correct weird mix of implementations

costs/__init__.py

@@ -6,4 +6,3 @@ from .end_of_life_costs import EndOfLifeCosts
 from .total_maintenance_costs import TotalMaintenanceCosts
 from .total_operational_costs import TotalOperationalCosts
 from .total_operational_incomes import TotalOperationalIncomes
-

costs/constants.py

@@ -1,3 +1,7 @@
+"""
+Constants module
+"""
+
 # constants
 CURRENT_STATUS = 0
 SKIN_RETROFIT = 1

costs/cost.py

@@ -1,10 +1,10 @@
 """
 Cost module
 """
-import hub.helpers.dictionaries
 import pandas as pd
 import numpy_financial as npf
 from hub.city_model_structure.building import Building
+from hub.helpers.dictionaries import Dictionaries
 
 from costs.configuration import Configuration
 from costs import CapitalCosts, EndOfLifeCosts, TotalMaintenanceCosts, TotalOperationalCosts, TotalOperationalIncomes
@@ -30,7 +30,9 @@ class Cost:
                retrofitting_year_construction=2020,
                factories_handler='montreal_custom',
                retrofit_scenario=CURRENT_STATUS,
-               dictionary=hub.helpers.dictionaries.Dictionaries().hub_function_to_montreal_custom_costs_function):
+               dictionary=None):
+    if dictionary is None:
+      dictionary = Dictionaries().hub_function_to_montreal_custom_costs_function
     self._building = building
     fuel_type = 0
     if "gas" in building.energy_systems_archetype_name:

costs/cost_base.py

@@ -3,7 +3,6 @@ Cost base module
 """
 
 from hub.city_model_structure.building import Building
-from hub.helpers.dictionaries import Dictionaries
 
