complete refactor
This commit is contained in:
parent
d066f2ce17
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@ -1,3 +1,3 @@
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# costs_workflow
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This workflow is a test to check that the proccess of calculating costs is correct before creating the API.
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This workflow is a test to check that the process of calculating costs is correct before creating the API.
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@ -4,6 +4,12 @@ Cost workflow initialization
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import glob
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import os
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from pathlib import Path
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from .capital_costs import CapitalCosts
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from .end_of_life_costs import EndOfLifeCosts
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from .total_maintenance_costs import TotalMaintenanceCosts
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from .total_operational_costs import TotalOperationalCosts
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from .total_operational_incomes import TotalOperationalIncomes
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# to remove
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204
costs/cost.py
204
costs/cost.py
@ -2,10 +2,12 @@
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Cost module
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"""
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import pandas as pd
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from hub.city_model_structure.city import City
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import numpy_financial as npf
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from hub.city_model_structure.building import Building
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from configuration import Configuration
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from capital_costs import LifeCycleCosts
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from costs import CapitalCosts, EndOfLifeCosts, TotalMaintenanceCosts, TotalOperationalCosts, TotalOperationalIncomes
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from costs import CURRENT_STATUS
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class Cost:
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@ -14,7 +16,7 @@ class Cost:
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"""
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def __init__(self,
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city: City,
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building: Building,
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number_of_years=31,
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percentage_credit=0,
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interest_rate=0.04,
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@ -25,8 +27,12 @@ class Cost:
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gas_price_index=0.05,
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discount_rate=0.03,
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retrofitting_year_construction=2020,
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factories_handler='montreal_custom'):
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self._city = city
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factories_handler='montreal_custom',
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retrofit_scenario=CURRENT_STATUS):
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self._building = building
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fuel_type = 0
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if "gas" in building.energy_systems_archetype_name:
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fuel_type = 1
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self._configuration = Configuration(number_of_years,
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percentage_credit,
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interest_rate, credit_years,
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@ -36,7 +42,12 @@ class Cost:
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gas_price_index,
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discount_rate,
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retrofitting_year_construction,
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factories_handler)
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factories_handler,
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retrofit_scenario,
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fuel_type)
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def _npv_from_list(self, list_cashflow):
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return npf.npv(self._configuration.discount_rate, list_cashflow)
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@property
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def life_cycle(self) -> pd.DataFrame:
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@ -45,118 +56,73 @@ class Cost:
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:return: DataFrame
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"""
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results = pd.DataFrame()
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for building in self._city.buildings:
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lcc = LifeCycleCosts(building, self._configuration)
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global_capital_costs, global_capital_incomes = lcc.calculate_capital_costs()
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global_end_of_life_costs = lcc.calculate_end_of_life_costs()
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global_operational_costs = lcc.calculate_total_operational_costs
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global_maintenance_costs = lcc.calculate_total_maintenance_costs()
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global_operational_incomes = lcc.calculate_total_operational_incomes()
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results[f'Scenario {retrofitting_scenario}'] = [life_cycle_costs_capital_skin,
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life_cycle_costs_capital_systems,
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life_cycle_costs_end_of_life_costs,
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life_cycle_operational_costs,
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life_cycle_maintenance_costs,
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life_cycle_operational_incomes,
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life_cycle_capital_incomes]
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global_capital_costs, global_capital_incomes = CapitalCosts(self._building, self._configuration).calculate()
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global_end_of_life_costs = EndOfLifeCosts(self._building, self._configuration).calculate()
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global_operational_costs = TotalOperationalCosts(self._building, self._configuration).calculate()
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global_maintenance_costs = TotalMaintenanceCosts(self._building, self._configuration).calculate()
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global_operational_incomes = TotalOperationalIncomes(self._building, self._configuration).calculate()
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df_capital_costs_skin = (
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global_capital_costs['B2010_opaque_walls'] +
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global_capital_costs['B2020_transparent'] +
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global_capital_costs['B3010_opaque_roof'] +
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global_capital_costs['B10_superstructure']
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)
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df_capital_costs_systems = (
