cleaned code. not found bug. not working

costs/README.md

@@ -1,4 +1,3 @@
-# Cerc costs 
+# costs_workflow
 
-Uses the cerc-hub as a base for cost calculation, it's intended to be used after executing the complete monthly energy
+This workflow is a test to check that the proccess of calculating costs is correct before creating the API.
-balance workflow called building by building

costs/__init__.py

@@ -1,9 +1,53 @@
 """
 Cost workflow initialization
 """
-from .capital_costs import CapitalCosts
+import glob
-from .end_of_life_costs import EndOfLifeCosts
+import os
-from .total_maintenance_costs import TotalMaintenanceCosts
+from pathlib import Path
-from .total_operational_costs import TotalOperationalCosts
-from .total_operational_incomes import TotalOperationalIncomes
 
+# configurable parameters
+file_path = Path('./data/selected_building_2864.geojson').resolve()
+CONSTRUCTION_FORMAT = 'nrcan'
+USAGE_FORMAT = 'comnet'
+ENERGY_SYSTEM_FORMAT = 'montreal_custom'
+ATTIC_HEATED_CASE = 0
+BASEMENT_HEATED_CASE = 1
+NUMBER_OF_YEARS = 31
+PERCENTAGE_CREDIT = 0
+INTEREST_RATE = 0.04
+CREDIT_YEARS = 15
+CONSUMER_PRICE_INDEX = 0.04
+ELECTRICITY_PEAK_INDEX = 0.05
+ELECTRICITY_PRICE_INDEX = 0.05
+GAS_PRICE_INDEX = 0.05
+DISCOUNT_RATE = 0.03
+RETROFITTING_YEAR_CONSTRUCTION = 2020
+
+CLIMATE_REFERENCE_CITY = 'Montreal'
+WEATHER_FILE = 'CAN_PQ_Montreal.Intl.AP.716270_CWEC.epw'
+WEATHER_FORMAT = 'epw'
+CURRENT_STATUS = 0
+SKIN_RETROFIT = 1
+SYSTEM_RETROFIT_AND_PV = 2
+SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV = 3
+RETROFITTING_SCENARIOS = [
+  CURRENT_STATUS,
+  SKIN_RETROFIT,
+  SYSTEM_RETROFIT_AND_PV,
+  SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV
+]
+
+EMISSION_FACTOR_ELECTRICITY_QUEBEC = 0.0015 #https://www.cer-rec.gc.ca/en/data-analysis/energy-markets/provincial-territorial-energy-profiles/provincial-territorial-energy-profiles-quebec.html#:~:text=GHG%20Emissions,-Quebec's%20GHG%20emissions&text=The%20largest%20emitting%20sectors%20in,2.3%20MT%20CO2e.
+EMISSION_FACTOR_GAS_QUEBEC = 0.183 #https://www.canada.ca/en/environment-climate-change/services/climate-change/pricing-pollution-how-it-will-work/output-based-pricing-system/federal-greenhouse-gas-offset-system/emission-factors-reference-values.html
+EMISSION_FACTOR_BIOMASS_QUEBEC = 0.035 #Data from Spain. https://www.miteco.gob.es/es/cambio-climatico/temas/mitigacion-politicas-y-medidas/factoresemision_tcm30-479095.pdf
+EMISSION_FACTOR_FUEL_OIL_QUEBEC = 0.274
+EMISSION_FACTOR_DIESEL_QUEBEC = 0.240
+
+
+tmp_folder = Path('./tmp').resolve()
+out_path = Path('./outputs').resolve()
+files = glob.glob(f'{out_path}/*')
+print('path', file_path)
+for file in files:
+  if file != '.gitignore':
+    os.remove(file)

