source Heating System with Unitary Split Cooling and Air Source HP DHW '
@@ -43,7 +43,7 @@ residential_new_systems_percentage = {
'Central Hydronic Ground and Electricity Source Heating System with Unitary Split and Air Source HP DHW': 0,
'Central Hydronic Water and Gas Source Heating System with Unitary Split and Air Source HP DHW': 0,
'Central Hydronic Water and Electricity Source Heating System with Unitary Split and Air Source HP DHW': 0,
- 'Grid Tied PV System': 0,
+ 'Grid Tied PV System': 100,
'system 1 gas': 0,
'system 1 gas grid tied pv': 0,
'system 1 electricity': 0,
@@ -70,12 +70,12 @@ non_residential_systems_percentage = {'system 1 gas': 0,
'system 1 electricity': 0,
'system 2 gas': 0,
'system 2 electricity': 0,
- 'system 3 and 4 gas': 39,
- 'system 3 and 4 electricity': 36,
+ 'system 3 and 4 gas': 50,
+ 'system 3 and 4 electricity': 0,
'system 5 gas': 0,
'system 5 electricity': 0,
- 'system 6 gas': 13,
- 'system 6 electricity': 12,
+ 'system 6 gas': 50,
+ 'system 6 electricity': 0,
'system 8 gas': 0,
'system 8 electricity': 0}
diff --git a/hub/data/energy_systems/montreal_future_systems.xml b/hub/data/energy_systems/montreal_future_systems.xml
index 12f5130e..60613716 100644
--- a/hub/data/energy_systems/montreal_future_systems.xml
+++ b/hub/data/energy_systems/montreal_future_systems.xml
@@ -449,19 +449,19 @@
12
Photovoltaic Module
photovoltaic
- 445MS
+ CS7N650MS
Canadian Solar
- 332
- 0.201
+ 487
+ 0.209
20
- 40
+ 41
800
25
1000
- 445
+ 650
0.35
- 2.01
- 1.048
+ 2.4
+ 1.3
diff --git a/hub/imports/usage/comnet_usage_parameters.py b/hub/imports/usage/comnet_usage_parameters.py
index 08d8175c..b930d346 100644
--- a/hub/imports/usage/comnet_usage_parameters.py
+++ b/hub/imports/usage/comnet_usage_parameters.py
@@ -39,7 +39,11 @@ class ComnetUsageParameters:
comnet_archetype_usages = []
building_functions = building.function.split('_')
for function in building_functions:
- usages.append(function.split('-'))
+ try:
+ float(function.split('-')[0])
+ usages.append(function.split('-', maxsplit=1))
+ except ValueError:
+ usages.append([function])
for usage in usages:
comnet_usage_name = Dictionaries().hub_usage_to_comnet_usage[usage[-1]]
try:
diff --git a/hub/imports/usage/nrcan_usage_parameters.py b/hub/imports/usage/nrcan_usage_parameters.py
index 4ff99a29..2e10e654 100644
--- a/hub/imports/usage/nrcan_usage_parameters.py
+++ b/hub/imports/usage/nrcan_usage_parameters.py
@@ -39,7 +39,11 @@ class NrcanUsageParameters:
comnet_archetype_usages = []
building_functions = building.function.split('_')
for function in building_functions:
- usages.append(function.split('-'))
+ try:
+ float(function.split('-')[0])
+ usages.append(function.split('-', maxsplit=1))
+ except ValueError:
+ usages.append([function])
for usage in usages:
usage_name = Dictionaries().hub_usage_to_nrcan_usage[usage[-1]]
try:
diff --git a/input_files/1.geojson b/input_files/1.geojson
new file mode 100644
index 00000000..58109d30
--- /dev/null
+++ b/input_files/1.geojson
@@ -0,0 +1,715 @@
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+}
\ No newline at end of file
diff --git a/input_files/2.geojson b/input_files/2.geojson
new file mode 100644
index 00000000..77bc11be