 from costs.configuration import Configuration
 

costs/life_cycle_costs.py

@@ -1,313 +0,0 @@
-"""
-Life cycle cost module
-SPDX - License - Identifier: LGPL - 3.0 - or -later
-Copyright © 2022 Project Author Guille Gutierrez Guillermo.GutierrezMorote@concordia.ca
-Code contributor Pilar Monsalvete Alvarez de Uribarri pilar_monsalvete@concordia.ca
-Code contributor Oriol Gavalda Torrellas oriol.gavalda@concordia.ca
-"""
-
-from hub.persistence.models.city_object import CityObject
-from configuration import Configuration
-
-
-class LifeCycleCosts:
-  """
-  Life cycle costs class
-  """
-  def __init__(self, building: CityObject, building_results: dict, configuration: Configuration):
-    self._building = building
-    self._building_results = building_results
-    self._configuration = configuration
-    self._archetype = None
-    for archetype in self._configuration.cost_catalog.entries('archetypes').archetype:
-      if str(building.function) == str(archetype.function):
-        self._archetype = archetype
-        break
-    if not self._archetype:
-      raise KeyError('archetype not found')
-
-  @property
-  def calculate_capital_costs(self):
-    """
-    Calculate capital cost
-    :return: pd.DataFrame
-    """
-    capital_cost_pv = 0
-    capital_cost_opaque = 0
-    capital_cost_ground = 0
-    capital_cost_transparent = 0
-    capital_cost_roof = 0
-    capital_cost_heating_equipment = 0
-    capital_cost_cooling_equipment = 0
-    capital_cost_distribution_equipment = 0
-    capital_cost_other_hvac_ahu = 0
-    capital_cost_lighting = 0
-
-    chapters = self._archetype.capital_cost
-
-    peak_heating = self._building_results.heating_peak_load[cte.YEAR].values[0]/1000
-    peak_cooling = building.cooling_peak_load[cte.YEAR].values[0]/1000
-    # 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
-
-    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, 'B3010_opaque_roof'] = 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
-    self._yearly_capital_costs.loc[0, 'D3080_other_hvac_ahu'] = 0
-    self._yearly_capital_costs.loc[0, 'D5020_lighting_and_branch_wiring'] = 0
-
-    self._yearly_capital_incomes.loc[0, 'Subsidies construction'] = 0
-    self._yearly_capital_incomes.loc[0, 'Subsidies HVAC'] = 0
-    self._yearly_capital_incomes.loc[0, 'Subsidies PV'] = 0
-
-    self._yearly_capital_costs.fillna(0, inplace=True)
-    if self._retrofitting_scenario in (SKIN_RETROFIT, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV):
-      chapter = chapters.chapter('B_shell')
-      capital_cost_opaque = self._building.wall_area * chapter.item('B2010_opaque_walls').refurbishment[0]
-      capital_cost_transparent = self._building.windows_area * chapter.item('B2020_transparent').refurbishment[0]
-      capital_cost_roof = self._building.roof_area * chapter.item('B3010_opaque_roof').refurbishment[0]
-      capital_cost_ground = self._building.area * chapter.item('B10_superstructure').refurbishment[0]
-
-
-      self._yearly_capital_costs.loc[0, 'B2010_opaque_walls'] = capital_cost_opaque * (1-PERCENTAGE_CREDIT)
-      self._yearly_capital_costs.loc[0]['B2020_transparent'] = capital_cost_transparent * (1-PERCENTAGE_CREDIT)
-      self._yearly_capital_costs.loc[0, 'B3010_opaque_roof'] = capital_cost_roof * (1-PERCENTAGE_CREDIT)
-      self._yearly_capital_costs.loc[0]['B10_superstructure'] = capital_cost_ground * (1-PERCENTAGE_CREDIT)
-
-
-    if self._retrofitting_scenario in (SYSTEM_RETROFIT_AND_PV, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV):
-      chapter = chapters.chapter('D_services')
-      capital_cost_pv = surface_pv * chapter.item('D301010_photovoltaic_system').initial_investment[0]
-      self._yearly_capital_costs.loc[0]['D301010_photovoltaic_system'] = capital_cost_pv
-      capital_cost_heating_equipment = (
-          peak_heating * chapter.item('D3020_heat_generating_systems').initial_investment[0]
-      )
-      capital_cost_cooling_equipment = (
-          peak_cooling * chapter.item('D3030_cooling_generation_systems').initial_investment[0]
-      )
-      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._building.total_heating_area * chapter.item('D5020_lighting_and_branch_wiring').initial_investment[0]
-
-      self._yearly_capital_costs.loc[0, 'D3020_heat_generating_systems'] = capital_cost_heating_equipment * (1-PERCENTAGE_CREDIT)
-      self._yearly_capital_costs.loc[0, 'D3030_cooling_generation_systems'] = capital_cost_cooling_equipment * (1-PERCENTAGE_CREDIT)
-      self._yearly_capital_costs.loc[0, 'D3040_distribution_systems'] = capital_cost_distribution_equipment * (1-PERCENTAGE_CREDIT)
-      self._yearly_capital_costs.loc[0, 'D3080_other_hvac_ahu'] = capital_cost_other_hvac_ahu * (1-PERCENTAGE_CREDIT)
-      self._yearly_capital_costs.loc[0, 'D5020_lighting_and_branch_wiring'] = capital_cost_lighting * (1-PERCENTAGE_CREDIT)
-
-    for year in range(1, self._number_of_years):
-      chapter = chapters.chapter('D_services')
-      costs_increase = math.pow(1 + self._consumer_price_index, year)
-      self._yearly_capital_costs.loc[year, 'B2010_opaque_walls'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS,
-                                                                          capital_cost_opaque * (PERCENTAGE_CREDIT))
-      self._yearly_capital_costs.loc[year, 'B2020_transparent'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS,