costs/__main__.py

@@ -4,3 +4,251 @@ SPDX - License - Identifier: LGPL - 3.0 - or -later
 Copyright © 2022 Project Author Pilar Monsalvete Alvarez de Uribarri pilar.monsalvete@concordia.ca
 Code contributor Oriol Gavalda Torrellas oriol.gavalda@concordia.ca
 """
+
+from pathlib import Path
+
+import numpy_financial as npf
+import pandas as pd
+from hub.catalog_factories.costs_catalog_factory import CostCatalogFactory
+from hub.helpers.dictionaries import Dictionaries
+from hub.imports.construction_factory import ConstructionFactory
+from hub.imports.energy_systems_factory import EnergySystemsFactory
+from hub.imports.geometry_factory import GeometryFactory
+from hub.imports.usage_factory import UsageFactory
+from hub.imports.weather_factory import WeatherFactory
+from monthly_energy_balance_engine import MonthlyEnergyBalanceEngine
+from sra_engine import SraEngine
+from printing_results import *
+from hub.helpers import constants as cte
+from life_cycle_costs import LifeCycleCosts
+
+from costs import CONSTRUCTION_FORMAT
+from costs import ENERGY_SYSTEM_FORMAT, RETROFITTING_SCENARIOS, NUMBER_OF_YEARS
+from costs import CONSUMER_PRICE_INDEX, ELECTRICITY_PEAK_INDEX, ELECTRICITY_PRICE_INDEX, GAS_PRICE_INDEX, DISCOUNT_RATE
+from costs import SKIN_RETROFIT, SYSTEM_RETROFIT_AND_PV, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV
+from costs import RETROFITTING_YEAR_CONSTRUCTION
+
+# import paths
+from results import Results
+
+
+def _npv_from_list(npv_discount_rate, list_cashflow):
+  lcc_value = npf.npv(npv_discount_rate, list_cashflow)
+  return lcc_value
+
+
+def _search_archetype(costs_catalog, building_function):
+  costs_archetypes = costs_catalog.entries('archetypes').archetypes
+  for building_archetype in costs_archetypes:
+    if str(building_function) == str(building_archetype.function):
+      return building_archetype
+  raise KeyError('archetype not found')
+
+
+life_cycle_results = pd.DataFrame()
+file_path = (Path(__file__).parent.parent / 'input_files' / 'summerschool_one_building.geojson')
+climate_reference_city = 'Montreal'
+weather_format = 'epw'
+construction_format = 'nrcan'
+usage_format = 'nrcan'
+energy_systems_format = 'montreal_custom'
+attic_heated_case = 0
+basement_heated_case = 1
+
+out_path = (Path(__file__).parent.parent / 'out_files')
+tmp_folder = (Path(__file__).parent / 'tmp')
+
+print('[simulation start]')
+city = GeometryFactory('geojson',
+                       path=file_path,
+                       height_field='citygml_me',
+                       year_of_construction_field='ANNEE_CONS',
+                       function_field='CODE_UTILI',
+                       function_to_hub=Dictionaries().montreal_function_to_hub_function).city
+city.climate_reference_city = climate_reference_city
+city.climate_file = (tmp_folder / f'{climate_reference_city}.cli').resolve()
+print(f'city created from {file_path}')
+WeatherFactory(weather_format, city).enrich()
+print('enrich weather... done')
+ConstructionFactory(construction_format, city).enrich()
+print('enrich constructions... done')
+UsageFactory(usage_format, city).enrich()
+print('enrich usage... done')
+for building in city.buildings:
+  building.energy_systems_archetype_name = 'system 1 gas pv'
+EnergySystemsFactory(energy_systems_format, city).enrich()
+print('enrich systems... done')
+
+print('exporting:')
+sra_file = (tmp_folder / f'{city.name}_sra.xml').resolve()
+SraEngine(city, sra_file, tmp_folder)
+print('    sra processed...')
+catalog = CostCatalogFactory('montreal_custom').catalog
+
+for retrofitting_scenario in RETROFITTING_SCENARIOS:
+
+  if retrofitting_scenario in (SKIN_RETROFIT, SYSTEM_RETROFIT_AND_PV):
+    for building in city.buildings:
+      building.year_of_construction = RETROFITTING_YEAR_CONSTRUCTION
+    ConstructionFactory(CONSTRUCTION_FORMAT, city).enrich()
+    print('enrich retrofitted constructions... done')
+
+  if retrofitting_scenario in (SYSTEM_RETROFIT_AND_PV, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV):
+    for building in city.buildings:
+      building.energy_systems_archetype_name = 'system 6 electricity pv'
+    EnergySystemsFactory(ENERGY_SYSTEM_FORMAT, city).enrich()
+    print('enrich systems... done')
+
+  MonthlyEnergyBalanceEngine(city, tmp_folder)
+  print('    insel processed...')
+
+  for building in city.buildings:
+    for energy_system in building.energy_systems:
+      if cte.HEATING in energy_system.demand_types:
+        energy_system.generation_system.heat_power = building.heating_peak_load[cte.YEAR][0]
+      if cte.COOLING in energy_system.demand_types:
+        energy_system.generation_system.cooling_power = building.cooling_peak_load[cte.YEAR][0]
+    print(f' heating consumption {building.heating_consumption[cte.YEAR][0]}')
+  print('importing results:')
+  results = Results(city, out_path)
+  results.print()
+  print('results printed...')
+
+  print('[simulation end]')
+
+  print(f'beginning costing scenario {retrofitting_scenario} systems... done')
+
+  for building in city.buildings:
+    total_floor_area = 0
+    function = Dictionaries().hub_function_to_montreal_custom_costs_function[building.function]
+    archetype = _search_archetype(catalog, function)
+    print('lcc for first building started')
+    if "gas" in building.energy_systems_archetype_name:
+      FUEL_TYPE = 1
+    else:
+      FUEL_TYPE = 0
+
+    lcc = LifeCycleCosts(building, archetype, NUMBER_OF_YEARS, CONSUMER_PRICE_INDEX, ELECTRICITY_PEAK_INDEX,
+                         ELECTRICITY_PRICE_INDEX, GAS_PRICE_INDEX, DISCOUNT_RATE, retrofitting_scenario, FUEL_TYPE)
+    global_capital_costs, global_capital_incomes = lcc.calculate_capital_costs()
+    global_end_of_life_costs = lcc.calculate_end_of_life_costs()
+    global_operational_costs = lcc.calculate_total_operational_costs
+    global_maintenance_costs = lcc.calculate_total_maintenance_costs()
+    global_operational_incomes = lcc.calculate_total_operational_incomes(retrofitting_scenario)
+    full_path_output = Path(out_path / f'output {retrofitting_scenario} {building.name}.xlsx').resolve()
+    with pd.ExcelWriter(full_path_output) as writer:
+      global_capital_costs.to_excel(writer, sheet_name='global_capital_costs')
+      global_end_of_life_costs.to_excel(writer, sheet_name='global_end_of_life_costs')
+      global_operational_costs.to_excel(writer, sheet_name='global_operational_costs')
+      global_maintenance_costs.to_excel(writer, sheet_name='global_maintenance_costs')
+      global_operational_incomes.to_excel(writer, sheet_name='global_operational_incomes')
+      global_capital_incomes.to_excel(writer, sheet_name='global_capital_incomes')
+
+    investmentcosts = pd.DataFrame([])
+    print('RETROFITTING SCENARIO', retrofitting_scenario)
+    if retrofitting_scenario == 0:
+      investmentcosts = [global_capital_costs['B2010_opaque_walls'][0],
+                         global_capital_costs['B2020_transparent'][0],
+                         global_capital_costs['B3010_opaque_roof'][0],
+                         global_capital_costs['B10_superstructure'][0],
+                         global_capital_costs['D3020_heat_generating_systems'][0],
+                         global_capital_costs['D3080_other_hvac_ahu'][0],
+                         global_capital_costs['D5020_lighting_and_branch_wiring'][0],
+                         global_capital_costs['D301010_photovoltaic_system'][0]]
+      investmentcosts = pd.DataFrame(investmentcosts)
+
+    else:
+      investmentcosts[f'retrofitting_scenario_{retrofitting_scenario}'] = \
+        [global_capital_costs['B2010_opaque_walls'][0],
+         global_capital_costs['B2020_transparent'][0],
+         global_capital_costs['B3010_opaque_roof'][0],
+         global_capital_costs['B10_superstructure'][0],
+         global_capital_costs['D3020_heat_generating_systems'][0],
+         global_capital_costs['D3080_other_hvac_ahu'][0],
+         global_capital_costs['D5020_lighting_and_branch_wiring'][0],
+         global_capital_costs['D301010_photovoltaic_system'][0]]
+
+    investmentcosts.index = ['Opaque walls', 'Transparent walls', 'Opaque roof', 'Superstructure',
+                             'Heat generation systems', 'Other HVAC AHU', 'Lighting and branch wiring', 'PV systems']
+
+    df_capital_costs_skin = (
+        global_capital_costs['B2010_opaque_walls'] + global_capital_costs['B2020_transparent'] +
+        global_capital_costs['B3010_opaque_roof'] + global_capital_costs['B10_superstructure']
+    )
+    df_capital_costs_systems = (
+        global_capital_costs['D3020_heat_generating_systems'] +
+        global_capital_costs['D3030_cooling_generation_systems'] +
+        global_capital_costs['D3080_other_hvac_ahu'] +
+        global_capital_costs['D5020_lighting_and_branch_wiring'] +
+        global_capital_costs['D301010_photovoltaic_system']
+    )
+    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'] +
+      global_operational_costs['Fixed_costs_gas'] +
+      global_operational_costs['Variable_costs_gas']
+    )
+    df_maintenance_costs = (
+        global_maintenance_costs['Heating_maintenance'] +
+        global_maintenance_costs['Cooling_maintenance'] +
+        global_maintenance_costs['PV_maintenance']
+    )
+    df_operational_incomes = global_operational_incomes['Incomes electricity']
+
+    df_capital_incomes = (
+        global_capital_incomes['Subsidies construction'] +
+        global_capital_incomes['Subsidies HVAC'] +
+        global_capital_incomes['Subsidies PV']
+    )
+
+    life_cycle_costs_capital_skin = _npv_from_list(DISCOUNT_RATE, df_capital_costs_skin.values.tolist())
+    life_cycle_costs_capital_systems = _npv_from_list(DISCOUNT_RATE, df_capital_costs_systems.values.tolist())
+    life_cycle_costs_end_of_life_costs = _npv_from_list(DISCOUNT_RATE, df_end_of_life_costs.values.tolist())
+    life_cycle_operational_costs = _npv_from_list(DISCOUNT_RATE, df_operational_costs.values.tolist())
+    life_cycle_maintenance_costs = _npv_from_list(DISCOUNT_RATE, df_maintenance_costs.values.tolist())
+    life_cycle_operational_incomes = _npv_from_list(DISCOUNT_RATE, df_operational_incomes.values.tolist())
+    life_cycle_capital_incomes = _npv_from_list(DISCOUNT_RATE, df_capital_incomes.values.tolist())
+
+    life_cycle_costs = (
+        life_cycle_costs_capital_skin +
+        life_cycle_costs_capital_systems +
+        life_cycle_costs_end_of_life_costs +
+        life_cycle_operational_costs +
+        life_cycle_maintenance_costs -
+        life_cycle_operational_incomes -
+        life_cycle_capital_incomes
+    )
+    total_floor_area += lcc.calculate_total_floor_area()
+    life_cycle_results[f'Scenario {retrofitting_scenario}'] = [life_cycle_costs_capital_skin,
+                                                               life_cycle_costs_capital_systems,
+                                                               life_cycle_costs_end_of_life_costs,
+                                                               life_cycle_operational_costs,
+                                                               life_cycle_maintenance_costs,
+                                                               -life_cycle_operational_incomes,
+                                                               -life_cycle_capital_incomes]
+
+    life_cycle_results.index = ['total_capital_costs_skin',
+                                'total_capital_costs_systems',
+                                'end_of_life_costs',
+                                'total_operational_costs',
+                                'total_maintenance_costs',
+                                'operational_incomes',
+                                'capital_incomes']
+
+    print(f'Scenario {retrofitting_scenario} {life_cycle_costs}')
+
+#    printing_results(investmentcosts, life_cycle_results, total_floor_area)
+
+
+
+
+
+
+
+
+
+