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global_capital_costs['D3020_heat_generating_systems'] +
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global_capital_costs['D3030_cooling_generation_systems'] +
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global_capital_costs['D3080_other_hvac_ahu'] +
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global_capital_costs['D5020_lighting_and_branch_wiring'] +
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global_capital_costs['D301010_photovoltaic_system']
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)
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df_end_of_life_costs = global_end_of_life_costs['End_of_life_costs']
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df_operational_costs = (
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global_operational_costs['Fixed_costs_electricity_peak'] +
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global_operational_costs['Fixed_costs_electricity_monthly'] +
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global_operational_costs['Fixed_costs_electricity_peak'] +
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global_operational_costs['Fixed_costs_electricity_monthly'] +
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global_operational_costs['Variable_costs_electricity'] +
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global_operational_costs['Fixed_costs_gas'] +
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global_operational_costs['Variable_costs_gas']
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)
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df_maintenance_costs = (
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global_maintenance_costs['Heating_maintenance'] +
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global_maintenance_costs['Cooling_maintenance'] +
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global_maintenance_costs['PV_maintenance']
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)
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df_operational_incomes = global_operational_incomes['Incomes electricity']
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df_capital_incomes = (
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global_capital_incomes['Subsidies construction'] +
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global_capital_incomes['Subsidies HVAC'] +
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global_capital_incomes['Subsidies PV']
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)
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life_cycle_costs_capital_skin = Cost._npv_from_list(
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self._configuration.discount_rate, df_capital_costs_skin.values.tolist()
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)
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life_cycle_costs_capital_systems = self._npv_from_list(df_capital_costs_systems.values.tolist())
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life_cycle_costs_end_of_life_costs = self._npv_from_list(df_end_of_life_costs.values.tolist())
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life_cycle_operational_costs = self._npv_from_list(df_operational_costs.values.tolist())
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life_cycle_maintenance_costs = self._npv_from_list(df_maintenance_costs.values.tolist())
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life_cycle_operational_incomes = self._npv_from_list(df_operational_incomes.values.tolist())
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life_cycle_capital_incomes = self._npv_from_list(df_capital_incomes.values.tolist())
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results[f'Scenario {self._configuration.retrofit_scenario}'] = [
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life_cycle_costs_capital_skin,
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life_cycle_costs_capital_systems,
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life_cycle_costs_end_of_life_costs,
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life_cycle_operational_costs,
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life_cycle_maintenance_costs,
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life_cycle_operational_incomes,
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life_cycle_capital_incomes
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]
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results.index = ['total_capital_costs_skin',
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'total_capital_costs_systems',
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'end_of_life_costs',
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'total_operational_costs',
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'total_maintenance_costs',
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'operational_incomes',
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'capital_incomes']
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life_cycle_results.index = ['total_capital_costs_skin',
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'total_capital_costs_systems',
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'end_of_life_costs',
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'total_operational_costs',
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'total_maintenance_costs',
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'operational_incomes',
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'capital_incomes']
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return results
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"""
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if "gas" in building.energy_systems_archetype_name:
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FUEL_TYPE = 1
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else:
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FUEL_TYPE = 0
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full_path_output = Path(out_path / f'output {retrofitting_scenario} {building.name}.xlsx').resolve()
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with pd.ExcelWriter(full_path_output) as writer:
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global_capital_costs.to_excel(writer, sheet_name='global_capital_costs')
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global_end_of_life_costs.to_excel(writer, sheet_name='global_end_of_life_costs')
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global_operational_costs.to_excel(writer, sheet_name='global_operational_costs')
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global_maintenance_costs.to_excel(writer, sheet_name='global_maintenance_costs')
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global_operational_incomes.to_excel(writer, sheet_name='global_operational_incomes')
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global_capital_incomes.to_excel(writer, sheet_name='global_capital_incomes')
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df_capital_costs_skin = (
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global_capital_costs['B2010_opaque_walls'] + global_capital_costs['B2020_transparent'] +
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global_capital_costs['B3010_opaque_roof'] + global_capital_costs['B10_superstructure']
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)
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df_capital_costs_systems = (
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global_capital_costs['D3020_heat_generating_systems'] +
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global_capital_costs['D3030_cooling_generation_systems'] +
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global_capital_costs['D3080_other_hvac_ahu'] +
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global_capital_costs['D5020_lighting_and_branch_wiring'] +
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global_capital_costs['D301010_photovoltaic_system']
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)
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df_end_of_life_costs = global_end_of_life_costs['End_of_life_costs']
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df_operational_costs = (
