partial refactor

costs/capital_costs.py

@@ -1,5 +1,5 @@
 """
-Life cycle costs module
+Capital costs module
 """
 import math
 
@@ -11,20 +11,26 @@ from configuration import Configuration
 from costs import SKIN_RETROFIT, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV, SYSTEM_RETROFIT_AND_PV
 
 
-class LifeCycleCosts:
+class CapitalCosts:
   """
-  Life cycle costs class
+  Capital costs class
   """
-  def __init__(self, building: Building, configuration: Configuration, retrofit_scenario):
+  def __init__(self, building: Building, configuration: Configuration):
     self._building = building
     self._configuration = configuration
-    self._retrofit_scenario = retrofit_scenario
     self._total_floor_area = 0
     for internal_zone in building.internal_zones:
       for thermal_zone in internal_zone.thermal_zones:
         self._total_floor_area += thermal_zone.total_floor_area
-
     self._archetype = None
+    for archetype in self._configuration.cost_catalog.entries('archetypes').archetype:
+      if str(building.function) == str(archetype.function):
+        self._archetype = archetype
+        self._capital_costs_chapter = self._archetype.capital_cost
+        break
+    if not self._archetype:
+      raise KeyError('archetype not found')
+
     self._capital_costs_chapter = None
     rng = range(configuration.number_of_years)
     self._yearly_capital_costs = pd.DataFrame(
@@ -66,18 +72,10 @@ class LifeCycleCosts:
     self._yearly_capital_incomes.loc[0, 'Subsidies HVAC'] = 0
     self._yearly_capital_incomes.loc[0, 'Subsidies PV'] = 0
 
-    for archetype in self._configuration.cost_catalog.entries('archetypes').archetype:
+  def calculate(self) -> tuple[pd.DataFrame, pd.DataFrame]:
-      if str(building.function) == str(archetype.function):
-        self._archetype = archetype
-        self._capital_costs_chapter = self._archetype.capital_cost
-        break
-    if not self._archetype:
-      raise KeyError('archetype not found')
-
-  def calculate_capital_costs(self):
     """
     Calculate capital cost
-    :return: pd.DataFrame
+    :return: pd.DataFrame, pd.DataFrame
     """
     surface_opaque = 0
     surface_transparent = 0
@@ -114,7 +112,7 @@ class LifeCycleCosts:
 
     self._yearly_capital_costs.fillna(0, inplace=True)
     own_capital = (1 - self._configuration.percentage_credit)
-    if self._retrofit_scenario in (SKIN_RETROFIT, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV):
+    if self._configuration.retrofit_scenario in (SKIN_RETROFIT, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV):
       chapter = self._capital_costs_chapter.chapter('B_shell')
       capital_cost_opaque = surface_opaque * chapter.item('B2010_opaque_walls').refurbishment[0]
       capital_cost_transparent = surface_transparent * chapter.item('B2020_transparent').refurbishment[0]
@@ -125,7 +123,7 @@ class LifeCycleCosts:
       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
 