costs/__main__emissions.py

@@ -0,0 +1,68 @@
+"""
+Costs Workflow
+SPDX - License - Identifier: LGPL - 3.0 - or -later
+Copyright © 2022 Project Author Pilar Monsalvete Alvarez de Uribarri pilar.monsalvete@concordia.ca
+Code contributor Oriol Gavalda Torrellas oriol.gavalda@concordia.ca
+"""
+
+from pathlib import Path
+
+import pandas as pd
+from hub.helpers.dictionaries import Dictionaries
+from hub.catalog_factories.costs_catalog_factory import CostCatalogFactory
+
+from costs import EMISSION_FACTOR_ELECTRICITY_QUEBEC, EMISSION_FACTOR_GAS_QUEBEC, EMISSION_FACTOR_BIOMASS_QUEBEC, \
+  EMISSION_FACTOR_FUEL_OIL_QUEBEC, EMISSION_FACTOR_DIESEL_QUEBEC, NUMBER_OF_YEARS
+
+def _search_archetype(costs_catalog, building_function):
+  costs_archetypes = costs_catalog.entries('archetypes').archetypes
+  for building_archetype in costs_archetypes:
+    if str(building_function) == str(building_archetype.function):
+      return building_archetype
+  raise KeyError('archetype not found')
+
+catalog = CostCatalogFactory('montreal_custom').catalog
+
+for building in city.buildings:
+  building_heating_consumption = 1000
+  building_domestic_water_consumption = 1000
+  building_cooling_consumption = 1000
+  distribution_systems_electrical_consumption = 1000
+  lighting_electrical_demand = 1000
+  appliances_electrical_demand = 1000
+  rng = range(NUMBER_OF_YEARS)
+
+  function = Dictionaries().hub_function_to_montreal_custom_costs_function[building.function]
+  archetype = _search_archetype(catalog, function)
+
+  print('co2 for first building started')
+  if "gas" in building.energy_systems_archetype_name:
+    gas_consumption = building_heating_consumption + building_domestic_water_consumption
+    electricity_consumption = building_cooling_consumption + distribution_systems_electrical_consumption + \
+                              lighting_electrical_demand + appliances_electrical_demand
+    biomass_consumption = 0
+    fuel_oil_consumption = 0
+    diesel_consumption = 0
+  else:
+    gas_consumption = 0
+    electricity_consumption = building_heating_consumption + building_domestic_water_consumption + \
+                              building_cooling_consumption + distribution_systems_electrical_consumption + \
+                              lighting_electrical_demand + appliances_electrical_demand
+    biomass_consumption = 0
+    fuel_oil_consumption = 0
+    diesel_consumption = 0
+
+  CO2_emissions = pd.DataFrame(index=rng, columns=['CO2 emissions gas', 'CO2 emissions electricity',
+                                                   'CO2 Emissions biomass', 'CO2 emissions fueloil',
+                                                   'CO2 emissions diesel'], dtype='float')
+
+  for year in range(1, NUMBER_OF_YEARS+1):
+
+    CO2_emissions.at[year,'CO2 emissions gas'] = gas_consumption * EMISSION_FACTOR_GAS_QUEBEC
+    CO2_emissions.at[year, 'CO2 emissions electricity'] = electricity_consumption * EMISSION_FACTOR_ELECTRICITY_QUEBEC
+    CO2_emissions.at[year, 'CO2 emissions biomass'] = biomass_consumption * EMISSION_FACTOR_BIOMASS_QUEBEC
+    CO2_emissions.at[year, 'CO2 emissions fueloil'] = fuel_oil_consumption * EMISSION_FACTOR_FUEL_OIL_QUEBEC
+    CO2_emissions.at[year, 'CO2 emissions diesel'] = diesel_consumption * EMISSION_FACTOR_DIESEL_QUEBEC
+
+  CO2_emissions_total = CO2_emissions.sum()
+

