fix: small bugs in the simulation model resolved

Reviewed-on: https://nextgenerations-cities.encs.concordia.ca/gitea/s_ranjbar/energy_system_modelling_workflow/pulls/10

central.py

@@ -0,0 +1,61 @@
+import pandas as pd
+from scripts.geojson_creator import process_geojson
+from pathlib import Path
+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 import random_assignation
+from hub.imports.energy_systems_factory import EnergySystemsFactory
+from scripts.energy_system_sizing_and_simulation_factory import EnergySystemsSimulationFactory
+from scripts.costs.cost import Cost
+from scripts.costs.constants import SYSTEM_RETROFIT_AND_PV
+from hub.exports.exports_factory import ExportsFactory
+
+# Specify the GeoJSON file path
+location = [45.49034212153445, -73.61435648647083]
+geojson_file = process_geojson(x=location[1], y=location[0], diff=0.0001)
+file_path = (Path(__file__).parent / 'input_files' / 'processed_output -single_building.geojson')
+# Specify the output path for the PDF file
+output_path = (Path(__file__).parent / 'out_files').resolve()
+# Create city object from GeoJSON file
+city = GeometryFactory('geojson',
+                       path=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
+# Enrich city data
+ConstructionFactory('nrcan', city).enrich()
+
+UsageFactory('nrcan', city).enrich()
+WeatherFactory('epw', city).enrich()
+ResultFactory('energy_plus_multiple_buildings', city, output_path).enrich()
+ExportsFactory('sra', city, output_path).export()
+random_assignation.call_random(city.buildings, random_assignation.residential_new_systems_percentage)
+EnergySystemsFactory('montreal_future', city).enrich()
+for building in city.buildings:
+  EnergySystemsSimulationFactory('archetype13', building=building, output_path=output_path).enrich()
+sum_floor_area = 0
+buildings_list = []
+for building in city.buildings:
+  buildings_list.append(building.name)
+df = pd.DataFrame(columns=['building_name', 'total_floor_area', 'investment_cost', 'lc CAPEX'])
+df['building_name'] = buildings_list
+for building in city.buildings:
+  for thermal_zone in building.thermal_zones_from_internal_zones:
+    sum_floor_area += thermal_zone.total_floor_area
+  costs = Cost(building=building, retrofit_scenario=SYSTEM_RETROFIT_AND_PV).life_cycle
+  costs.loc['global_capital_costs', f'Scenario {SYSTEM_RETROFIT_AND_PV}'].to_csv(
+    output_path / f'{building.name}_cc.csv')
+  investment_cost = costs.loc['global_capital_costs',
+                              f'Scenario {SYSTEM_RETROFIT_AND_PV}'].loc[0, 'D3020_heat_and_cooling_generating_systems']
+  lcc_capex = costs.loc['total_capital_costs_systems', f'Scenario {SYSTEM_RETROFIT_AND_PV}']
+  df.loc[df['building_name'] == building.name, 'total_floor_area'] = (
+    building.thermal_zones_from_internal_zones[0].total_floor_area)
+  df.loc[df['building_name'] == building.name, 'investment_cost'] = investment_cost
+  df.loc[df['building_name'] == building.name, 'lc CAPEX'] = lcc_capex
+
+df.to_csv(output_path / 'economic analysis.csv')

hub/city_model_structure/building.py

@@ -484,7 +484,7 @@ class Building(CityObject):
       monthly_values = PeakLoads().peak_loads_from_hourly(self.domestic_hot_water_heat_demand[cte.HOUR])
     if monthly_values is None:
       return None
-    results[cte.MONTH] = [x for x in monthly_values]
+    results[cte.MONTH] = [x / cte.WATTS_HOUR_TO_JULES for x in monthly_values]
     results[cte.YEAR] = [max(monthly_values) / cte.WATTS_HOUR_TO_JULES]
     return results
 

input_files/processed_output -single_building.geojson

@@ -0,0 +1,50 @@
+{
+    "type": "FeatureCollection",
+    "name": "lachine_group_mach_buildings",
+    "crs": {
+        "type": "name",
+        "properties": {
+            "name": "urn:ogc:def:crs:OGC:1.3:CRS84"
+        }
+    },
+    "features": [
+        {
+            "type": "Feature",
+            "properties": {
+                "name": "1",
+                "address": "",
+                "function": 1000,
+                "height": 23.29,
+                "year_of_construction": 2023
+            },
+            "geometry": {
+                "type": "Polygon",
+                "coordinates": [
+                    [
+                        [
+                            -73.66557613653009,
+                            45.43551716511939
+                        ],
+                        [
+                            -73.66530891881455,
+                            45.43551716511939
+                        ],
+                        [
+                            -73.66530891881455,
+                            45.43590129058549
+                        ],
+                        [
+                            -73.66557613653009,
+                            45.43590129058549
+                        ],
+                        [
+                            -73.66557613653009,
+                            45.43551716511939
+                        ]
+                    ]
+                ]
+            },
+            "id": 1
+        }
+    ]
+}