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[-73.62381459005861, 45.529561746216324], [-73.62379778991384, 45.529594146931544], [-73.6237978897737, 45.529594146823314], [-73.62396899141011, 45.52964674581957], [-73.62398899105872, 45.529614445987995], [-73.62412409067701, 45.52965594651627]]]}}, {"type": "Feature", "properties": {"name": "03078303", "address": "rue Hutchison (MTL+OUT) 7300", "function": 9510, "height": 9, "year_of_construction": 1950, "id": 123929}, "geometry": {"type": "Polygon", "coordinates": [[[-73.624056068251, 45.529774883742355], [-73.62396269703619, 45.529933785089675], [-73.624466791505, 45.530080746635406], [-73.62455917130055, 45.529925054786936], [-73.624056068251, 45.529774883742355]]]}}, {"type": "Feature", "properties": {"name": "03081995", "address": "avenue Ogilvy (MTL) 444", "function": 1000, "height": 10, "year_of_construction": 1955, "id": 128445}, "geometry": {"type": "Polygon", "coordinates": [[[-73.62452499092255, 45.529748746108915], [-73.62448097226299, 45.52975016004159], [-73.6246354856489, 45.52979534974257], [-73.62471119047582, 45.529668646272796], [-73.62470479138236, 45.52966674649997], [-73.62445938853517, 45.52959235809751], [-73.62445536849485, 45.52959118278851], [-73.6243847903687, 45.52970614660761], [-73.62452499092255, 45.529748746108915]], [[-73.62452499092255, 45.529748746108915], [-73.6245255898649, 45.52974864647372], [-73.62452549044556, 45.52974884634636], [-73.62452499092255, 45.529748746108915]]]}}]}
\ No newline at end of file
diff --git a/main.py b/main.py
index e69de29b..dc392b81 100644
--- a/main.py
+++ b/main.py
@@ -0,0 +1,132 @@
+from pathlib import Path
+import pandas as pd
+from building_modelling.ep_run_enrich import energy_plus_workflow
+from hub.helpers.dictionaries import Dictionaries
+from hub.imports.construction_factory import ConstructionFactory
+from hub.imports.energy_systems_factory import EnergySystemsFactory
+from hub.imports.geometry_factory import GeometryFactory
+from hub.imports.usage_factory import UsageFactory
+from hub.imports.weather_factory import WeatherFactory
+from energy_system_modelling_package import random_assignation
+from energy_system_modelling_package.energy_system_modelling_factories.pv_assessment.electricity_demand_calculator import HourlyElectricityDemand
+import hub.helpers.constants as cte
+import json
+base_path = Path(__file__).parent.resolve()
+input_files_path = base_path / 'input_files'
+input_files_path.mkdir(parents=True, exist_ok=True)
+output_files_path = base_path / 'out_files'
+output_files_path.mkdir(exist_ok=True, parents=True)
+energy_plus_output_path = output_files_path / 'energy_plus_outputs'
+energy_plus_output_path.mkdir(parents=True, exist_ok=True)
+geojson_path = input_files_path / 'selected_buildings.geojson'
+city = GeometryFactory(file_type='geojson',
+ path=geojson_path,
+ aliases_field=['address'],
+ height_field='height',
+ year_of_construction_field='year_of_construction',
+ function_field='function',
+ function_to_hub=Dictionaries().montreal_function_to_hub_function).city
+for building in city.buildings:
+ if Dictionaries().hub_function_to_nrcan_construction_function[building.function] == 'n/a':
+ building.function = cte.WAREHOUSE
+ConstructionFactory('nrcan', city).enrich()
+UsageFactory('nrcan', city).enrich()
+WeatherFactory('epw', city).enrich()
+residential_buildings = []
+non_residential_buildings = []
+for building in city.buildings:
+ if building.function == cte.RESIDENTIAL:
+ residential_buildings.append(building)
+ else:
+ non_residential_buildings.append(building)
+# random_assignation.call_random(residential_buildings, random_assignation.residential_systems_percentage)
+# random_assignation.call_random(non_residential_buildings, random_assignation.non_residential_systems_percentage)
+# EnergySystemsFactory('montreal_future', city).enrich()
+base_results = pd.read_csv(output_files_path / 'results_summary.csv')