costs/capital_costs.py

@@ -1,236 +0,0 @@
-"""
-Capital costs module
-"""
-import math
-
-import pandas as pd
-import numpy_financial as npf
-from hub.city_model_structure.building import Building
-import hub.helpers.constants as cte
-from costs.configuration import Configuration
-from costs.constants import SKIN_RETROFIT, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV, SYSTEM_RETROFIT_AND_PV
-from costs.cost_base import CostBase
-
-
-class CapitalCosts(CostBase):
-  """
-  Capital costs class
-  """
-  def __init__(self, building: Building, configuration: Configuration):
-    super().__init__(building, configuration)
-    self._yearly_capital_costs = pd.DataFrame(
-      index=self._rng,
-      columns=[
-        'B2010_opaque_walls',
-        'B2020_transparent',
-        'B3010_opaque_roof',
-        'B10_superstructure',
-        'D301010_photovoltaic_system',
-        'D3020_heat_generating_systems',
-        'D3030_cooling_generation_systems',
-        'D3040_distribution_systems',
-        'D3080_other_hvac_ahu',
-        'D5020_lighting_and_branch_wiring'
-      ],
-      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, '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 = pd.DataFrame(
-      index=self._rng,
-      columns=[
-        'Subsidies construction',
-        'Subsidies HVAC',
-        'Subsidies PV'
-      ],
-      dtype='float'
-    )
-    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
-
-  def calculate(self) -> tuple[pd.DataFrame, pd.DataFrame]:
-    """
-    Calculate capital cost
-    :return: pd.DataFrame, pd.DataFrame
-    """
-    surface_opaque = 0
-    surface_transparent = 0
-    surface_roof = 0
-    surface_ground = 0
-    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
-
-    for internal_zone in self._building.internal_zones:
-      for thermal_zone in internal_zone.thermal_zones:
-        for thermal_boundary in thermal_zone.thermal_boundaries:
-          if thermal_boundary.type == 'Ground':
-            surface_ground += thermal_boundary.opaque_area
-          elif thermal_boundary.type == 'Roof':
-            surface_roof += thermal_boundary.opaque_area
-          elif thermal_boundary.type == 'Wall':
-            surface_opaque += thermal_boundary.opaque_area * (1 - thermal_boundary.window_ratio)
-            surface_transparent += thermal_boundary.opaque_area * thermal_boundary.window_ratio
-
-    peak_heating = self._building.heating_peak_load[cte.YEAR][0] / 1000
-    peak_cooling = self._building.cooling_peak_load[cte.YEAR][0] / 1000
-
-    surface_pv = 0
-    for roof in self._building.roofs:
-      surface_pv += roof.solid_polygon.area * roof.solar_collectors_area_reduction_factor
-
-    self._yearly_capital_costs.fillna(0, inplace=True)
-    own_capital = 1 - self._configuration.percentage_credit
-    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]
-      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, 'B3010_opaque_roof'] = capital_cost_roof * 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')
-      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]
-      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._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, '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
-      self._yearly_capital_costs.loc[0, 'D3080_other_hvac_ahu'] = capital_cost_other_hvac_ahu * own_capital
-      self._yearly_capital_costs.loc[0, 'D5020_lighting_and_branch_wiring'] = capital_cost_lighting * own_capital
-
-    for year in range(1, self._configuration.number_of_years):
-      chapter = self._capital_costs_chapter.chapter('D_services')
-      costs_increase = math.pow(1 + self._configuration.consumer_price_index, year)
-      self._yearly_capital_costs.loc[year, 'B2010_opaque_walls'] = (
-        -npf.pmt(
-          self._configuration.interest_rate,
-          self._configuration.credit_years,
-          capital_cost_opaque * self._configuration.percentage_credit
-        )
-      )
-      self._yearly_capital_costs.loc[year, 'B2020_transparent'] = (
-        -npf.pmt(
-          self._configuration.interest_rate,
-          self._configuration.credit_years,
-          capital_cost_transparent * self._configuration.percentage_credit
-        )
-      )
-      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._yearly_capital_costs.loc[year, 'B10_superstructure'] = (
-        -npf.pmt(
-          self._configuration.interest_rate,
-          self._configuration.credit_years,
-          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,
-          capital_cost_heating_equipment * self._configuration.percentage_credit
-        )
-      )
-      self._yearly_capital_costs.loc[year, 'D3030_cooling_generation_systems'] = (
-        -npf.pmt(
-          self._configuration.interest_rate,
-          self._configuration.credit_years,
-          capital_cost_cooling_equipment * 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] * 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._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._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 * 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 * self._archetype.income.construction_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 * 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

