diff --git a/energy_system_modelling_package/energy_system_modelling_factories/system_sizing_methods/genetic_algorithm/multi_objective_genetic_algorithm.py b/energy_system_modelling_package/energy_system_modelling_factories/system_sizing_methods/genetic_algorithm/multi_objective_genetic_algorithm.py index e532cce4..3b460294 100644 --- a/energy_system_modelling_package/energy_system_modelling_factories/system_sizing_methods/genetic_algorithm/multi_objective_genetic_algorithm.py +++ b/energy_system_modelling_package/energy_system_modelling_factories/system_sizing_methods/genetic_algorithm/multi_objective_genetic_algorithm.py @@ -38,7 +38,7 @@ class MultiObjectiveGeneticAlgorithm: operators such as crossover and mutation rates. """ - def __init__(self, population_size=50, generations=50, crossover_rate=0.9, mutation_rate=0.33, + def __init__(self, population_size=20, generations=20, crossover_rate=0.9, mutation_rate=0.33, number_of_selected_solutions=None, optimization_scenario=None): self.population_size = population_size self.population = [] @@ -804,9 +804,11 @@ class MultiObjectiveGeneticAlgorithm: storage_type = storage_component['type'] capacity = storage_component['capacity'] volume = storage_component['volume'] + heating_coil = storage_component['heating_coil_capacity'] selected_solutions[solution_type]['Storage Components'].append({'storage type': storage_type, 'capacity (W)': capacity, - 'volume (m3)': volume}) + 'volume (m3)': volume, + 'heating coil capacity (W)': heating_coil}) if 'energy-consumption' in self.optimization_scenario: selected_solutions[solution_type]['total energy consumption kWh'] = individual['total_energy_consumption'] if 'cost' in self.optimization_scenario: diff --git a/simulation_test.py b/simulation_test.py new file mode 100644 index 00000000..1ea9a1da --- /dev/null +++ b/simulation_test.py @@ -0,0 +1,58 @@ +from pathlib import Path +import subprocess +from building_modelling.ep_run_enrich import energy_plus_workflow +from energy_system_modelling_package.energy_system_modelling_factories.montreal_energy_system_archetype_modelling_factory import \ + MontrealEnergySystemArchetypesSimulationFactory +from energy_system_modelling_package.energy_system_modelling_factories.system_sizing_methods.genetic_algorithm.multi_objective_genetic_algorithm import MultiObjectiveGeneticAlgorithm +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 +import hub.helpers.constants as cte +from building_modelling.geojson_creator import process_geojson +from energy_system_modelling_package import random_assignation +from hub.imports.energy_systems_factory import EnergySystemsFactory +from energy_system_modelling_package.energy_system_modelling_factories.energy_system_sizing_factory import \ + EnergySystemsSizingFactory +from energy_system_modelling_package.energy_system_retrofit.energy_system_retrofit_results import consumption_data, \ + cost_data +from costing_package.cost import Cost +from costing_package.constants import * +from hub.exports.exports_factory import ExportsFactory + +# 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=0.00006) +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() +energy_plus_workflow(city, energy_plus_output_path) +random_assignation.call_random(city.buildings, random_assignation.residential_new_systems_percentage) +EnergySystemsFactory('montreal_future', city).enrich() +for building in city.buildings: + design_period_demands = MultiObjectiveGeneticAlgorithm(optimization_scenario='energy-consumption_cost').design_period_identification(city.buildings[0]) + heating_demand = design_period_demands[cte.HEATING]['demands'] diff --git a/test.py b/test.py index 644d3548..73be2f09 100644 --- a/test.py +++ b/test.py @@ -54,5 +54,5 @@ energy_plus_workflow(city, energy_plus_output_path) random_assignation.call_random(city.buildings, random_assignation.residential_new_systems_percentage) EnergySystemsFactory('montreal_future', city).enrich() for building in city.buildings: - energy_system = building.energy_systems[1] + energy_system = building.energy_systems[-1] MultiObjectiveGeneticAlgorithm(optimization_scenario='energy-consumption_cost').solve_ga(building, energy_system)