Update costs/version.py

.gitignore

@@ -1 +1,3 @@
 .idea
+cerc_costs.egg-info
+dist

cerc_costs.egg-info/PKG-INFO

@@ -1,9 +0,0 @@
-Metadata-Version: 2.1
-Name: cerc-costs
-Version: 0.1.0.0
-Summary: CERC costs contains the basic cost calculation per CERC-Hub building
-Classifier: License :: OSI Approved :: GNU Library or Lesser General Public License (LGPL)
-Classifier: Programming Language :: Python
-Classifier: Programming Language :: Python :: 3
-
-CERC costs contains the basic cost calculation per CERC-Hub building

cerc_costs.egg-info/SOURCES.txt

@@ -1,20 +0,0 @@
-pyproject.toml
-requirements.txt
-setup.py
-cerc_costs.egg-info/PKG-INFO
-cerc_costs.egg-info/SOURCES.txt
-cerc_costs.egg-info/dependency_links.txt
-cerc_costs.egg-info/requires.txt
-cerc_costs.egg-info/top_level.txt
-costs/__init__.py
-costs/__main__.py
-costs/capital_costs.py
-costs/configuration.py
-costs/constants.py
-costs/cost.py
-costs/cost_base.py
-costs/end_of_life_costs.py
-costs/total_maintenance_costs.py
-costs/total_operational_costs.py
-costs/total_operational_incomes.py
-costs/version.py

cerc_costs.egg-info/dependency_links.txt

@@ -1 +0,0 @@
-

cerc_costs.egg-info/requires.txt

@@ -1,4 +0,0 @@
-numpy_financial
-cerc_hub
-pandas
-setuptools

cerc_costs.egg-info/top_level.txt

@@ -1 +0,0 @@
-costs

costs/capital_costs.py

@@ -39,9 +39,9 @@ class CapitalCosts(CostBase):
       dtype='float'
     )
     self._yearly_capital_costs.loc[0, 'B2010_opaque_walls'] = 0
-    self._yearly_capital_costs.loc[0]['B2020_transparent'] = 0
+    self._yearly_capital_costs.loc[0, 'B2020_transparent'] = 0
     self._yearly_capital_costs.loc[0, 'B3010_opaque_roof'] = 0
-    self._yearly_capital_costs.loc[0]['B10_superstructure'] = 0
+    self._yearly_capital_costs.loc[0, 'B10_superstructure'] = 0
     self._yearly_capital_costs.loc[0, 'D3020_heat_generating_systems'] = 0
     self._yearly_capital_costs.loc[0, 'D3030_cooling_generation_systems'] = 0
     self._yearly_capital_costs.loc[0, 'D3040_distribution_systems'] = 0
@@ -81,8 +81,7 @@ class CapitalCosts(CostBase):
     capital_cost_other_hvac_ahu = 0
     capital_cost_lighting = 0
 
-    for internal_zone in self._building.internal_zones:
-      for thermal_zone in internal_zone.thermal_zones:
+    for thermal_zone in self._building.thermal_zones_from_internal_zones:
       for thermal_boundary in thermal_zone.thermal_boundaries:
         if thermal_boundary.type == 'Ground':
           surface_ground += thermal_boundary.opaque_area
@@ -108,9 +107,9 @@ class CapitalCosts(CostBase):
       capital_cost_roof = surface_roof * chapter.item('B3010_opaque_roof').refurbishment[0]
       capital_cost_ground = surface_ground * chapter.item('B10_superstructure').refurbishment[0]
       self._yearly_capital_costs.loc[0, 'B2010_opaque_walls'] = capital_cost_opaque * own_capital
-      self._yearly_capital_costs.loc[0]['B2020_transparent'] = capital_cost_transparent * own_capital
+      self._yearly_capital_costs.loc[0, 'B2020_transparent'] = capital_cost_transparent * own_capital
       self._yearly_capital_costs.loc[0, 'B3010_opaque_roof'] = capital_cost_roof * own_capital
-      self._yearly_capital_costs.loc[0]['B10_superstructure'] = capital_cost_ground * own_capital
+      self._yearly_capital_costs.loc[0, 'B10_superstructure'] = capital_cost_ground * own_capital
 