@@ -1,225 +0,0 @@
-"""
-Configuration module
-"""
-from hub.catalog_factories.costs_catalog_factory import CostsCatalogFactory
-from hub.catalog_factories.catalog import Catalog
-
-
-class Configuration:
-  """
-  Configuration class
-  """
-
-  def __init__(self,
-               number_of_years,
-               percentage_credit,
-               interest_rate,
-               credit_years,
-               consumer_price_index,
-               electricity_peak_index,
-               electricity_price_index,
-               gas_price_index,
-               discount_rate,
-               retrofitting_year_construction,
-               factories_handler,
-               retrofit_scenario,
-               fuel_type,
-               dictionary
-               ):
-    self._number_of_years = number_of_years
-    self._percentage_credit = percentage_credit
-    self._interest_rate = interest_rate
-    self._credit_years = credit_years
-    self._consumer_price_index = consumer_price_index
-    self._electricity_peak_index = electricity_peak_index
-    self._electricity_price_index = electricity_price_index
-    self._gas_price_index = gas_price_index
-    self._discount_rate = discount_rate
-    self._retrofitting_year_construction = retrofitting_year_construction
-    self._factories_handler = factories_handler
-    self._costs_catalog = CostsCatalogFactory(factories_handler).catalog
-    self._retrofit_scenario = retrofit_scenario
-    self._fuel_type = fuel_type
-    self._dictionary = dictionary
-
-  @property
-  def number_of_years(self):
-    """
-    Get number of years
-    """
-    return self._number_of_years
-
-  @number_of_years.setter
-  def number_of_years(self, value):
-    """
-    Set number of years
-    """
-    self._number_of_years = value
-
-  @property
-  def percentage_credit(self):
-    """
-    Get percentage credit
-    """
-    return self._percentage_credit
-
-  @percentage_credit.setter
-  def percentage_credit(self, value):
-    """
-    Set percentage credit
-    """
-    self._percentage_credit = value
-
-  @property
-  def interest_rate(self):
-    """
-    Get interest rate
-    """
-    return self._interest_rate
-
-  @interest_rate.setter
-  def interest_rate(self, value):
-    """
-    Set interest rate
-    """
-    self._interest_rate = value
-
-  @property
-  def credit_years(self):
-    """
-    Get credit years
-    """
-    return self._credit_years
-
-  @credit_years.setter
-  def credit_years(self, value):
-    """
-    Set credit years
-    """
-    self._credit_years = value
-
-  @property
-  def consumer_price_index(self):
-    """
-    Get consumer price index
-    """
-    return self._consumer_price_index
-
-  @consumer_price_index.setter
-  def consumer_price_index(self, value):
-    """
-    Set consumer price index
-    """
-    self._consumer_price_index = value
-
-  @property
-  def electricity_peak_index(self):
-    """
-    Get electricity peak index
-    """
-    return self._electricity_peak_index
-
-  @electricity_peak_index.setter
-  def electricity_peak_index(self, value):
-    """
-    Set electricity peak index
-    """
-    self._electricity_peak_index = value
-
-  @property
-  def electricity_price_index(self):
-    """
-    Get electricity price index
-    """
-    return self._electricity_price_index
-
-  @electricity_price_index.setter
-  def electricity_price_index(self, value):
-    """
-    Set electricity price index
-    """
-    self._electricity_price_index = value
-
-  @property
-  def gas_price_index(self):
-    """
-    Get gas price index
-    """
-    return self._gas_price_index
-
-  @gas_price_index.setter
-  def gas_price_index(self, value):
-    """
-    Set gas price index
-    """
-    self._gas_price_index = value
-
-  @property
-  def discount_rate(self):
-    """
-    Get discount rate
-    """
-    return self._discount_rate
-
-  @discount_rate.setter
-  def discount_rate(self, value):
-    """
-    Set discount rate
-    """
-    self._discount_rate = value
-
-  @property
-  def retrofitting_year_construction(self):
-    """
-    Get retrofitting year construction
-    """
-    return self._retrofitting_year_construction
-
-  @retrofitting_year_construction.setter
-  def retrofitting_year_construction(self, value):
-    """
-    Set retrofitting year construction
-    """
-    self._retrofitting_year_construction = value
-
-  @property
-  def factories_handler(self):
-    """
-    Get factories handler
-    """
-    return self._factories_handler
-
-  @factories_handler.setter
-  def factories_handler(self, value):
-    """
-    Set factories handler
-    """
-    self._factories_handler = value
-
-  @property
-  def costs_catalog(self) -> Catalog:
-    """
-    Get costs catalog
-    """
-    return self._costs_catalog
-
-  @property
-  def retrofit_scenario(self):
-    """
-    Get retrofit scenario
-    """
-    return self._retrofit_scenario
-
-  @property
-  def fuel_type(self):
-    """
-    Get fuel type (0: Electricity, 1: Gas)
-    """
-    return self._fuel_type
-
-  @property
-  def dictionary(self):
-    """
-    Get hub function to cost function dictionary
-    """
-    return self._dictionary

costs/constants.py

@@ -1,11 +0,0 @@
-# constants
-CURRENT_STATUS = 0
-SKIN_RETROFIT = 1
-SYSTEM_RETROFIT_AND_PV = 2
-SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV = 3
-RETROFITTING_SCENARIOS = [
-  CURRENT_STATUS,
-  SKIN_RETROFIT,
-  SYSTEM_RETROFIT_AND_PV,
-  SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV
-]

costs/cost.py

@@ -1,143 +0,0 @@
-"""
-Cost module
-"""
-import hub.helpers.dictionaries
-import pandas as pd
-import numpy_financial as npf
-from hub.city_model_structure.building import Building
-
-from costs.configuration import Configuration
-from costs import CapitalCosts, EndOfLifeCosts, TotalMaintenanceCosts, TotalOperationalCosts, TotalOperationalIncomes
-from costs.constants import CURRENT_STATUS
-
-
-class Cost:
-  """
-  Cost class
-  """
-
-  def __init__(self,
-               building: Building,
-               number_of_years=31,
-               percentage_credit=0,
-               interest_rate=0.04,
-               credit_years=15,
-               consumer_price_index=0.04,
-               electricity_peak_index=0.05,
-               electricity_price_index=0.05,
-               gas_price_index=0.05,
-               discount_rate=0.03,
-               retrofitting_year_construction=2020,
-               factories_handler='montreal_custom',
-               retrofit_scenario=CURRENT_STATUS,
-               dictionary=hub.helpers.dictionaries.Dictionaries().hub_function_to_montreal_custom_costs_function):
-    self._building = building
-    fuel_type = 0
-    if "gas" in building.energy_systems_archetype_name:
-      fuel_type = 1
-    self._configuration = Configuration(number_of_years,
-                                        percentage_credit,
-                                        interest_rate, credit_years,
-                                        consumer_price_index,
-                                        electricity_peak_index,
-                                        electricity_price_index,
-                                        gas_price_index,
-                                        discount_rate,
-                                        retrofitting_year_construction,
-                                        factories_handler,
-                                        retrofit_scenario,
-                                        fuel_type,
-                                        dictionary)
-
-  @property
-  def building(self) -> Building:
-    """
-    Get current building.
-    """
-    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)
-
-  @property
-  def life_cycle(self) -> pd.DataFrame:
-    """
-    Get complete life cycle costs
-    :return: DataFrame
-    """
-    results = pd.DataFrame()
-    global_capital_costs, global_capital_incomes = CapitalCosts(self._building, self._configuration).calculate()
-    global_end_of_life_costs = EndOfLifeCosts(self._building, self._configuration).calculate()
-    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'] +
-        global_capital_costs['B3010_opaque_roof'] +
-        global_capital_costs['B10_superstructure']
-    )
-    df_capital_costs_systems = (
-        global_capital_costs['D3020_heat_generating_systems'] +
-        global_capital_costs['D3030_cooling_generation_systems'] +
-        global_capital_costs['D3080_other_hvac_ahu'] +
-        global_capital_costs['D5020_lighting_and_branch_wiring'] +
-        global_capital_costs['D301010_photovoltaic_system']
-    )
-    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'] +
-        global_operational_costs['Fixed_costs_gas'] +
-        global_operational_costs['Variable_costs_gas']
-    )
-    df_maintenance_costs = (
-        global_maintenance_costs['Heating_maintenance'] +
-        global_maintenance_costs['Cooling_maintenance'] +
-        global_maintenance_costs['PV_maintenance']
-    )
-    df_operational_incomes = global_operational_incomes['Incomes electricity']
-    df_capital_incomes = (
-        global_capital_incomes['Subsidies construction'] +
-        global_capital_incomes['Subsidies HVAC'] +
-        global_capital_incomes['Subsidies PV']
-    )
-
-    life_cycle_costs_capital_skin = self._npv_from_list(df_capital_costs_skin.values.tolist())
-    life_cycle_costs_capital_systems = self._npv_from_list(df_capital_costs_systems.values.tolist())
-    life_cycle_costs_end_of_life_costs = self._npv_from_list(df_end_of_life_costs.values.tolist())
-    life_cycle_operational_costs = self._npv_from_list(df_operational_costs.values.tolist())
-    life_cycle_maintenance_costs = self._npv_from_list(df_maintenance_costs.values.tolist())
-    life_cycle_operational_incomes = self._npv_from_list(df_operational_incomes.values.tolist())
-    life_cycle_capital_incomes = self._npv_from_list(df_capital_incomes.values.tolist())
-
-    results[f'Scenario {self._configuration.retrofit_scenario}'] = [
-      life_cycle_costs_capital_skin,
-      life_cycle_costs_capital_systems,
-      life_cycle_costs_end_of_life_costs,
-      life_cycle_operational_costs,
-      life_cycle_maintenance_costs,
-      life_cycle_operational_incomes,
-      life_cycle_capital_incomes
-    ]
-
-    results.index = ['total_capital_costs_skin',
-                     'total_capital_costs_systems',
-                     'end_of_life_costs',
-                     'total_operational_costs',
-                     'total_maintenance_costs',
-                     'operational_incomes',
-                     'capital_incomes']
-
-    return results