-    if self._retrofit_scenario in (SYSTEM_RETROFIT_AND_PV, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV):
+    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')
       capital_cost_pv = surface_pv * chapter.item('D301010_photovoltaic_system').initial_investment[0]
       capital_cost_heating_equipment = peak_heating * chapter.item('D3020_heat_generating_systems').initial_investment[0]
@@ -160,7 +158,8 @@ class LifeCycleCosts:
       self._yearly_capital_costs.loc[year, 'B3010_opaque_roof'] = (
         -npf.pmt(
           self._configuration.interest_rate,
-          self._configuration.credit_years,capital_cost_roof * self._configuration.percentage_credit
+          self._configuration.credit_years,
+          capital_cost_roof * self._configuration.percentage_credit
         )
       )
       self._yearly_capital_costs.loc[year, 'B10_superstructure'] = (
@@ -170,46 +169,71 @@ class LifeCycleCosts:
           capital_cost_ground * self._configuration.percentage_credit
         )
       )
-      self._yearly_capital_costs.loc[year, 'D3020_heat_generating_systems'] = -npf.pmt(self._configuration.interest_rate,self._configuration.credit_years,
+      self._yearly_capital_costs.loc[year, 'D3020_heat_generating_systems'] = (
-                                                                                      capital_cost_heating_equipment
+        -npf.pmt(
-                                                                                      * (self._configuration.percentage_credit))
+          self._configuration.interest_rate,
-      self._yearly_capital_costs.loc[year, 'D3030_cooling_generation_systems'] = -npf.pmt(self._configuration.interest_rate, self._configuration.credit_years,
+          self._configuration.credit_years,
-                                                                                      capital_cost_cooling_equipment
+          capital_cost_heating_equipment * self._configuration.percentage_credit
-                                                                                      * (self._configuration.percentage_credit))
+        )
-      self._yearly_capital_costs.loc[year, 'D3040_distribution_systems'] = -npf.pmt(self._configuration.interest_rate, self._configuration.credit_years,
+      )
-                                                                                      capital_cost_distribution_equipment
+      self._yearly_capital_costs.loc[year, 'D3030_cooling_generation_systems'] = (
-                                                                                      * (self._configuration.percentage_credit))
+        -npf.pmt(
-      self._yearly_capital_costs.loc[year, 'D3080_other_hvac_ahu'] = -npf.pmt(self._configuration.interest_rate, self._configuration.credit_years,
+          self._configuration.interest_rate,
-                                                                                      capital_cost_other_hvac_ahu
+          self._configuration.credit_years,
-                                                                                      * (self._configuration.percentage_credit))
+          capital_cost_cooling_equipment * self._configuration.percentage_credit
-      self._yearly_capital_costs.loc[year, 'D5020_lighting_and_branch_wiring'] = -npf.pmt(self._configuration.interest_rate, self._configuration.credit_years,
+        )
-                                                                                      capital_cost_lighting
+      )
-                                                                                      * (self._configuration.percentage_credit))
+      self._yearly_capital_costs.loc[year, 'D3040_distribution_systems'] = (
+        -npf.pmt(
+          self._configuration.interest_rate,
+          self._configuration.credit_years,
+          capital_cost_distribution_equipment * self._configuration.percentage_credit
+        )
+      )
+      self._yearly_capital_costs.loc[year, 'D3080_other_hvac_ahu'] = (
+        -npf.pmt(
+          self._configuration.interest_rate,
+          self._configuration.credit_years,
+          capital_cost_other_hvac_ahu * self._configuration.percentage_credit
+        )
+      )
+      self._yearly_capital_costs.loc[year, 'D5020_lighting_and_branch_wiring'] = (
+        -npf.pmt(
+          self._configuration.interest_rate,
+          self._configuration.credit_years,
+          capital_cost_lighting * self._configuration.percentage_credit
+        )
+      )
+
       if (year % chapter.item('D3020_heat_generating_systems').lifetime) == 0:
-        reposition_cost_heating_equipment = peak_heating * chapter.item('D3020_heat_generating_systems').reposition[0] \
+        reposition_cost_heating_equipment = (
-                                            * costs_increase
+            peak_heating * chapter.item('D3020_heat_generating_systems').reposition[0] * costs_increase
+        )
         self._yearly_capital_costs.loc[year, 'D3020_heat_generating_systems'] += reposition_cost_heating_equipment
 
       if (year % chapter.item('D3030_cooling_generation_systems').lifetime) == 0:
-        reposition_cost_cooling_equipment = peak_cooling \
+        reposition_cost_cooling_equipment = (
-                                            * chapter.item('D3030_cooling_generation_systems').reposition[0] \
+            peak_cooling * chapter.item('D3030_cooling_generation_systems').reposition[0] * costs_increase
-                                            * costs_increase
+        )
         self._yearly_capital_costs.loc[year, 'D3030_cooling_generation_systems'] += reposition_cost_cooling_equipment
 
       if (year % chapter.item('D3080_other_hvac_ahu').lifetime) == 0:
-        reposition_cost_hvac_ahu = peak_cooling * chapter.item('D3080_other_hvac_ahu').reposition[0] * costs_increase
+        reposition_cost_hvac_ahu = (
+            peak_cooling * chapter.item('D3080_other_hvac_ahu').reposition[0] * costs_increase
+        )
         self._yearly_capital_costs.loc[year, 'D3080_other_hvac_ahu'] = reposition_cost_hvac_ahu
 
       if (year % chapter.item('D5020_lighting_and_branch_wiring').lifetime) == 0:
-        reposition_cost_lighting = total_floor_area * chapter.item('D5020_lighting_and_branch_wiring').reposition[0] \
+        reposition_cost_lighting = (
-                                   * costs_increase
+            self._total_floor_area * chapter.item('D5020_lighting_and_branch_wiring').reposition[0] * costs_increase
+        )
         self._yearly_capital_costs.loc[year, 'D5020_lighting_and_branch_wiring'] += reposition_cost_lighting
 