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global_operational_costs['Fixed_costs_electricity_peak'] +
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global_operational_costs['Fixed_costs_electricity_monthly'] +
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global_operational_costs['Fixed_costs_electricity_peak'] +
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global_operational_costs['Fixed_costs_electricity_monthly'] +
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global_operational_costs['Variable_costs_electricity'] +
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global_operational_costs['Fixed_costs_gas'] +
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global_operational_costs['Variable_costs_gas']
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)
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df_maintenance_costs = (
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global_maintenance_costs['Heating_maintenance'] +
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global_maintenance_costs['Cooling_maintenance'] +
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global_maintenance_costs['PV_maintenance']
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)
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df_operational_incomes = global_operational_incomes['Incomes electricity']
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df_capital_incomes = (
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global_capital_incomes['Subsidies construction'] +
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global_capital_incomes['Subsidies HVAC'] +
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global_capital_incomes['Subsidies PV']
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)
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life_cycle_costs_capital_skin = npf.npv(self._discount_rate, list_cashflow)_npv_from_list(, df_capital_costs_skin.values.tolist())
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life_cycle_costs_capital_systems = _npv_from_list(DISCOUNT_RATE, df_capital_costs_systems.values.tolist())
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life_cycle_costs_end_of_life_costs = _npv_from_list(DISCOUNT_RATE, df_end_of_life_costs.values.tolist())
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life_cycle_operational_costs = _npv_from_list(DISCOUNT_RATE, df_operational_costs.values.tolist())
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life_cycle_maintenance_costs = _npv_from_list(DISCOUNT_RATE, df_maintenance_costs.values.tolist())
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life_cycle_operational_incomes = _npv_from_list(DISCOUNT_RATE, df_operational_incomes.values.tolist())
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life_cycle_capital_incomes = _npv_from_list(DISCOUNT_RATE, df_capital_incomes.values.tolist())
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life_cycle_costs = (
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life_cycle_costs_capital_skin +
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life_cycle_costs_capital_systems +
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life_cycle_costs_end_of_life_costs +
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life_cycle_operational_costs +
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life_cycle_maintenance_costs -
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life_cycle_operational_incomes -
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life_cycle_capital_incomes
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)
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life_cycle_results[f'Scenario {retrofitting_scenario}'] = [life_cycle_costs_capital_skin,
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life_cycle_costs_capital_systems,
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life_cycle_costs_end_of_life_costs,
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life_cycle_operational_costs,
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life_cycle_maintenance_costs,
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life_cycle_operational_incomes,
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life_cycle_capital_incomes]
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life_cycle_results.index = ['total_capital_costs_skin',
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'total_capital_costs_systems',
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'end_of_life_costs',
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'total_operational_costs',
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'total_maintenance_costs',
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'operational_incomes',
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'capital_incomes']
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print(life_cycle_results)
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print(f'Scenario {retrofitting_scenario} {life_cycle_costs}')
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return results
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"""
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@ -1,371 +0,0 @@
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"""
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LifeCycleCosts module calculates the life cycle costs of one building
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SPDX - License - Identifier: LGPL - 3.0 - or -later
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Copyright © 2022 Project Author Pilar Monsalvete Alvarez de Uribarri pilar_monsalvete@concordia.ca
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Code contributor Oriol Gavalda Torrellas oriol.gavalda@concordia.ca
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"""
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import math
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import pandas as pd
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import numpy_financial as npf
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import hub.helpers.constants as cte
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from costs import SKIN_RETROFIT, SYSTEM_RETROFIT_AND_PV, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV, PERCENTAGE_CREDIT,INTEREST_RATE,CREDIT_YEARS
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class LifeCycleCosts:
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"""
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Life cycle cost class
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"""
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def __init__(self, building, archetype, number_of_years, consumer_price_index, electricity_peak_index,
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electricity_price_index, gas_price_index, discount_rate,
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retrofitting_scenario, fuel_type):
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self._building = building
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self._number_of_years = number_of_years
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self._consumer_price_index = consumer_price_index
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self._electricity_peak_index = electricity_peak_index
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self._electricity_price_index = electricity_price_index
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self._gas_price_index = gas_price_index
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self._discount_rate = discount_rate
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self._archetype = archetype
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self._end_of_life_cost = 0
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self._capital_costs_at_year_0 = 0
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self._items = 0
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self._fuels = 0
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self._concepts = 0
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self._retrofitting_scenario = retrofitting_scenario
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self._total_floor_area = 0
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self._fuel_type = fuel_type