     if self._configuration.retrofit_scenario in (SYSTEM_RETROFIT_AND_PV, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV):
       chapter = self._capital_costs_chapter.chapter('D_services')
@@ -120,7 +119,7 @@ class CapitalCosts(CostBase):
       capital_cost_distribution_equipment = peak_cooling * chapter.item('D3040_distribution_systems').initial_investment[0]
       capital_cost_other_hvac_ahu = peak_cooling * chapter.item('D3080_other_hvac_ahu').initial_investment[0]
       capital_cost_lighting = self._total_floor_area * chapter.item('D5020_lighting_and_branch_wiring').initial_investment[0]
-      self._yearly_capital_costs.loc[0]['D301010_photovoltaic_system'] = capital_cost_pv
+      self._yearly_capital_costs.loc[0, 'D301010_photovoltaic_system'] = capital_cost_pv
       self._yearly_capital_costs.loc[0, 'D3020_heat_generating_systems'] = capital_cost_heating_equipment * own_capital
       self._yearly_capital_costs.loc[0, 'D3030_cooling_generation_systems'] = capital_cost_cooling_equipment * own_capital
       self._yearly_capital_costs.loc[0, 'D3040_distribution_systems'] = capital_cost_distribution_equipment * own_capital
@@ -220,7 +219,7 @@ class CapitalCosts(CostBase):
 
       if self._configuration.retrofit_scenario in (SYSTEM_RETROFIT_AND_PV, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV):
         if (year % chapter.item('D301010_photovoltaic_system').lifetime) == 0:
-          self._yearly_capital_costs.loc[year]['D301010_photovoltaic_system'] += (
+          self._yearly_capital_costs.loc[year, 'D301010_photovoltaic_system'] += (
               surface_pv * chapter.item('D301010_photovoltaic_system').reposition[0] * costs_increase
           )
     capital_cost_skin = capital_cost_opaque + capital_cost_ground + capital_cost_transparent + capital_cost_roof

costs/cost.py

@@ -5,6 +5,8 @@ Copyright © 2023 Project Coder Guille Gutierrez guillermo.gutierrezmorote@conco
 Code contributor Pilar Monsalvete Alvarez de Uribarri pilar.monsalvete@concordia.ca
 Code contributor Oriol Gavalda Torrellas oriol.gavalda@concordia.ca
 """
+import datetime
+
 import pandas as pd
 import numpy_financial as npf
 from hub.city_model_structure.building import Building
@@ -62,13 +64,6 @@ class Cost:
     """
     return self._building
 
-  @building.setter
-  def building(self, value: Building):
-    """
-    Set current building.
-    """
-    self._building = value
-
   def _npv_from_list(self, list_cashflow):
     return npf.npv(self._configuration.discount_rate, list_cashflow)
 
@@ -84,7 +79,6 @@ class Cost:
     global_operational_costs = TotalOperationalCosts(self._building, self._configuration).calculate()
     global_maintenance_costs = TotalMaintenanceCosts(self._building, self._configuration).calculate()
     global_operational_incomes = TotalOperationalIncomes(self._building, self._configuration).calculate()
-
     df_capital_costs_skin = (
         global_capital_costs['B2010_opaque_walls'] +
         global_capital_costs['B2020_transparent'] +
@@ -101,8 +95,6 @@ class Cost:
 
     df_end_of_life_costs = global_end_of_life_costs['End_of_life_costs']
     df_operational_costs = (
-        global_operational_costs['Fixed_costs_electricity_peak'] +
-        global_operational_costs['Fixed_costs_electricity_monthly'] +
         global_operational_costs['Fixed_costs_electricity_peak'] +
         global_operational_costs['Fixed_costs_electricity_monthly'] +
         global_operational_costs['Variable_costs_electricity'] +
@@ -160,5 +152,4 @@ class Cost:
       'global_maintenance_costs',
       'global_operational_incomes'
     ]
-
     return results

costs/cost_base.py

@@ -19,8 +19,7 @@ class CostBase:
     self._building = building
     self._configuration = configuration
     self._total_floor_area = 0
-    for internal_zone in building.internal_zones:
-      for thermal_zone in internal_zone.thermal_zones:
+    for thermal_zone in building.thermal_zones_from_internal_zones:
       self._total_floor_area += thermal_zone.total_floor_area
     self._archetype = None
     self._capital_costs_chapter = None