-      if self._retrofitting_scenario in (SYSTEM_RETROFIT_AND_PV, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV):
+      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'] += surface_pv \
+          self._yearly_capital_costs.loc[year]['D301010_photovoltaic_system'] += (
-                                                                                * chapter.item(
+              surface_pv * chapter.item('D301010_photovoltaic_system').reposition[0] * costs_increase
-            'D301010_photovoltaic_system').reposition[0] * costs_increase
+          )
     capital_cost_skin = capital_cost_opaque + capital_cost_ground + capital_cost_transparent + capital_cost_roof
     capital_cost_hvac = (
         capital_cost_heating_equipment +
@@ -219,9 +243,9 @@ class LifeCycleCosts:
     )
 
     self._yearly_capital_incomes.loc[0, 'Subsidies construction'] = (
-        capital_cost_skin * archetype.income.construction_subsidy/100
+        capital_cost_skin * self._archetype.income.construction_subsidy/100
     )
-    self._yearly_capital_incomes.loc[0, 'Subsidies HVAC'] = capital_cost_hvac * archetype.income.hvac_subsidy/100
+    self._yearly_capital_incomes.loc[0, 'Subsidies HVAC'] = capital_cost_hvac * self._archetype.income.hvac_subsidy/100
-    self._yearly_capital_incomes.loc[0, 'Subsidies PV'] = capital_cost_pv * archetype.income.photovoltaic_subsidy/100
+    self._yearly_capital_incomes.loc[0, 'Subsidies PV'] = capital_cost_pv * self._archetype.income.photovoltaic_subsidy/100
     self._yearly_capital_incomes.fillna(0, inplace=True)
     return self._yearly_capital_costs, self._yearly_capital_incomes

costs/configuration.py

@@ -21,7 +21,9 @@ class Configuration:
                gas_price_index,
                discount_rate,
                retrofitting_year_construction,
-               factories_handler
+               factories_handler,
+               retrofit_scenario,
+               fuel_type
                ):
     self._number_of_years = number_of_years
     self._percentage_credit = percentage_credit
@@ -35,6 +37,8 @@ class Configuration:
     self._retrofitting_year_construction = retrofitting_year_construction
     self._factories_handler = factories_handler
     self._cost_catalog = CostCatalogFactory(factories_handler).catalog
+    self._retrofit_scenario = retrofit_scenario
+    self._fuel_type = fuel_type
 
   @property
   def number_of_years(self):
@@ -196,3 +200,11 @@ class Configuration:
     Get cost catalog
     """
     return self._cost_catalog
+
+  @property
+  def retrofit_scenario(self):
+    return self._retrofit_scenario
+
+  @property
+  def fuel_type(self):
+    return self._fuel_type

costs/cost.py

@@ -5,7 +5,7 @@ import pandas as pd
 from hub.city_model_structure.city import City
 
 from configuration import Configuration
-from life_cycle_costs import LifeCycleCosts
+from capital_costs import LifeCycleCosts
 
 
 class Cost:

costs/end_of_life_costs.py

@@ -0,0 +1,48 @@
+"""
+End of life costs module
+"""
+import math
+import pandas as pd
+from hub.city_model_structure.building import Building
+
+from configuration import Configuration
+
+
+class EndOfLifeCosts:
+  """
+  End of life costs class
+  """
+  def __init__(self, building: Building, configuration: Configuration):
+    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:
+        self._total_floor_area += thermal_zone.total_floor_area
+    self._archetype = None
+    for archetype in self._configuration.cost_catalog.entries('archetypes').archetype:
+      if str(building.function) == str(archetype.function):
+        self._archetype = archetype
+        self._capital_costs_chapter = self._archetype.capital_cost
+        break
+    if not self._archetype:
+      raise KeyError('archetype not found')
+
+    rng = range(configuration.number_of_years)
+    self._yearly_end_of_life_costs = pd.DataFrame(index=rng, columns=['End_of_life_costs'], dtype='float')
+
+  def calculate(self):
+    """
+    Calculate end of life costs
+    :return: pd.DataFrame
+    """
+    archetype = self._archetype
+    total_floor_area = self._total_floor_area
+    for year in range(1, self._configuration.number_of_years + 1):
+      price_increase = math.pow(1 + self._configuration.consumer_price_index, year)
+      if year == self._configuration.number_of_years:
+        self._yearly_end_of_life_costs.at[year, 'End_of_life_costs'] = (
+            total_floor_area * archetype.end_of_life_cost * price_increase
+        )
+    self._yearly_end_of_life_costs.fillna(0, inplace=True)
+    return self._yearly_end_of_life_costs