-                                                                          capital_cost_transparent * (PERCENTAGE_CREDIT)
-                                                                          )
-      self._yearly_capital_costs.loc[year, 'B3010_opaque_roof'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS,capital_cost_roof
-                                                                          * (PERCENTAGE_CREDIT))
-      self._yearly_capital_costs.loc[year, 'B10_superstructure'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS,
-                                                                             capital_cost_ground * (PERCENTAGE_CREDIT))
-      self._yearly_capital_costs.loc[year, 'D3020_heat_generating_systems'] = -npf.pmt(INTEREST_RATE,CREDIT_YEARS,
-                                                                                      capital_cost_heating_equipment
-                                                                                      * (PERCENTAGE_CREDIT))
-      self._yearly_capital_costs.loc[year, 'D3030_cooling_generation_systems'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS,
-                                                                                      capital_cost_cooling_equipment
-                                                                                      * (PERCENTAGE_CREDIT))
-      self._yearly_capital_costs.loc[year, 'D3040_distribution_systems'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS,
-                                                                                      capital_cost_distribution_equipment
-                                                                                      * (PERCENTAGE_CREDIT))
-      self._yearly_capital_costs.loc[year, 'D3080_other_hvac_ahu'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS,
-                                                                                      capital_cost_other_hvac_ahu
-                                                                                      * (PERCENTAGE_CREDIT))
-      self._yearly_capital_costs.loc[year, 'D5020_lighting_and_branch_wiring'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS,
-                                                                                      capital_cost_lighting
-                                                                                      * (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] \
-                                            * 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 \
-                                            * chapter.item('D3030_cooling_generation_systems').reposition[0] \
-                                            * 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
-        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 = self._building.total_heating_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 (year % chapter.item('D301010_photovoltaic_system').lifetime) == 0:
-          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
-    capital_cost_hvac = (
-        capital_cost_heating_equipment +
-        capital_cost_cooling_equipment +
-        capital_cost_distribution_equipment +
-        capital_cost_other_hvac_ahu + capital_cost_lighting
-    )
-
-    self._yearly_capital_incomes.loc[0, 'Subsidies construction'] = (
-        capital_cost_skin * 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 PV'] = capital_cost_pv * archetype.income.photovoltaic_subsidy/100
-    self._yearly_capital_incomes.fillna(0, inplace=True)
-    return self._yearly_capital_costs, self._yearly_capital_incomes
-
-  @property
-  def calculate_end_of_life_costs(self):
-    """
-    Calculate end of life costs
-    :return: pd.DataFrame
-    """
-    archetype = self._archetype
-
-    for year in range(1, self._number_of_years + 1):
-      price_increase = math.pow(1 + self._consumer_price_index, year)
-      if year == self._number_of_years:
-        self._yearly_end_of_life_costs.at[
-          year, 'End_of_life_costs'] = self._building.total_heating_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
-
-  @property
-  def calculate_total_operational_costs(self):
-    """
-    Calculate total operational costs
-    :return: pd.DataFrame
-    """
-    building = self._building
-    archetype = self._archetype
-
-    factor_residential = self._building.total_heating_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._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._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._number_of_years + 1):
-      price_increase_electricity = math.pow(1 + self._electricity_price_index, year)
-      price_increase_peak_electricity = math.pow(1 + self._electricity_peak_index, year)
-      price_increase_gas = math.pow(1 + self._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
-
-  @property
-  def calculate_total_operational_incomes(self):
-    """
-    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._number_of_years + 1):
-      price_increase_electricity = math.pow(1 + self._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
-
-  @property
-  def calculate_total_maintenance_costs(self):
-    """
-    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._number_of_years + 1):
-      costs_increase = math.pow(1 + self._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/peak_load.py