costs/peak_load.py

@@ -28,38 +28,29 @@ class PeakLoad:
     heating = 0
     cooling = 0
     for system in self._building.energy_systems:
-      for demand_type in system.demand_types:
-        if demand_type == cte.HEATING:
+      if cte.HEATING in system.demand_types:
         heating = 1
-        if demand_type == cte.COOLING:
+      if cte.COOLING in system.demand_types:
         cooling = 1
     if cte.MONTH in self._building.heating_peak_load.keys() and cte.MONTH in self._building.cooling_peak_load.keys():
-      peak_lighting = 0
-      peak_appliances = 0
-      for thermal_zone in self._building.internal_zones[0].thermal_zones:
-        lighting = thermal_zone.lighting
-        for schedule in lighting.schedules:
-          peak = max(schedule.values) * lighting.density * thermal_zone.total_floor_area
-          if peak > peak_lighting:
-            peak_lighting = peak
-        appliances = thermal_zone.appliances
-        for schedule in appliances.schedules:
-          peak = max(schedule.values) * appliances.density * thermal_zone.total_floor_area
-          if peak > peak_appliances:
-            peak_appliances = peak
+      peak_lighting = self._building.lighting_peak_load[cte.YEAR][0]
+      peak_appliances = self._building.appliances_peak_load[cte.YEAR][0]
       monthly_electricity_peak = [0.9 * peak_lighting + 0.7 * peak_appliances] * 12
-      conditioning_peak = []
-      for i, value in enumerate(self._building.heating_peak_load[cte.MONTH]):
-        if cooling * self._building.cooling_peak_load[cte.MONTH][i] > heating * value:
-          conditioning_peak.append(cooling * self._building.cooling_peak_load[cte.MONTH][i])
+      conditioning_peak = max(self._building.heating_peak_load[cte.MONTH], self._building.cooling_peak_load[cte.MONTH])
+      for i in range(len(conditioning_peak)):
+        if cooling == 1 and heating == 1:
+          conditioning_peak[i] = conditioning_peak[i]
+          continue
+        elif cooling == 0:
+          conditioning_peak[i] = self._building.heating_peak_load[cte.MONTH][i] * heating
         else:
-          conditioning_peak.append(heating * value)
+          conditioning_peak[i] = self._building.cooling_peak_load[cte.MONTH][i] * cooling
         monthly_electricity_peak[i] += 0.8 * conditioning_peak[i]
+
       electricity_peak_load_results = pd.DataFrame(
         monthly_electricity_peak,
-        columns=[f'{self._building.name} electricity peak load W']
+        columns=[f'electricity peak load W']
       )
     else:
-      electricity_peak_load_results = pd.DataFrame(array, columns=[f'{self._building.name} electricity peak load W'])
-
+      electricity_peak_load_results = pd.DataFrame(array, columns=[f'electricity peak load W'])
     return electricity_peak_load_results

costs/total_operational_costs.py

@@ -20,6 +20,7 @@ class TotalOperationalCosts(CostBase):
   """
   End of life costs class
   """
+
   def __init__(self, building: Building, configuration: Configuration):
     super().__init__(building, configuration)
     self._yearly_operational_costs = pd.DataFrame(
@@ -48,19 +49,20 @@ class TotalOperationalCosts(CostBase):
     variable_gas_cost_year_0 = 0
     electricity_heating = 0
     domestic_hot_water_electricity = 0
+    # todo: each fuel has different units that have to be processed
     if self._configuration.fuel_type == 1:
       fixed_gas_cost_year_0 = archetype.operational_cost.fuels[1].fixed_monthly * 12 * factor_residential
       variable_gas_cost_year_0 = (
-          (building.heating_consumption[cte.YEAR][0] + building.domestic_hot_water_consumption[cte.YEAR][0]) / 1000 *
-          archetype.operational_cost.fuels[1].variable[0]
+          (building.heating_consumption[cte.YEAR][0] + building.domestic_hot_water_consumption[cte.YEAR][0])
+          / (1000 * cte.WATTS_HOUR_TO_JULES) * archetype.operational_cost.fuels[1].variable[0]
       )
     if self._configuration.fuel_type == 0:
       electricity_heating = building.heating_consumption[cte.YEAR][0] / 1000
       domestic_hot_water_electricity = building.domestic_hot_water_consumption[cte.YEAR][0] / 1000
 