costs/cost_base.py

@@ -1,38 +0,0 @@
-"""
-Cost base module
-"""
-
-from hub.city_model_structure.building import Building
-from hub.helpers.dictionaries import Dictionaries
-
-from costs.configuration import Configuration
-
-
-class CostBase:
-  """
-  Abstract base class for the costs
-  """
-  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
-    self._capital_costs_chapter = None
-    for archetype in self._configuration.costs_catalog.entries().archetypes:
-      if configuration.dictionary[str(building.function)] == str(archetype.function):
-        self._archetype = archetype
-        self._capital_costs_chapter = self._archetype.capital_cost
-        break
-    if not self._archetype:
-      raise KeyError(f'archetype not found for function {building.function}')
-
-    self._rng = range(configuration.number_of_years)
-
-  def calculate(self):
-    """
-    Raises not implemented exception
-    """
-    raise NotImplementedError()

costs/data/.gitignore

@@ -0,0 +1,4 @@
+# Ignore everything in this directory
+*
+# Except this file
+!.gitignore

costs/end_of_life_costs.py

@@ -1,34 +0,0 @@
-"""
-End of life costs module
-"""
-import math
-import pandas as pd
-from hub.city_model_structure.building import Building
-
-from costs.configuration import Configuration
-from costs.cost_base import CostBase
-
-
-class EndOfLifeCosts(CostBase):
-  """
-  End of life costs class
-  """
-  def __init__(self, building: Building, configuration: Configuration):
-    super().__init__(building, configuration)
-    self._yearly_end_of_life_costs = pd.DataFrame(index=self._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.py

@@ -0,0 +1,375 @@
+"""
+LifeCycleCosts module calculates the life cycle costs of one building
+SPDX - License - Identifier: LGPL - 3.0 - or -later
+Copyright © 2022 Project Author Pilar Monsalvete Alvarez de Uribarri pilar_monsalvete@concordia.ca
+Code contributor Oriol Gavalda Torrellas oriol.gavalda@concordia.ca
+"""
+
+import math
+
+import pandas as pd
+import numpy_financial as npf
+import hub.helpers.constants as cte
+from costs import SKIN_RETROFIT, SYSTEM_RETROFIT_AND_PV, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV, PERCENTAGE_CREDIT,INTEREST_RATE,CREDIT_YEARS
+
+
+class LifeCycleCosts:
+  """
+  Life cycle cost class
+  """
+
+  def __init__(self, building, archetype, number_of_years, consumer_price_index, electricity_peak_index,
+               electricity_price_index, gas_price_index, discount_rate,
+               retrofitting_scenario, fuel_type):
+    self._building = building
+    self._number_of_years = number_of_years
+    self._consumer_price_index = consumer_price_index
+    self._electricity_peak_index = electricity_peak_index
+    self._electricity_price_index = electricity_price_index
+    self._gas_price_index = gas_price_index
+    self._discount_rate = discount_rate
+    self._archetype = archetype
+    self._end_of_life_cost = 0
+    self._capital_costs_at_year_0 = 0
+    self._items = 0
+    self._fuels = 0
+    self._concepts = 0
+    self._retrofitting_scenario = retrofitting_scenario
+    self._total_floor_area = 0
+    self._fuel_type = fuel_type
+    for internal_zone in building.internal_zones:
+      for thermal_zone in internal_zone.thermal_zones:
+        self._total_floor_area += thermal_zone.total_floor_area
+
+    # todo: revise if it works
+    rng = range(number_of_years)
+    self._yearly_capital_costs = pd.DataFrame(index=rng, columns=['B2010_opaque_walls', 'B2020_transparent',
+                                                                  'B3010_opaque_roof', 'B10_superstructure',
+                                                                  'D301010_photovoltaic_system',
+                                                                  'D3020_heat_generating_systems',
+                                                                  'D3030_cooling_generation_systems',
+                                                                  'D3040_distribution_systems',
+                                                                  'D3080_other_hvac_ahu',
+                                                                  'D5020_lighting_and_branch_wiring'],
+                                              dtype='float')
+    self._yearly_end_of_life_costs = pd.DataFrame(index=rng, columns=['End_of_life_costs'], dtype='float')
+    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')
+    self._yearly_maintenance_costs = pd.DataFrame(index=rng, columns=['Heating_maintenance', 'Cooling_maintenance',
+                                                                      'PV_maintenance'], dtype='float')
+    self._yearly_operational_incomes = pd.DataFrame(index=rng, columns=['Incomes electricity'], dtype='float')
+
+    self._yearly_capital_incomes = pd.DataFrame(index=rng, columns=['Subsidies construction',
+                                                                    'Subsidies HVAC', 'Subsidies PV'], dtype='float')
+
+  def calculate_capital_costs(self):
+    """
+    Calculate capital cost
+    :return: pd.DataFrame
+    """
+    building = self._building
+    archetype = self._archetype
+
+    surface_opaque = 0
+    surface_transparent = 0
+    surface_roof = 0
+    surface_ground = 0
+    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
+
+    total_floor_area = self._total_floor_area
+
+    for internal_zone in building.internal_zones:
+      for thermal_zone in internal_zone.thermal_zones:
+        for thermal_boundary in thermal_zone.thermal_boundaries:
+          if thermal_boundary.type == 'Ground':
+            surface_ground += thermal_boundary.opaque_area
+          elif thermal_boundary.type == 'Roof':
+            surface_roof += thermal_boundary.opaque_area
+          elif thermal_boundary.type == 'Wall':
+            surface_opaque += thermal_boundary.opaque_area * (1 - thermal_boundary.window_ratio)
+            surface_transparent += thermal_boundary.opaque_area * thermal_boundary.window_ratio
+
+    chapters = archetype.capital_cost
+    peak_heating = building.heating_peak_load[cte.YEAR][0]/1000
+    peak_cooling = building.cooling_peak_load[cte.YEAR][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 = surface_opaque * chapter.item('B2010_opaque_walls').refurbishment[0]
+      capital_cost_transparent = surface_transparent * chapter.item('B2020_transparent').refurbishment[0]
+      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 * (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 = total_floor_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 = 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 (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
+
+  def calculate_end_of_life_costs(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._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'] = 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
+
+  def calculate_total_floor_area(self):
+    total_floor_area = self._total_floor_area
+    return total_floor_area
+  @property
+  def calculate_total_operational_costs(self):
+    """
+    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._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
+    )
+    print(f'electricity consumption {total_electricity_consumption}')
+
+    # todo: change when peak electricity demand is coded. Careful with factor residential
+    peak_electricity_demand = 0.1*total_floor_area # 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
+
+  def calculate_total_operational_incomes(self, retrofitting_scenario):
+    """
+    Calculate total operational incomes
+    :return: pd.DataFrame
+    """
+    building = self._building
+    if cte.YEAR not in building.onsite_electrical_production:
+      onsite_electricity_production = 0
+    else:
+      if retrofitting_scenario == 0 or retrofitting_scenario == 1:
+        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
+
+  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][0]/1000
+    peak_cooling = building.heating_peak_load[cte.YEAR][0]/1000
+
+    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/outputs/.gitignore