@@ -0,0 +1,52 @@
+import pandas as pd
+
+import hub.helpers.constants as cte
+
+
+class PeakLoad:
+
+  def __init__(self, building):
+    self._building = building
+
+  @property
+  def electricity_peak_load(self):
+    array = [None] * 12
+    heating = 0
+    cooling = 0
+    for system in self._building.energy_systems:
+      for demand_type in system.demand_types:
+        if demand_type == cte.HEATING:
+          heating = 1
+        if demand_type == cte.COOLING:
+          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:
+          for value in schedule.values:
+            if value * lighting.density * thermal_zone.total_floor_area > peak_lighting:
+              peak_lighting = value * lighting.density * thermal_zone.total_floor_area
+        appliances = thermal_zone.appliances
+        for schedule in appliances.schedules:
+          for value in schedule.values:
+            if value * appliances.density * thermal_zone.total_floor_area > peak_appliances:
+              peak_appliances = value * appliances.density * thermal_zone.total_floor_area
+
+      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])
+        else:
+          conditioning_peak.append(heating * value)
+        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']
+      )
+    else:
+      electricity_peak_load_results = pd.DataFrame(array, columns=[f'{self._building.name} electricity peak load W'])
+
+    return electricity_peak_load_results

costs/results.py

@@ -1,122 +0,0 @@
-class Results:
-  def __init__(self, building_results: dict):
-    self._monthly_cooling_peak_load = building_results['monthly_cooling_peak_load']
-    self._yearly_cooling_peak_load = building_results['yearly_cooling_peak_load']
-    self._monthly_heating_peak_load = building_results['monthly_heating_peak_load']
-    self._yearly_heating_peak_load = building_results['yearly_heating_peak_load']
-    self._monthly_cooling_demand = building_results['monthly_cooling_demand']
-    self._yearly_cooling_demand = building_results['yearly_cooling_demand']
-    self._monthly_heating_demand = building_results['monthly_heating_demand']
-    self._yearly_heating_demand = building_results['yearly_heating_demand']
-    self._monthly_lighting_electrical_demand = building_results['monthly_lighting_electrical_demand']
-    self._yearly_lighting_electrical_demand = building_results['yearly_lighting_electrical_demand']
-    self._monthly_appliances_electrical_demand = building_results['monthly_appliances_electrical_demand']
-    self._yearly_appliances_electrical_demand = building_results['yearly_appliances_electrical_demand']
-    self._monthly_domestic_hot_water_heat_demand = building_results['monthly_domestic_hot_water_heat_demand']
-    self._yearly_domestic_hot_water_heat_demand = building_results['yearly_domestic_hot_water_heat_demand']
-    self._monthly_heating_consumption = building_results['monthly_heating_consumption']
-    self._yearly_heating_consumption = building_results['yearly_heating_consumption']
-    self._monthly_cooling_consumption = building_results['monthly_cooling_consumption']
-    self._yearly_cooling_consumption = building_results['yearly_cooling_consumption']
-    self._monthly_domestic_hot_water_consumption = building_results['monthly_domestic_hot_water_consumption']
-    self._yearly_domestic_hot_water_consumption = building_results['yearly_domestic_hot_water_consumption']
-    self._monthly_distribution_systems_electrical_consumption = building_results['monthly_distribution_systems_electrical_consumption']
-    self._yearly_distribution_systems_electrical_consumption = building_results['yearly_distribution_systems_electrical_consumption']
-    self._monthly_on_site_electrical_production = building_results['monthly_on_site_electrical_production']
-    self._yearly_on_site_electrical_production = building_results['yearly_on_site_electrical_production']
-
-  @property
-  def monthly_cooling_peak_load(self):
-    return self._monthly_cooling_peak_load
-
-  @property
-  def yearly_cooling_peak_load(self):
-    return self._yearly_cooling_peak_load
-
-  @property
-  def monthly_heating_peak_load(self):
-    return self._monthly_heating_peak_load
-
-  @property
-  def yearly_heating_peak_load(self):
-    return self._yearly_heating_peak_load
-
-  @property
-  def monthly_cooling_demand(self):
-    return self._monthly_cooling_demand
-
-  @property
-  def yearly_cooling_demand(self):
-    return self._yearly_cooling_demand
-
-  @property
-  def monthly_heating_demand(self):
-    return self._monthly_heating_demand
-
-  @property
-  def yearly_heating_demand(self):
-    return self._yearly_heating_demand
-
-  @property
-  def monthly_lighting_electrical_demand(self):
-    return self._monthly_lighting_electrical_demand
-
-  @property
-  def yearly_lighting_electrical_demand(self):
-    return self._yearly_lighting_electrical_demand
-
-  @property
-  def monthly_appliances_electrical_demand(self):
-    return self._monthly_appliances_electrical_demand
-
-  @property
-  def yearly_appliances_electrical_demand(self):
-    return self._yearly_appliances_electrical_demand
-
-  @property
-  def monthly_domestic_hot_water_heat_demand(self):
-    return self._monthly_heating_demand
-
-  @property
-  def yearly_domestic_hot_water_heat_demand(self):
-    return self._yearly_heating_demand
-
-  @property
-  def monthly_heating_consumption(self):
-    return self._monthly_heating_consumption
-
-  @property
-  def yearly_heating_consumption(self):
-    return self._yearly_heating_consumption
-
-  @property
-  def monthly_cooling_consumption(self):
-    return self._monthly_cooling_consumption
-
-  @property
-  def yearly_cooling_consumption(self):
-    return self._yearly_cooling_consumption
-
-  @property
-  def monthly_domestic_hot_water_consumption(self):
-    return self._monthly_domestic_hot_water_consumption
-
-  @property
-  def yearly_domestic_hot_water_consumption(self):
-    return self._yearly_domestic_hot_water_consumption
-
-  @property
-  def monthly_distribution_systems_electrical_consumption(self):
-    return self._monthly_distribution_systems_electrical_consumption
-
-  @property
-  def yearly_distribution_systems_electrical_consumption(self):
-    return self._yearly_distribution_systems_electrical_consumption
-
-  @property
-  def monthly_on_site_electrical_production(self):
-    return self._monthly_on_site_electrical_production
-
-  @property
-  def yearly_on_site_electrical_production(self):
-    return self._yearly_on_site_electrical_production