     electricity_cooling = building.cooling_consumption[cte.YEAR][0] / 1000
-    electricity_lighting = building.lighting_electrical_demand[cte.YEAR]['insel meb'] / 1000
-    electricity_plug_loads = building.appliances_electrical_demand[cte.YEAR]['insel meb'] / 1000
+    electricity_lighting = building.lighting_electrical_demand[cte.YEAR][0] / 1000
+    electricity_plug_loads = building.appliances_electrical_demand[cte.YEAR][0] / 1000
     electricity_distribution = 0
     total_electricity_consumption = (
         electricity_heating + electricity_cooling + electricity_lighting + domestic_hot_water_electricity +
@@ -71,7 +73,9 @@ class TotalOperationalCosts(CostBase):
     peak_electricity_load = PeakLoad(building).electricity_peak_load
     peak_load_value = peak_electricity_load.max(axis=1)
     peak_electricity_demand = peak_load_value[1] / 1000  # self._peak_electricity_demand adapted to kW
-    variable_electricity_cost_year_0 = total_electricity_consumption * archetype.operational_cost.fuels[0].variable[0]
+    variable_electricity_cost_year_0 = (
+      total_electricity_consumption / cte.WATTS_HOUR_TO_JULES * archetype.operational_cost.fuels[0].variable[0]
+    )
     peak_electricity_cost_year_0 = peak_electricity_demand * archetype.operational_cost.fuels[0].fixed_power * 12
     monthly_electricity_cost_year_0 = archetype.operational_cost.fuels[0].fixed_monthly * 12 * factor_residential
 
@@ -85,8 +89,12 @@ class TotalOperationalCosts(CostBase):
       self._yearly_operational_costs.at[year, 'Fixed_costs_electricity_monthly'] = (
           monthly_electricity_cost_year_0 * price_increase_peak_electricity
       )
+      if not isinstance(variable_electricity_cost_year_0, pd.DataFrame):
+        variable_costs_electricity = variable_electricity_cost_year_0 * price_increase_electricity
+      else:
+        variable_costs_electricity = float(variable_electricity_cost_year_0.iloc[0] * price_increase_electricity)
       self._yearly_operational_costs.at[year, 'Variable_costs_electricity'] = (
-        float(variable_electricity_cost_year_0.iloc[0] * price_increase_electricity)
+        variable_costs_electricity
       )
       self._yearly_operational_costs.at[year, 'Fixed_costs_gas'] = fixed_gas_cost_year_0 * price_increase_gas
       self._yearly_operational_costs.at[year, 'Variable_costs_gas'] = (

costs/total_operational_incomes.py

@@ -28,15 +28,16 @@ class TotalOperationalIncomes(CostBase):
     :return: pd.DataFrame
     """
     building = self._building
+    archetype = self._archetype
     if cte.YEAR not in building.onsite_electrical_production:
       onsite_electricity_production = 0
     else:
-      onsite_electricity_production = building.onsite_electrical_production[cte.YEAR][0] / 1000
+      onsite_electricity_production = building.onsite_electrical_production[cte.YEAR][0]
 
     for year in range(1, self._configuration.number_of_years + 1):
       price_increase_electricity = math.pow(1 + self._configuration.electricity_price_index, year)
       # todo: check the adequate assignation of price. Pilar
-      price_export = 0.075  # archetype.income.electricity_export
+      price_export = archetype.income.electricity_export * cte.WATTS_HOUR_TO_JULES * 1000  # to account for unit change
       self._yearly_operational_incomes.loc[year, 'Incomes electricity'] = (
           onsite_electricity_production * price_export * price_increase_electricity
       )

costs/version.py

@@ -5,4 +5,4 @@ Copyright © 2023 Project Coder Guille Gutierrez guillermo.gutierrezmorote@conco
 Code contributor Pilar Monsalvete Alvarez de Uribarri pilar.monsalvete@concordia.ca
 Code contributor Oriol Gavalda Torrellas oriol.gavalda@concordia.ca
 """
-__version__ = '0.1.0.1'
+__version__ = '0.1.0.6'