costs/life_cycle_costs_old.py

@@ -334,6 +334,8 @@ class LifeCycleCosts:
     self._yearly_operational_incomes.fillna(0, inplace=True)
     return self._yearly_operational_incomes
 
+  ___________________________________________________________
+
   def calculate_total_maintenance_costs(self):
     """
     Calculate total maintenance costs

costs/total_maintenance_costs.py

@@ -0,0 +1,75 @@
+"""
+Total maintenance costs module
+"""
+import math
+import pandas as pd
+from hub.city_model_structure.building import Building
+import hub.helpers.constants as cte
+
+from configuration import Configuration
+
+
+class TotalMaintenanceCosts:
+  """
+  Total maintenance costs class
+  """
+  def __init__(self, building: Building, configuration: Configuration):
+    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:
+        self._total_floor_area += thermal_zone.total_floor_area
+    self._archetype = None
+    for archetype in self._configuration.cost_catalog.entries('archetypes').archetype:
+      if str(building.function) == str(archetype.function):
+        self._archetype = archetype
+        self._capital_costs_chapter = self._archetype.capital_cost
+        break
+    if not self._archetype:
+      raise KeyError('archetype not found')
+
+    rng = range(configuration.number_of_years)
+    self._yearly_maintenance_costs = pd.DataFrame(
+      index=rng,
+      columns=[
+        'Heating_maintenance',
+        'Cooling_maintenance',
+        'PV_maintenance'
+      ],
+      dtype='float'
+    )
+
+  def calculate(self) -> pd.DataFrame:
+    """
+    Calculate total maintenance costs
+    :return: pd.DataFrame
+    """
+    building = self._building
+    archetype = self._archetype
+    # todo: change area pv when the variable exists
+    roof_area = 0
+    for roof in building.roofs:
+      roof_area += roof.solid_polygon.area
+    surface_pv = roof_area * 0.5
+
+    peak_heating = building.heating_peak_load[cte.YEAR][cte.HEATING_PEAK_LOAD][0]
+    peak_cooling = building.cooling_peak_load[cte.YEAR][cte.COOLING_PEAK_LOAD][0]
+
+    maintenance_heating_0 = peak_heating * archetype.operational_cost.maintenance_heating
+    maintenance_cooling_0 = peak_cooling * archetype.operational_cost.maintenance_cooling
+    maintenance_pv_0 = surface_pv * archetype.operational_cost.maintenance_pv
+
+    for year in range(1, self._configuration.number_of_years + 1):
+      costs_increase = math.pow(1 + self._configuration.consumer_price_index, year)
+      self._yearly_maintenance_costs.loc[year, 'Heating_maintenance'] = (
+          maintenance_heating_0 * costs_increase
+      )
+      self._yearly_maintenance_costs.loc[year, 'Cooling_maintenance'] = (
+          maintenance_cooling_0 * costs_increase
+      )
+      self._yearly_maintenance_costs.loc[year, 'PV_maintenance'] = (
+          maintenance_pv_0 * costs_increase
+      )
+    self._yearly_maintenance_costs.fillna(0, inplace=True)
+    return self._yearly_maintenance_costs

