2024-08-08 12:26:49 -04:00
9 changed files with 66 additions and 129 deletions
--- a/energy_system_retrofit.py
+++ b/energy_system_retrofit.py
@ -92,9 +92,8 @@ for building in city.buildings:
                       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)
-for i in range(12):
-  dhw_consumption = 0
-  for building in city.buildings:
-    dhw_consumption += building.domestic_hot_water_consumption[cte.MONTH][i] / 3.6e6
+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()


--- a/input_files/test_geojson.geojson
+++ b/input_files/test_geojson.geojson
@ -1,55 +0,0 @@
-{
-  "type": "FeatureCollection",
-  "features": [
-    {
-      "type": "Feature",
-      "geometry": {
-        "type": "Polygon",
-        "coordinates": [
-          [
-            [
-              -73.58000127109773,
-              45.49613461675315
-            ],
-            [
-              -73.57962787855432,
-              45.496524875557746
-            ],
-            [
-              -73.57996357265695,
-              45.49668114195629
-            ],
-            [
-              -73.57996427397713,
-              45.496680342403664
-            ],
-            [
-              -73.58034707390021,
-              45.49625804233725
-            ],
-            [
-              -73.58034697395713,
-              45.496257942524835
-            ],
-            [
-              -73.58000127109773,
-              45.49613461675315
-            ]
-          ]
-        ]
-      },
-      "id": 179764,
-      "properties": {
-        "name": "01119274",
-        "address": "rue Guy (MTL) 2157",
-        "function": "Mixed use",
-        "mixed_type_1": "commercial",
-        "mixed_type_1_percentage": 50,
-        "mixed_type_2": "6000",
-        "mixed_type_2_percentage": 50,
-        "height": 62,
-        "year_of_construction": 1954
-      }
-    }
-  ]
-}
--- a/input_files/test_geojson1.geojson
+++ b/input_files/test_geojson1.geojson
@ -1,52 +0,0 @@
-{
-  "type": "FeatureCollection",
-  "features": [
-    {
-      "type": "Feature",
-      "geometry": {
-        "type": "Polygon",
-        "coordinates": [
-          [
-            [
-              -73.58000127109773,
-              45.49613461675315
-            ],
-            [
-              -73.57962787855432,
-              45.496524875557746
-            ],
-            [
-              -73.57996357265695,
-              45.49668114195629
-            ],
-            [
-              -73.57996427397713,
-              45.496680342403664
-            ],
-            [
-              -73.58034707390021,
-              45.49625804233725
-            ],
-            [
-              -73.58034697395713,
-              45.496257942524835
-            ],
-            [
-              -73.58000127109773,
-              45.49613461675315
-            ]
-          ]
-        ]
-      },
-      "id": 179764,
-      "properties": {
-        "name": "01119274",
-        "address": "rue Guy (MTL) 2157",
-        "function": "Mixed use",
-        "usages": [{"usage": "commercial", "percentage": 50}, {"usage": "6000", "percentage": 50}],
-        "height": 62,
-        "year_of_construction": 1954
-      }
-    }
-  ]
-}
--- a/main.py
+++ b/main.py
@ -27,8 +27,8 @@ import numpy as np
 data = {}
 input_files_path = (Path(__file__).parent / 'input_files')
 input_files_path.mkdir(parents=True, exist_ok=True)
-# geojson_file = process_geojson(x=-73.58001358793511, y=45.496445294438715, diff=0.0001)
-geojson_file_path = input_files_path / 'test_geojson1.geojson'
+geojson_file = process_geojson(x=-73.58001358793511, y=45.496445294438715, 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'
@ -45,8 +45,8 @@ city = GeometryFactory(file_type='geojson',
                       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()
+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
--- a/scripts/optimization/energy_system_sizing_optimization.py
+++ b/scripts/optimization/energy_system_sizing_optimization.py
@ -0,0 +1,26 @@
+import random
+import numpy as np
+import hub.helpers.constants as cte
+
+class EnergySystemOptimizer:
+  def __init__(self, building, objectives, population_size=20, number_of_generations=100, crossover_rate=0.8,
+               mutation_rate=0.1):
+    self.building = building
+    self.objectives = objectives
+    self.population_size = population_size
+    self.num_gen = number_of_generations
+    self.crossover_rate = crossover_rate
+    self.mutation_rate = mutation_rate
+
+# Initialize population
+  def initialize_population(self):
+    population = []
+    for _ in range(self.population_size):
+      individual = [
+        random.uniform(0.1, 10.0),  # hp_size
+        random.uniform(0.1, 10.0),  # boiler_size
+        random.uniform(0.1, 10.0),  # tes_size
+        random.uniform(40, 60)  # cutoff_temp
+      ]
+      population.append(individual)
+    return population
--- a/scripts/optimization/objectives.py
+++ b/scripts/optimization/objectives.py
@ -0,0 +1,16 @@
+# Objective functions
+MINIMUM_LCC = 1
+MINIMUM_EC = 2
+MINIMUM_EMISSIONS = 3
+MINIMUM_LCC_MINIMUM_EC = 4
+MINIMUM_LCC_MINIMUM_EMISSIONS = 5
+MINIMUM_EC_MINIMUM_EMISSIONS = 6
+MINIMUM_LCC_MINIMUM_EC_MINIMUM_EMISSIONS = 7
+OBJECTIVE_FUNCTIONS = [MINIMUM_LCC,
+                       MINIMUM_EC,
+                       MINIMUM_EMISSIONS,
+                       MINIMUM_LCC_MINIMUM_EC,
+                       MINIMUM_LCC_MINIMUM_EMISSIONS,
+                       MINIMUM_EC_MINIMUM_EMISSIONS,
+                       MINIMUM_LCC_MINIMUM_EC_MINIMUM_EMISSIONS]
+
--- a/scripts/random_assignation.py
+++ b/scripts/random_assignation.py
@ -28,8 +28,8 @@ residential_systems_percentage = {'system 1 gas': 15,
                                  'system 8 gas': 15,
                                  'system 8 electricity': 35}