input_files/selected_building_2864.geojson

@@ -1,121 +0,0 @@
-{
-    "type": "FeatureCollection",
-    "features": [
-        {
-            "type": "Feature",
-            "id": 2864,
-            "geometry": {
-                "type": "Polygon",
-                "coordinates": [
-                    [
-                        [
-                            -73.55628837310991,
-                            45.60732526295055
-                        ],
-                        [
-                            -73.55628287285629,
-                            45.607324262904456
-                        ],
-                        [
-                            -73.55609247288925,
-                            45.607288563416546
-                        ],
-                        [
-                            -73.55607107262188,
-                            45.60734486277528
-                        ],
-                        [
-                            -73.55612487276466,
-                            45.60735496306114
-                        ],
-                        [
-                            -73.55609867281544,
-                            45.60742366317157
-                        ],
-                        [
-                            -73.55624087271804,
-                            45.60745026331904
-                        ],
-                        [
-                            -73.55628837310991,
-                            45.60732526295055
-                        ]
-                    ]
-                ]
-            },
-            "properties": {
-                "OBJECTID_12_13": 2864,
-                "ID_UEV": "02033771",
-                "CIVIQUE_DE": " 8212",
-                "CIVIQUE_FI": " 8212",
-                "NOM_RUE": "avenue Peterborough  (ANJ)",
-                "SUITE_DEBU": " ",
-                "MUNICIPALI": "50",
-                "ETAGE_HORS": 1,
-                "NOMBRE_LOG": 1,
-                "ANNEE_CONS": 1960,
-                "CODE_UTILI": "1000",
-                "LETTRE_DEB": " ",
-                "LETTRE_FIN": " ",
-                "LIBELLE_UT": "Logement",
-                "CATEGORIE_": "R\u00c3\u00a9gulier",
-                "MATRICULE8": "0051-49-2041-2-000-0000",
-                "SUPERFICIE": 450,
-                "SUPERFIC_1": 176,
-                "NO_ARROND_": "REM09",
-                "Shape_Leng": 0.000666191644361,
-                "OBJECTID": 2864,
-                "Join_Count": 1,
-                "TARGET_FID": 2864,
-                "feature_id": "bdd1f0fe-89de-46d2-80dc-87d3636df60a",
-                "md_id": " ",
-                "acqtech": 1360,
-                "acqtech_en": "Lidar",
-                "acqtech_fr": "Lidar",
-                "provider": 461,
-                "provideren": "Municipal",
-                "providerfr": "Municipal",
-                "datemin": "20151124",
-                "datemax": "20151208",
-                "haccmin": 2,
-                "haccmax": 2,
-                "vaccmin": 1,
-                "vaccmax": 1,
-                "heightmin": 1.17,
-                "heightmax": 7.5,
-                "elevmin": 45.48,
-                "elevmax": 45.96,
-                "bldgarea": 193.18,
-                "comment": " ",
-                "OBJECTID_1": 2864,
-                "Shape_Le_1": 0.000666191644361,
-                "Shape_Ar_1": 2.22753099997e-08,
-                "OBJECTID_12": 2864,
-                "Join_Count_1": 1,
-                "TARGET_FID_1": 2863,
-                "g_objectid": "897744",
-                "g_co_mrc": "66023",
-                "g_code_mun": "66023",
-                "g_arrond": "REM09",
-                "g_anrole": "2019",
-                "g_usag_pre": "R\u00c3\u00a9sidentiel",
-                "g_no_lot": "1113400",
-                "g_nb_poly_": "1",
-                "g_utilisat": "1000",
-                "g_nb_logem": "1",
-                "g_nb_locau": " ",
-                "g_descript": "Unit\u00c3\u00a9 d'\u00c3\u00a9valuation",
-                "g_id_provi": "66023005149204120000000",
-                "g_sup_tota": "450.1",
-                "g_geometry": "0.000958907",
-                "g_geomet_1": "5.20226e-008",
-                "g_dat_acqu": "2020-02-12 00:00:00.0000000",
-                "g_dat_char": "2020-02-17 00:00:00.0000000",
-                "Shape_Leng_1": 0.000666191644361,
-                "Shape_Area_1": 2.22753099997e-08,
-                "Shape_Length": 0.0006661919640545334,
-                "Shape_Area": 2.22753099997e-08
-            }
-        }
-    ]
-}

tests/unit_tests.py

@@ -42,14 +42,16 @@ class Initialize:
       sra_file = str((output_path / f'{city.name}_sra.xml').resolve())
       subprocess.run(['sra', sra_file], stdout=subprocess.DEVNULL)
       ResultFactory('sra', city, output_path).enrich()
-
+      print(f'sra completed {datetime.datetime.now() - start}')
       for building in city.buildings:
         building.energy_systems_archetype_name = 'system 1 gas pv'
       EnergySystemsFactory('montreal_custom', city).enrich()
+      print(f'energy systems completed {datetime.datetime.now() - start}')
       EnergyBuildingsExportsFactory('insel_monthly_energy_balance', city, output_path).export()
       _insel_files = glob.glob(f'{output_path}/*.insel')
       for insel_file in _insel_files:
         subprocess.run(['insel', str(insel_file)], stdout=subprocess.DEVNULL)
+      print(f'insel completed {datetime.datetime.now() - start}')
       ResultFactory('insel_monthly_energy_balance', city, output_path).enrich()
       self._city = city
       print(f'init completed {datetime.datetime.now() - start}')