main.py

@@ -0,0 +1,52 @@
+import pandas as pd
+from pathlib import Path
+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 scripts import random_assignation
+from hub.imports.energy_systems_factory import EnergySystemsFactory
+from scripts.energy_system_sizing_and_simulation_factory import EnergySystemsSimulationFactory
+from scripts.costs.cost import Cost
+from scripts.costs.constants import SYSTEM_RETROFIT_AND_PV
+# Specify the GeoJSON file path
+file_path = (Path(__file__).parent / 'input_files' / 'processed_output.geojson')
+output_path = (Path(__file__).parent / 'out_files').resolve()
+city = GeometryFactory('geojson',
+                       path=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)
+random_assignation.call_random(city.buildings, random_assignation.residential_new_systems_percentage)
+EnergySystemsFactory('montreal_future', city).enrich()
+for building in city.buildings:
+  EnergySystemsSimulationFactory('archetype13', building=building, output_path=output_path).enrich()
+sum_floor_area = 0
+buildings_list = []
+for building in city.buildings:
+  buildings_list.append(building.name)
+df = pd.DataFrame(columns=['building_name', 'total_floor_area', 'investment_cost', 'lc CAPEX'])
+df['building_name'] = buildings_list
+for building in city.buildings:
+  for thermal_zone in building.thermal_zones_from_internal_zones:
+    sum_floor_area += thermal_zone.total_floor_area
+  costs = Cost(building=building, retrofit_scenario=SYSTEM_RETROFIT_AND_PV).life_cycle
+  costs.loc['global_capital_costs', f'Scenario {SYSTEM_RETROFIT_AND_PV}'].to_csv(
+    output_path / f'{building.name}_cc.csv')
+  investment_cost = costs.loc['global_capital_costs',
+                              f'Scenario {SYSTEM_RETROFIT_AND_PV}'].loc[0, 'D3020_heat_and_cooling_generating_systems']
+  lcc_capex = costs.loc['total_capital_costs_systems', f'Scenario {SYSTEM_RETROFIT_AND_PV}']
+  df.loc[df['building_name'] == building.name, 'total_floor_area'] = (
+    building.thermal_zones_from_internal_zones[0].total_floor_area)
+  df.loc[df['building_name'] == building.name, 'investment_cost'] = investment_cost
+  df.loc[df['building_name'] == building.name, 'lc CAPEX'] = lcc_capex
+
+df.to_csv(output_path / 'economic analysis.csv')

scripts/costs/capital_costs.py

@@ -155,13 +155,12 @@ class CapitalCosts(CostBase):
     capital_cost_energy_storage_equipment = 0
     capital_cost_distribution_equipment = 0
     capital_cost_lighting = 0
-    capital_cost_pv = self._surface_pv * chapter.item('D2010_photovoltaic_system').initial_investment[0]
+    capital_cost_pv = 0
     for (i, component) in enumerate(system_components):
       if component_categories[i] == 'generation':
         capital_cost_heating_and_cooling_equipment += chapter.item(component).initial_investment[0] * component_sizes[i]
       elif component_categories[i] == 'dhw':
-        capital_cost_domestic_hot_water_equipment += chapter.item(component).initial_investment[0] * \
-                                                      component_sizes[i]
+        capital_cost_domestic_hot_water_equipment += 0
       elif component_categories[i] == 'distribution':
         capital_cost_distribution_equipment += chapter.item(component).initial_investment[0] * \
                                                       component_sizes[i]
@@ -237,7 +236,7 @@ class CapitalCosts(CostBase):
               reposition_cost_heating_and_cooling_equipment = chapter.item(component).reposition[0] * component_sizes[i] * costs_increase
               self._yearly_capital_costs.loc[year, 'D3020_heat_and_cooling_generating_systems'] += reposition_cost_heating_and_cooling_equipment
             elif component_categories[i] == 'dhw':
-              reposition_cost_domestic_hot_water_equipment = chapter.item(component).reposition[0] * component_sizes[i] * costs_increase
+              reposition_cost_domestic_hot_water_equipment = 0
               self._yearly_capital_costs.loc[year, 'D40_dhw'] += reposition_cost_domestic_hot_water_equipment
             elif component_categories[i] == 'distribution':
               reposition_cost_distribution_equipment = chapter.item(component).reposition[0] * component_sizes[i] * costs_increase
@@ -248,13 +247,13 @@ class CapitalCosts(CostBase):
       if self._configuration.retrofit_scenario == CURRENT_STATUS and pv:
         if (year % chapter.item('D2010_photovoltaic_system').lifetime) == 0:
           self._yearly_capital_costs.loc[year, 'D2010_photovoltaic_system'] += (
-              self._surface_pv * chapter.item('D2010_photovoltaic_system').reposition[0] * costs_increase
+              self._surface_pv * 0 * costs_increase
           )
       elif self._configuration.retrofit_scenario in (PV, SYSTEM_RETROFIT_AND_PV,
                                                      SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV):
         if (year % chapter.item('D2010_photovoltaic_system').lifetime) == 0:
           self._yearly_capital_costs.loc[year, 'D2010_photovoltaic_system'] += (
-              self._surface_pv * chapter.item('D2010_photovoltaic_system').reposition[0] * costs_increase
+              self._surface_pv * 0 * costs_increase
           )
 