@@ -0,0 +1,4 @@
+# Ignore everything in this directory
+*
+# Except this file
+!.gitignore

costs/printing_results.py

@@ -0,0 +1,58 @@
+import plotly.graph_objects as go
+import matplotlib.pyplot as plt
+import plotly.express as px
+
+
+def printing_results(investmentcosts, life_cycle_results,total_floor_area):
+
+  labels = investmentcosts.index
+  values = investmentcosts['retrofitting_scenario_1']
+  values2 = investmentcosts['retrofitting_scenario_2']
+  values3 = investmentcosts['retrofitting_scenario_3']
+
+  fig = go.Figure(data=[go.Pie(labels=labels, values=values)])
+  fig2 = go.Figure(data=[go.Pie(labels=labels, values=values2)])
+  fig3 = go.Figure(data=[go.Pie(labels=labels, values=values3)])
+  # Set the layout properties
+  fig.update_layout(
+    title='Retrofitting scenario 1',
+    showlegend=True
+  )
+  fig2.update_layout(
+    title='Retrofitting scenario 2',
+    showlegend=True
+  )
+  fig3.update_layout(
+    title='Retrofitting scenario 3',
+    showlegend=True
+  )
+
+  # Display the chart
+  fig.show()
+  fig2.show()
+  fig3.show()
+
+  df = life_cycle_results / total_floor_area
+
+  # Transpose the DataFrame (swap columns and rows)
+  df_swapped = df.transpose()
+
+  # Reset the index to make the current index a regular column
+  df_swapped = df_swapped.reset_index()
+
+  # Assign new column names
+  df_swapped.columns = ['Scenarios', 'total_capital_costs_skin',
+                        'total_capital_costs_systems',
+                        'end_of_life_costs',
+                        'total_operational_costs',
+                        'total_maintenance_costs',
+                        'operational_incomes',
+                        'capital_incomes']
+
+  df_swapped.index = df_swapped['Scenarios']
+  df_swapped = df_swapped.drop('Scenarios', axis=1)
+  print(df_swapped)
+  fig = px.bar(df_swapped, title='Life Cycle Costs for buildings')
+  fig.show()
+  # Display the chart
+  plt.show()

costs/tmp/.gitignore

@@ -0,0 +1,4 @@
+# Ignore everything in this directory
+*
+# Except this file
+!.gitignore

costs/total_maintenance_costs.py

@@ -1,61 +0,0 @@
-"""
-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 costs.configuration import Configuration
-from costs.cost_base import CostBase
-
-
-class TotalMaintenanceCosts(CostBase):
-  """
-  Total maintenance costs class
-  """
-  def __init__(self, building: Building, configuration: Configuration):
-    super().__init__(building, configuration)
-    self._yearly_maintenance_costs = pd.DataFrame(
-      index=self._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][0]
-    peak_cooling = building.cooling_peak_load[cte.YEAR][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

@@ -1,92 +0,0 @@
-"""
-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 costs.configuration import Configuration
-from costs.cost_base import CostBase
-
-
-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(
-      index=self._rng,
-      columns=[
-        'Fixed_costs_electricity_peak',
-        'Fixed_costs_electricity_monthly',
-        'Variable_costs_electricity',
-        'Fixed_costs_gas',
-        'Variable_costs_gas'
-      ],
-      dtype='float'
-    )
-
-  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.iloc[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