costs/total_operational_costs.py

@@ -0,0 +1,109 @@
+"""
+Total operational costs module
+"""
+import math
+import pandas as pd
+
+from hub.city_model_structure.building import Building
+import hub.helpers.constants as cte
+
+from configuration import Configuration
+
+
+class TotalOperationalCosts:
+  """
+  End of life costs class
+  """
+  def __init__(self, building: Building, configuration: Configuration):
+    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:
+        self._total_floor_area += thermal_zone.total_floor_area
+    self._archetype = None
+    for archetype in self._configuration.cost_catalog.entries('archetypes').archetype:
+      if str(building.function) == str(archetype.function):
+        self._archetype = archetype
+        self._capital_costs_chapter = self._archetype.capital_cost
+        break
+    if not self._archetype:
+      raise KeyError('archetype not found')
+
+    rng = range(configuration.number_of_years)
+    self._yearly_operational_costs = pd.DataFrame(
+      index=rng,
+      columns=[
+        'Fixed_costs_electricity_peak',
+        'Fixed_costs_electricity_monthly',
+        'Variable_costs_electricity',
+        'Fixed_costs_gas',
+        'Variable_costs_gas'
+      ],
+      dtype='float'
+    )
+
+  @property
+  def calculate(self) -> pd.DataFrame:
+    """
+    Calculate total operational costs
+    :return: pd.DataFrame
+    """
+    building = self._building
+    archetype = self._archetype
+    total_floor_area = self._total_floor_area
+    factor_residential = total_floor_area / 80
+    # todo: split the heating between fuels
+    fixed_gas_cost_year_0 = 0
+    variable_gas_cost_year_0 = 0
+    electricity_heating = 0
+    domestic_hot_water_electricity = 0
+    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]
+      )
+    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_distribution = 0
+    total_electricity_consumption = (
+        electricity_heating + electricity_cooling + electricity_lighting + domestic_hot_water_electricity +
+        electricity_plug_loads + electricity_distribution
+    )
+
+    # todo: change when peak electricity demand is coded. Careful with factor residential
+    peak_electricity_demand = 100  # self._peak_electricity_demand
+    variable_electricity_cost_year_0 = total_electricity_consumption * 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
+
+    for year in range(1, self._configuration.number_of_years + 1):
+      price_increase_electricity = math.pow(1 + self._configuration.electricity_price_index, year)
+      price_increase_peak_electricity = math.pow(1 + self._configuration.electricity_peak_index, year)
+      price_increase_gas = math.pow(1 + self._configuration.gas_price_index, year)
+      self._yearly_operational_costs.at[year, 'Fixed_costs_electricity_peak'] = (
+          peak_electricity_cost_year_0 * price_increase_peak_electricity
+      )
+
+      self._yearly_operational_costs.at[year, 'Fixed_costs_electricity_monthly'] = (
+          monthly_electricity_cost_year_0 * price_increase_peak_electricity
+      )
+      self._yearly_operational_costs.at[year, 'Variable_costs_electricity'] = float(
+        variable_electricity_cost_year_0 * price_increase_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'] = (
+          variable_gas_cost_year_0 * price_increase_peak_electricity
+      )
+      self._yearly_operational_costs.at[year, 'Variable_costs_gas'] = (
+          variable_gas_cost_year_0 * price_increase_peak_electricity
+      )
+    self._yearly_operational_costs.fillna(0, inplace=True)
+
+    return self._yearly_operational_costs

costs/total_operational_incomes.py

@@ -0,0 +1,55 @@
+"""
+Total operational incomes module
+"""
+import math
+import pandas as pd
+from hub.city_model_structure.building import Building
+import hub.helpers.constants as cte
+
+from configuration import Configuration
+
+
+class TotalOperationalIncomes:
+  """
+  Total operational incomes class
+  """
+  def __init__(self, building: Building, configuration: Configuration):
+    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:
+        self._total_floor_area += thermal_zone.total_floor_area
+    self._archetype = None
+    for archetype in self._configuration.cost_catalog.entries('archetypes').archetype:
+      if str(building.function) == str(archetype.function):
+        self._archetype = archetype
+        self._capital_costs_chapter = self._archetype.capital_cost
+        break
+    if not self._archetype:
+      raise KeyError('archetype not found')
+
+    rng = range(configuration.number_of_years)
+    self._yearly_operational_incomes = pd.DataFrame(index=rng, columns=['Incomes electricity'], dtype='float')
+
+  def calculate(self) -> pd.DataFrame:
+    """
+    Calculate total operational incomes
+    :return: pd.DataFrame
+    """
+    building = self._building
+    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
+
+    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
+      self._yearly_operational_incomes.loc[year, 'Incomes electricity'] = (
+          onsite_electricity_production * price_export * price_increase_electricity
+      )
+
+    self._yearly_operational_incomes.fillna(0, inplace=True)
+    return self._yearly_operational_incomes