+energy_system_archetypes = base_results['energy_system_archetype_name'].to_list()
+for (i, building) in enumerate(city.buildings):
+ building.energy_systems_archetype_name = energy_system_archetypes[i]
+EnergySystemsFactory('montreal_future', city).enrich()
+energy_plus_workflow(city, energy_plus_output_path)
+# hourly_simulation_results = {}
+# hourly_elec_consumption = pd.DataFrame()
+# hourly_lighting_appliance_consumption = pd.DataFrame()
+# for building in city.buildings:
+# hourly_electricity_consumption = HourlyElectricityDemand(building).calculate()
+# heating_electricity_consumption = building.heating_consumption[
+# cte.HOUR] if 'electricity' in building.energy_systems_archetype_name else [0] * len(
+# building.heating_demand[cte.HOUR])
+# dhw_electricity_consumption = building.domestic_hot_water_consumption[
+# cte.HOUR] if 'electricity' in building.energy_systems_archetype_name else [0] * len(
+# building.domestic_hot_water_heat_demand[cte.HOUR])
+# if building.cooling_consumption[cte.YEAR][0] == 0:
+# cooling_electricity_consumption = [building.cooling_demand[cte.HOUR][i] / (2 * 3.23) for i in
+# range(len(building.cooling_consumption[cte.HOUR]))]
+# hourly_electricity_consumption = [hourly_electricity_consumption[i] + cooling_electricity_consumption[i] for i in range(len(hourly_electricity_consumption))]
+# else:
+# cooling_electricity_consumption = building.cooling_consumption[cte.HOUR]
+# lighting = building.lighting_electrical_demand[cte.HOUR]
+# appliance = building.appliances_electrical_demand[cte.HOUR]
+#
+# results = pd.DataFrame()
+# results['heating_electricity_consumption_kWh'] = [x / (cte.WATTS_HOUR_TO_JULES * 1000) for x in
+# heating_electricity_consumption]
+# results['cooling_electricity_consumption_kWh'] = [x / (cte.WATTS_HOUR_TO_JULES * 1000) for x in
+# cooling_electricity_consumption]
+# results['dhw_electricity_consumption_kWh'] = [x / (cte.WATTS_HOUR_TO_JULES * 1000) for x in
+# dhw_electricity_consumption]
+# results['lighting_kWh'] = [x / (cte.WATTS_HOUR_TO_JULES * 1000) for x in lighting]
+#
+# results['appliance_kWh'] = [x / (cte.WATTS_HOUR_TO_JULES * 1000) for x in appliance]
+# results['lighting_appliance_total_kWh'] = [(lighting[i] + appliance[i]) / (cte.WATTS_HOUR_TO_JULES * 1000)
+# for i in range(len(lighting))]
+# results['total_electricity_consumption_kWh'] = [x / (cte.WATTS_HOUR_TO_JULES * 1000) for x in hourly_electricity_consumption]
+# results.to_csv(output_files_path / 'paper_results' / 'individual_building_simulation_results' / f'{building.name}.csv')
+# hourly_elec_consumption[f'{building.name}'] = [x / (cte.WATTS_HOUR_TO_JULES * 1000) for x in hourly_electricity_consumption]
+# hourly_lighting_appliance_consumption[f'{building.name}'] = [(lighting[i] + appliance[i]) / (cte.WATTS_HOUR_TO_JULES * 1000)
+# for i in range(len(lighting))]
+#
+# hourly_elec_consumption.to_csv(output_files_path / 'paper_results' / 'total_hourly_electricity_consumption.csv')
+# hourly_lighting_appliance_consumption.to_csv(output_files_path / 'paper_results' / 'total_lighting_appliance.csv')
+building_names = [building.name for building in city.buildings]
+building_addresses = [building.aliases[0] for building in city.buildings]
+building_heights = [building.max_height for building in city.buildings]
+buildings_total_floor_areas = [building.thermal_zones_from_internal_zones[0].total_floor_area
+ for building in city.buildings]
+buildings_roof_areas = [building.roofs[0].perimeter_area for building in city.buildings]