@@ -1,41 +0,0 @@
-"""
-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 costs.configuration import Configuration
-from costs.cost_base import CostBase
-
-
-class TotalOperationalIncomes(CostBase):
-  """
-  Total operational incomes class
-  """
-  def __init__(self, building: Building, configuration: Configuration):
-    super().__init__(building, configuration)
-    self._yearly_operational_incomes = pd.DataFrame(index=self._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

costs/version.py

@@ -1,4 +0,0 @@
-"""
-Cost version number
-"""
-__version__ = '0.1.0.0'

input_files/summerschool_one_building.geojson

@@ -0,0 +1,294 @@
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+        "citygml_re": " ",
+        "citygml__3": " ",
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+        "citygml__4": " ",
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+        "citygml__5": " ",
+        "citygml_us": " ",
+        "citygml__6": " ",
+        "citygml_ye": " ",
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+        "citygml_ro": " ",
+        "citygml__8": " ",
+        "citygml_me": 19.113,
+        "citygml__9": "#m",
+        "citygml_st": " ",
+        "citygml_10": " ",
+        "citygml_11": " ",
+        "citygml_12": " ",
+        "citygml_13": " ",
+        "citygml_14": " ",
+        "citygml_ou": " ",
+        "citygml_in": " ",
+        "citygml_bo": " ",
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+        "citygml_15": " ",
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+        "citygml_ad": " ",
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+        "citygml_17": "boundedBy",
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+        "citygml_71": " ",
+        "citygml_72": " ",
+        "citygml_73": " ",
+        "Area_1": 191.404,
+        "cityGML_hi": 0,
+        "Z_Min": 46.1162,
+        "Z_Max": 64.399,
+        "Shape_Leng": 63.6906066955,
+        "ID_UEV": "01036804",
+        "CIVIQUE_DE": " 2170",
+        "CIVIQUE_FI": " 2170",
+        "NOM_RUE": "rue Bishop  (MTL)",
+        "MUNICIPALI": 50,
+        "ETAGE_HORS": 3,
+        "NOMBRE_LOG": 1,
+        "ANNEE_CONS": 1900,
+        "CODE_UTILI": 6000,
+        "LIBELLE_UT": "Immeuble à bureaux",
+        "CATEGORIE_": "Régulier",
+        "MATRICULE8": "9839-57-7770-3-000-0000",
+        "SUPERFICIE": 259,
+        "SUPERFIC_1": 490,
+        "NO_ARROND_": "REM19",
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+        "Z_Min_1": null,
+        "Z_Max_1": null,
+        "Shape_Length": 63.69060669550123,
+        "Shape_Area": 174.69050030775531
+      }
+    }
+  ]
+}

out_files/.gitignore

@@ -0,0 +1,4 @@
+# Ignore everything in this directory
+.gitignore
+# Except this file
+!.gitignore

pyproject.toml

@@ -1,8 +0,0 @@
-# pyproject.toml
-
-[build-system]
-requires = ["setuptools>=61.0.0", "wheel"]
-build-backend = "setuptools.build_meta"
-
-[options.packages.find_namespace]
-where = "costs"

resources.txt

@@ -1,3 +1,2 @@
 numpy_financial
 cerc_hub
-pandas

setup.py

@@ -1,36 +0,0 @@
-import glob
-import pathlib
-from distutils.util import convert_path
-from setuptools import setup
-
-with pathlib.Path('requirements.txt').open() as r:
-  install_requires = [
-    str(requirement).replace('\n', '')
-    for requirement
-    in r.readlines()
-  ]
-install_requires.append('setuptools')
-
-main_ns = {}
-version = convert_path('costs/version.py')
-with open(version) as f:
-  exec(f.read(), main_ns)
-
-setup(
-  name='cerc-costs',
-  version=main_ns['__version__'],
-  description="CERC costs contains the basic cost calculation per CERC-Hub building",
-  long_description="CERC costs contains the basic cost calculation per CERC-Hub building",
-  classifiers=[
-    "License :: OSI Approved :: GNU Library or Lesser General Public License (LGPL)",
-    "Programming Language :: Python",
-    "Programming Language :: Python :: 3",
-  ],
-  include_package_data=True,
-  packages=['costs'],
-  setup_requires=install_requires,
-  install_requires=install_requires,
-  data_files=[
-    ('costs', glob.glob('requirements.txt'))
-  ]
-)

tests/output/.gitignore

@@ -1,2 +0,0 @@
-*
-!.gitignore

tests/unit_tests.py

@@ -1,73 +0,0 @@
-import glob
-import os
-import subprocess
-import unittest
-
-from pathlib import Path
-
-from hub.exports.energy_building_exports_factory import EnergyBuildingsExportsFactory
-from hub.exports.exports_factory import ExportsFactory
-from hub.imports.construction_factory import ConstructionFactory
-from hub.imports.energy_systems_factory import EnergySystemsFactory
-from hub.imports.geometry_factory import GeometryFactory
-from hub.imports.results_factory import ResultFactory
-from hub.imports.usage_factory import UsageFactory
-from hub.helpers.dictionaries import Dictionaries
-
-from costs.cost import Cost
-from costs.constants import SKIN_RETROFIT, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV, SYSTEM_RETROFIT_AND_PV
-
-
-class UnitTests(unittest.TestCase):
-  def setUp(self) -> None:
-    city_file = Path("./tests/data/test.geojson").resolve()
-    output_path = Path('./tests/output/').resolve()
-    city = GeometryFactory('geojson',
-                           city_file,
-                           height_field='citygml_me',
-                           year_of_construction_field='ANNEE_CONS',
-                           function_field='CODE_UTILI',
-                           function_to_hub=Dictionaries().montreal_function_to_hub_function).city
-    ConstructionFactory('nrcan', city).enrich()
-    UsageFactory('nrcan', city).enrich()
-    ExportsFactory('sra', city, output_path).export()
-    sra_file = str((output_path / f'{city.name}_sra.xml').resolve())
-    subprocess.run(['/usr/local/bin/sra', sra_file])
-    ResultFactory('sra', city, output_path).enrich()
-
-    for building in city.buildings:
-      building.energy_systems_archetype_name = 'system 1 gas pv'
-    EnergySystemsFactory('montreal_custom', city).enrich()
-    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)
-    ResultFactory('insel_monthly_energy_balance', city, output_path).enrich()
-    self._city = city
-
-  def test_current_status(self):
-    for building in self._city.buildings:
-      result = Cost(building).life_cycle
-      self.assertIsNotNone(result)
-      self.assertEqual(0, result.values[0])
-
-  def test_scenario_1(self):
-    for building in self._city.buildings:
-      result = Cost(building, retrofit_scenario=SKIN_RETROFIT).life_cycle
-      self.assertIsNotNone(result)
-
-  def test_scenario_2(self):
-    for building in self._city.buildings:
-      result = Cost(building, retrofit_scenario=SYSTEM_RETROFIT_AND_PV).life_cycle
-      self.assertIsNotNone(result)
-      self.assertEqual(0, result.values[0])
-
-  def test_scenario_3(self):
-    for building in self._city.buildings:
-      result = Cost(building, retrofit_scenario=SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV).life_cycle
-      self.assertIsNotNone(result)
-
-  def tearDown(self):
-    files = glob.glob('output/[!.]*')
-    for file in files:
-      os.unlink(file)