costs/total_operational_costs.py

@@ -9,48 +9,7 @@ import hub.helpers.constants as cte
 
 from costs.configuration import Configuration
 from costs.cost_base import CostBase
-
+from costs.peak_load import PeakLoad
-
-def Peak_load(building):
-  array = [None] * 12
-  heating = 0
-  cooling = 0
-  for system in building.energy_systems:
-    for demand_type in system.demand_types:
-      if demand_type == cte.HEATING:
-        heating = 1
-      if demand_type == cte.COOLING:
-        cooling = 1
-  if cte.MONTH in building.heating_peak_load.keys() and cte.MONTH in building.cooling_peak_load.keys():
-    peak_lighting = 0
-    peak_appliances = 0
-    for thermal_zone in building.internal_zones[0].thermal_zones:
-      lighting = thermal_zone.lighting
-      for schedule in lighting.schedules:
-        for value in schedule.values:
-          if value * lighting.density * thermal_zone.total_floor_area > peak_lighting:
-            peak_lighting = value * lighting.density * thermal_zone.total_floor_area
-      appliances = thermal_zone.appliances
-      for schedule in appliances.schedules:
-        for value in schedule.values:
-          if value * appliances.density * thermal_zone.total_floor_area > peak_appliances:
-            peak_appliances = value * appliances.density * thermal_zone.total_floor_area
-
-    monthly_electricity_peak = [0.9 * peak_lighting + 0.7 * peak_appliances] * 12
-    conditioning_peak = []
-    for i, value in enumerate(building.heating_peak_load[cte.MONTH]):
-      if cooling * building.cooling_peak_load[cte.MONTH][i] > heating * value:
-        conditioning_peak.append(cooling * building.cooling_peak_load[cte.MONTH][i])
-      else:
-        conditioning_peak.append(heating * value)
-      monthly_electricity_peak[i] += 0.8 * conditioning_peak[i]
-
-    electricity_peak_load_results = pd.DataFrame(monthly_electricity_peak
-                                                 , columns=[f'{building.name} electricity peak load W'])
-  else:
-    electricity_peak_load_results = pd.DataFrame(array, columns=[f'{building.name} electricity peak load W'])
-
-  return electricity_peak_load_results
 
 
 class TotalOperationalCosts(CostBase):
@@ -106,7 +65,7 @@ class TotalOperationalCosts(CostBase):
     )
 
     # todo: change when peak electricity demand is coded. Careful with factor residential
-    peak_electricity_load = Peak_load(building)
+    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]