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for internal_zone in building.internal_zones:
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for thermal_zone in internal_zone.thermal_zones:
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self._total_floor_area += thermal_zone.total_floor_area
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# todo: revise if it works
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rng = range(number_of_years)
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self._yearly_capital_costs = pd.DataFrame(index=rng, columns=['B2010_opaque_walls', 'B2020_transparent',
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'B3010_opaque_roof', 'B10_superstructure',
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'D301010_photovoltaic_system',
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'D3020_heat_generating_systems',
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'D3030_cooling_generation_systems',
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'D3040_distribution_systems',
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'D3080_other_hvac_ahu',
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'D5020_lighting_and_branch_wiring'],
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dtype='float')
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self._yearly_end_of_life_costs = pd.DataFrame(index=rng, columns=['End_of_life_costs'], dtype='float')
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self._yearly_operational_costs = pd.DataFrame(index=rng, columns=['Fixed_costs_electricity_peak',
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'Fixed_costs_electricity_monthly',
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'Variable_costs_electricity', 'Fixed_costs_gas',
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'Variable_costs_gas'],
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dtype='float')
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self._yearly_maintenance_costs = pd.DataFrame(index=rng, columns=['Heating_maintenance', 'Cooling_maintenance',
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'PV_maintenance'], dtype='float')
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self._yearly_operational_incomes = pd.DataFrame(index=rng, columns=['Incomes electricity'], dtype='float')
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self._yearly_capital_incomes = pd.DataFrame(index=rng, columns=['Subsidies construction',
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'Subsidies HVAC', 'Subsidies PV'], dtype='float')
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def calculate_capital_costs(self):
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"""
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Calculate capital cost
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:return: pd.DataFrame
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"""
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building = self._building
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archetype = self._archetype
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surface_opaque = 0
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surface_transparent = 0
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surface_roof = 0
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surface_ground = 0
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capital_cost_pv = 0
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capital_cost_opaque = 0
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capital_cost_ground = 0
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capital_cost_transparent = 0
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capital_cost_roof = 0
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capital_cost_heating_equipment = 0
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capital_cost_cooling_equipment = 0
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capital_cost_distribution_equipment = 0
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capital_cost_other_hvac_ahu = 0
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capital_cost_lighting = 0
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total_floor_area = self._total_floor_area
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for internal_zone in building.internal_zones:
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for thermal_zone in internal_zone.thermal_zones:
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for thermal_boundary in thermal_zone.thermal_boundaries:
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if thermal_boundary.type == 'Ground':
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surface_ground += thermal_boundary.opaque_area
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elif thermal_boundary.type == 'Roof':
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surface_roof += thermal_boundary.opaque_area
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elif thermal_boundary.type == 'Wall':
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surface_opaque += thermal_boundary.opaque_area * (1 - thermal_boundary.window_ratio)
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surface_transparent += thermal_boundary.opaque_area * thermal_boundary.window_ratio
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chapters = archetype.capital_cost
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peak_heating = building.heating_peak_load[cte.YEAR].values[0]/1000
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peak_cooling = building.cooling_peak_load[cte.YEAR].values[0]/1000
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# todo: change area pv when the variable exists
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roof_area = 0
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for roof in building.roofs:
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roof_area += roof.solid_polygon.area
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surface_pv = roof_area * 0.5
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self._yearly_capital_costs.loc[0, 'B2010_opaque_walls'] = 0
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self._yearly_capital_costs.loc[0]['B2020_transparent'] = 0
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self._yearly_capital_costs.loc[0, 'B3010_opaque_roof'] = 0
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self._yearly_capital_costs.loc[0]['B10_superstructure'] = 0
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self._yearly_capital_costs.loc[0, 'D3020_heat_generating_systems'] = 0
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self._yearly_capital_costs.loc[0, 'D3030_cooling_generation_systems'] = 0
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self._yearly_capital_costs.loc[0, 'D3040_distribution_systems'] = 0
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self._yearly_capital_costs.loc[0, 'D3080_other_hvac_ahu'] = 0
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self._yearly_capital_costs.loc[0, 'D5020_lighting_and_branch_wiring'] = 0
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self._yearly_capital_incomes.loc[0, 'Subsidies construction'] = 0
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self._yearly_capital_incomes.loc[0, 'Subsidies HVAC'] = 0
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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
|
||||
|
||||
@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
|
||||
)
|
||||
|
||||
# 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
|
||||
|
||||
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
|
||||
|
||||
___________________________________________________________
|
||||
|
||||
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
|
||||
@ -43,7 +43,6 @@ class TotalOperationalCosts:
|
||||
dtype='float'
|
||||
)
|
||||
|
||||
@property
|
||||
def calculate(self) -> pd.DataFrame:
|
||||
"""
|
||||
Calculate total operational costs
|
||||
@ -105,5 +104,4 @@ class TotalOperationalCosts:
|
||||
variable_gas_cost_year_0 * price_increase_peak_electricity
|
||||
)
|
||||
self._yearly_operational_costs.fillna(0, inplace=True)
|
||||
|
||||
return self._yearly_operational_costs
|
||||
|
||||
Loading…
Reference in New Issue
Block a user