+building_energy_system_archetype_names = [building.energy_systems_archetype_name for building in city.buildings]
+building_yearly_heating_electricity_consumptions = []
+building_yearly_dhw_electricity_consumptions = []
+for building in city.buildings:
+ if 'electricity' in building.energy_systems_archetype_name:
+ building_yearly_heating_electricity_consumptions.append(building.heating_consumption[cte.YEAR][0] /
+ (cte.WATTS_HOUR_TO_JULES * 1000))
+ building_yearly_dhw_electricity_consumptions.append(building.domestic_hot_water_consumption[cte.YEAR][0] /
+ (cte.WATTS_HOUR_TO_JULES * 1000))
+ else:
+ building_yearly_heating_electricity_consumptions.append(0)
+ building_yearly_dhw_electricity_consumptions.append(0)
+
+building_yearly_cooling_consumptions = []
+for building in city.buildings:
+ if building.cooling_consumption[cte.YEAR][0] == 0:
+ building_yearly_cooling_consumptions.append(building.cooling_demand[cte.YEAR][0] / (2 * 3.23 * cte.WATTS_HOUR_TO_JULES * 1000))
+ else:
+ building_yearly_cooling_consumptions.append(building.cooling_consumption[cte.YEAR][0] / (cte.WATTS_HOUR_TO_JULES * 1000))
+building_yearly_lighting_demands = [building.lighting_electrical_demand[cte.YEAR][0] / (cte.WATTS_HOUR_TO_JULES * 1000)
+ for building in city.buildings]
+building_yearly_appliance_demands = [building.appliances_electrical_demand[cte.YEAR][0] / (cte.WATTS_HOUR_TO_JULES * 1000)
+ for building in city.buildings]
+summary = pd.DataFrame()
+summary['building_name'] = building_names
+summary['building_address'] = building_addresses
+summary['building_height_m'] = building_heights
+summary['total_floor_area_m2'] = buildings_total_floor_areas
+summary['roof_area_m2'] = buildings_roof_areas
+summary['energy_system_archetype_name'] = building_energy_system_archetype_names
+summary['yearly_heating_electricity_consumption_kWh'] = building_yearly_heating_electricity_consumptions
+summary['yearly_cooling_electricity_consumption_kWh'] = building_yearly_cooling_consumptions
+summary['yearly_dhw_electricity_consumption_kWh'] = building_yearly_dhw_electricity_consumptions
+summary['yearly_lighting_consumption_kWh'] = building_yearly_lighting_demands
+summary['yearly_appliance_consumption_kWh'] = building_yearly_appliance_demands
+summary.to_csv(output_files_path / 'yearly_results.csv', index=False)
diff --git a/pv_athena.py b/pv_athena.py
new file mode 100644
index 00000000..a38fa480
--- /dev/null
+++ b/pv_athena.py
@@ -0,0 +1,98 @@
+from pathlib import Path
+import subprocess
+
+import pandas as pd
+
+from energy_system_modelling_package import random_assignation
+from energy_system_modelling_package.energy_system_modelling_factories.pv_assessment.pv_system_assessment import \
+ PvSystemAssessment
+from energy_system_modelling_package.energy_system_modelling_factories.pv_assessment.solar_calculator import \
+ SolarCalculator
+from hub.imports.energy_systems_factory import EnergySystemsFactory
+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 hub.exports.exports_factory import ExportsFactory
+import hub.helpers.constants as cte
+
+# Define paths for input and output directories, ensuring directories are created if they do not exist
+base_path = Path(__file__).parent.resolve()
+input_files_path = base_path / 'input_files'
+input_files_path.mkdir(parents=True, exist_ok=True)
+output_files_path = base_path / 'out_files'
+output_files_path.mkdir(exist_ok=True, parents=True)
+energy_plus_output_path = output_files_path / 'energy_plus_outputs'
+energy_plus_output_path.mkdir(parents=True, exist_ok=True)
+geojson_path = input_files_path / 'selected_buildings.geojson'