-residential_new_systems_percentage = {'PV+ASHP+GasBoiler+TES': 100,
-                                      'PV+4Pipe+DHW': 0,
+residential_new_systems_percentage = {'PV+ASHP+GasBoiler+TES': 0,
+                                      'PV+4Pipe+DHW': 100,
                                      'PV+ASHP+ElectricBoiler+TES': 0,
                                      'PV+GSHP+GasBoiler+TES': 0,
                                      'PV+GSHP+ElectricBoiler+TES': 0,
--- a/scripts/system_simulation_models/archetype1.py
+++ b/scripts/system_simulation_models/archetype1.py
@ -16,7 +16,8 @@ class Archetype1:
    self._domestic_hot_water_peak_load = building.domestic_hot_water_peak_load[cte.YEAR][0]
    self._hourly_heating_demand = [0] + [demand / 3600 for demand in building.heating_demand[cte.HOUR]]
    self._hourly_cooling_demand = [demand / 3600 for demand in building.cooling_demand[cte.HOUR]]
-    self._hourly_dhw_demand = building.domestic_hot_water_heat_demand[cte.HOUR]
+    self._hourly_dhw_demand = [demand / cte.WATTS_HOUR_TO_JULES for demand in
+                               building.domestic_hot_water_heat_demand[cte.HOUR]]
    self._output_path = output_path
    self._t_out = [0] + building.external_temperature[cte.HOUR]
    self.results = {}
@ -27,9 +28,9 @@ class Archetype1:
    heat_pump = self._hvac_system.generation_systems[0]
    boiler = self._hvac_system.generation_systems[1]
    thermal_storage = heat_pump.energy_storage_systems[0]
-    heat_pump.nominal_heat_output = round(0.5 * self._heating_peak_load / 3600)
-    heat_pump.nominal_cooling_output = round(self._cooling_peak_load / 3600)
-    boiler.nominal_heat_output = round(0.5 * self._heating_peak_load / 3600)
+    heat_pump.nominal_heat_output = round(0.5 * self._heating_peak_load)
+    heat_pump.nominal_cooling_output = round(self._cooling_peak_load)
+    boiler.nominal_heat_output = round(0.5 * self._heating_peak_load)
    thermal_storage.volume = round(
      (self._heating_peak_load * storage_factor * cte.WATTS_HOUR_TO_JULES) /
      (cte.WATER_HEAT_CAPACITY * cte.WATER_DENSITY * 25))
--- a/scripts/system_simulation_models/archetype13.py
+++ b/scripts/system_simulation_models/archetype13.py
@ -5,7 +5,7 @@ from hub.helpers.monthly_values import MonthlyValues


 class Archetype13:
-  def __init__(self, building, output_path):
+  def __init__(self, building, output_path, csv_output=True,):
    self._building = building
    self._name = building.name
    self._pv_system = building.energy_systems[0]
@ -25,6 +25,7 @@ class Archetype13:
    self._t_out = building.external_temperature[cte.HOUR]
    self.results = {}
    self.dt = 900
+    self.csv_output = csv_output

  def hvac_sizing(self):
    storage_factor = 3
@ -374,10 +375,11 @@ class Archetype13:
      MonthlyValues.get_total_month(self._building.domestic_hot_water_consumption[cte.HOUR]))
    self._building.domestic_hot_water_consumption[cte.YEAR] = [
      sum(self._building.domestic_hot_water_consumption[cte.MONTH])]
-    file_name = f'energy_system_simulation_results_{self._name}.csv'
-    with open(self._output_path / file_name, 'w', newline='') as csvfile:
-      output_file = csv.writer(csvfile)
-      # Write header
-      output_file.writerow(self.results.keys())
-      # Write data
-      output_file.writerows(zip(*self.results.values()))
+    if self.csv_output:
+      file_name = f'energy_system_simulation_results_{self._name}.csv'
+      with open(self._output_path / file_name, 'w', newline='') as csvfile:
+        output_file = csv.writer(csvfile)
+        # Write header
+        output_file.writerow(self.results.keys())
+        # Write data
+        output_file.writerows(zip(*self.results.values()))