   def system_components(self):

scripts/costs/total_maintenance_costs.py

@@ -57,14 +57,15 @@ class TotalMaintenanceCosts(CostBase):
     for energy_system in energy_systems:
       if cte.COOLING in energy_system.demand_types:
         for generation_system in energy_system.generation_systems:
-          if generation_system.system_type == cte.HEAT_PUMP and generation_system.source_medium == cte.AIR:
-            cooling_equipments['air_source_heat_pump'] = generation_system.nominal_cooling_output / 1000
-          elif generation_system.system_type == cte.HEAT_PUMP and generation_system.source_medium == cte.GROUND:
-            cooling_equipments['ground_source_heat_pump'] = generation_system.nominal_cooling_output / 1000
-          elif generation_system.system_type == cte.HEAT_PUMP and generation_system.source_medium == cte.WATER:
-            cooling_equipments['water_source_heat_pump'] = generation_system.nominal_cooling_output / 1000
-          else:
-            cooling_equipments['general_cooling_equipment'] = generation_system.nominal_cooling_output / 1000
+          if generation_system.fuel_type == cte.ELECTRICITY:
+            if generation_system.system_type == cte.HEAT_PUMP and generation_system.source_medium == cte.AIR:
+              cooling_equipments['air_source_heat_pump'] = generation_system.nominal_cooling_output / 1000
+            elif generation_system.system_type == cte.HEAT_PUMP and generation_system.source_medium == cte.GROUND:
+              cooling_equipments['ground_source_heat_pump'] = generation_system.nominal_cooling_output / 1000
+            elif generation_system.system_type == cte.HEAT_PUMP and generation_system.source_medium == cte.WATER:
+              cooling_equipments['water_source_heat_pump'] = generation_system.nominal_cooling_output / 1000
+            else:
+              cooling_equipments['general_cooling_equipment'] = generation_system.nominal_cooling_output / 1000
       if cte.HEATING in energy_system.demand_types:
         for generation_system in energy_system.generation_systems:
           if generation_system.system_type == cte.HEAT_PUMP and generation_system.source_medium == cte.AIR:
@@ -94,7 +95,7 @@ class TotalMaintenanceCosts(CostBase):
           else:
             dhw_equipments['general_heating_equipment'] = generation_system.nominal_heat_output / 1000
 
-    print(dhw_equipments)
+
     for heating_equipment in heating_equipments:
       component = self.search_hvac_equipment(heating_equipment)
       maintenance_cost = component.maintenance[0]

scripts/system_simulation_models/archetype13.py

@@ -19,7 +19,8 @@ class Archetype13:
     self._domestic_hot_water_peak_load = building.domestic_hot_water_peak_load[cte.YEAR][0]
     self._hourly_heating_demand = [demand / cte.HOUR_TO_SECONDS for demand in building.heating_demand[cte.HOUR]]
     self._hourly_cooling_demand = [demand / cte.HOUR_TO_SECONDS 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 = building.external_temperature[cte.HOUR]
     self.results = {}
@@ -30,11 +31,12 @@ class Archetype13:
     heat_pump = self._hvac_system.generation_systems[1]
     boiler = self._hvac_system.generation_systems[0]
     thermal_storage = boiler.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.WATER_HEAT_CAPACITY * cte.WATER_DENSITY * 25))
+      (self._heating_peak_load * storage_factor * cte.WATTS_HOUR_TO_JULES) /
+      (cte.WATER_HEAT_CAPACITY * cte.WATER_DENSITY * 25))
     return heat_pump, boiler, thermal_storage
 
   def dhw_sizing(self):
@@ -45,6 +47,8 @@ class Archetype13:
     dhw_tes = dhw_hp.energy_storage_systems[0]
     dhw_tes.volume = round(
       (self._domestic_hot_water_peak_load * storage_factor * 3600) / (cte.WATER_HEAT_CAPACITY * cte.WATER_DENSITY * 10))
+    if dhw_tes.volume == 0:
+      dhw_tes.volume = 1
     return dhw_hp, dhw_tes
 
   def heating_system_simulation(self):