+sra_output_path = output_files_path / 'sra_outputs'
+sra_output_path.mkdir(parents=True, exist_ok=True)
+pv_assessment_path = output_files_path / 'pv_outputs'
+pv_assessment_path.mkdir(parents=True, exist_ok=True)
+# Generate a GeoJSON file for city buildings based on latitude, longitude, and building dimensions
+
+# Initialize a city object from the geojson file, mapping building functions using a predefined dictionary
+city = GeometryFactory(file_type='geojson',
+ path=geojson_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 with construction, usage, and weather information specific to the location
+for building in city.buildings:
+ if Dictionaries().hub_function_to_nrcan_construction_function[building.function] == 'n/a':
+ building.function = cte.WAREHOUSE
+ConstructionFactory('nrcan', city).enrich()
+UsageFactory('nrcan', city).enrich()
+WeatherFactory('epw', city).enrich()
+# Execute the EnergyPlus workflow to simulate building energy performance and generate output
+# energy_plus_workflow(city, energy_plus_output_path)
+# Export the city data in SRA-compatible format to facilitate solar radiation assessment
+ExportsFactory('sra', city, sra_output_path).export()
+# Run SRA simulation using an external command, passing the generated SRA XML file path as input
+sra_path = (sra_output_path / f'{city.name}_sra.xml').resolve()
+subprocess.run(['sra', str(sra_path)])
+# Enrich city data with SRA simulation results for subsequent analysis
+ResultFactory('sra', city, sra_output_path).enrich()
+# Assign PV system archetype name to the buildings in city
+random_assignation.call_random(city.buildings, random_assignation.residential_new_systems_percentage)
+# Enrich city model with Montreal future systems parameters
+EnergySystemsFactory('montreal_future', city).enrich()
+# # Initialize solar calculation parameters (e.g., azimuth, altitude) and compute irradiance and solar angles
+tilt_angle = 37
+solar_parameters = SolarCalculator(city=city,
+ surface_azimuth_angle=180,
+ tilt_angle=tilt_angle,
+ standard_meridian=-75)
+solar_angles = solar_parameters.solar_angles # Obtain solar angles for further analysis
+solar_parameters.tilted_irradiance_calculator() # Calculate the solar radiation on a tilted surface
+# # PV modelling building by building
+# List of available PV modules ['RE400CAA Pure 2', 'RE410CAA Pure 2', 'RE420CAA Pure 2', 'RE430CAA Pure 2',
+# 'REC600AA Pro M', 'REC610AA Pro M', 'REC620AA Pro M', 'REC630AA Pro M', 'REC640AA Pro M']
+building_names = []
+hourly_pv_outputs = pd.DataFrame()
+for building in city.buildings:
+ building_names.append(building.name)
+ pv_modeller = PvSystemAssessment(building=building,
+ pv_system=None,
+ battery=None,
+ tilt_angle=tilt_angle,
+ solar_angles=solar_angles,
+ pv_installation_type='rooftop',
+ simulation_model_type='explicit',
+ module_model_name='CS7N650MS',
+ inverter_efficiency=0.95,
+ system_catalogue_handler='montreal_future',
+ roof_percentage_coverage=0.75,
+ facade_coverage_percentage=0,
+ csv_output=False,
+ output_path=pv_assessment_path)
+ pv_modeller.enrich()
+ results = pv_modeller.results
+ pv_output = [x / 1000 for x in results['total_hourly_pv_system_output_W']]
+ hourly_pv_outputs[f'{building.name}'] = pv_output
+hourly_pv_outputs.to_csv(output_files_path / 'paper_results' / 'hourly_pv_outputs.csv')
+
+
diff --git a/real_map_with_ids.html b/real_map_with_ids.html
new file mode 100644
index 00000000..3bac9ee3
--- /dev/null
+++ b/real_map_with_ids.html
@@ -0,0 +1,198 @@
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\ No newline at end of file