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ca002926f7 Empty-Commit 2023-07-18 16:45:04 -04:00
f4fafa1afa Empty-Commit 2023-07-18 16:06:29 -04:00
91fd120807 Test 2023-07-18 16:06:18 -04:00
569729df59 Test 2023-07-18 15:54:31 -04:00
5aadf2ff50 Remove trailing space 2023-07-18 15:35:44 -04:00
134293f6e3 test 2023-07-18 15:30:34 -04:00
da89983ca9 Empty-Commit 2023-07-18 13:22:32 -04:00
c052690c08 Empty-Commit 2023-07-18 13:21:57 -04:00
7f2084c9c7 Empty-Commit 2023-07-18 13:16:38 -04:00
69f14da4c3 Empty-Commit 2023-07-18 13:14:59 -04:00
44559bcf00 Empty-Commit 2023-07-18 12:28:57 -04:00
bde6ff90f5 Empty-Commit 2023-07-18 12:27:29 -04:00
a6381141e0 Empty-Commit 2023-07-18 12:19:43 -04:00
3f152e00e3 Empty-Commit 2023-07-18 12:16:38 -04:00
fd3afe5b2d Empty-Commit 2023-07-18 12:16:05 -04:00
8c094244de Empty-Commit 2023-07-18 12:12:11 -04:00
b6cbfc0c06 Empty-Commit 2023-07-18 12:11:13 -04:00
e470aafd80 Empty-Commit 2023-07-18 12:01:28 -04:00
037b6915dd Empty-Commit 2023-07-18 11:58:28 -04:00
8053de22b3 Empty-Commit 2023-07-18 11:50:46 -04:00
064cdf600f Empty-Commit 2023-07-18 11:49:28 -04:00
75127e6b36 Empty-Commit 2023-07-18 11:46:29 -04:00
f8bf442ae1 Empty-Commit 2023-07-18 11:45:23 -04:00
538b82d413 Empty-Commit 2023-07-18 11:44:15 -04:00
746def3dfa Empty-Commit 2023-07-18 11:37:03 -04:00
8733108c52 Empty-Commit 2023-07-18 11:34:19 -04:00
4381b1e4c7 Empty-Commit 2023-07-18 11:33:11 -04:00
e7cf14b8ca Empty-Commit 2023-07-18 11:23:54 -04:00
d311b7292e Empty-Commit 2023-07-18 11:16:35 -04:00
dc0e0dcfcf Empty-Commit 2023-07-18 11:14:55 -04:00
746788b60c Empty-Commit 2023-07-18 11:10:28 -04:00
8deb92480b test web_hook 2023-07-18 11:05:29 -04:00
61b9780140 correct typo 2023-07-18 10:01:15 -04:00
334288ed87 improve unit tests 2023-07-18 09:48:44 -04:00
2e809601fc Add unit tests 2023-07-18 09:44:05 -04:00
24546a08d4 Bug fixing in packet 2023-07-17 16:36:39 -04:00
6941484d59 Bug fixing in packet 2023-07-17 15:35:21 -04:00
d3bdf3d485 Bugfixing in packet 2023-07-17 15:18:32 -04:00
890171dc3a Bugfixing in packet 2023-07-17 14:35:12 -04:00
a07f368047 Create wheel package 2023-07-17 11:24:12 -04:00
93d670167d complete refactor 2023-07-14 16:39:47 -04:00
3816e0ba80 complete refactor 2023-07-14 16:18:33 -04:00
d066f2ce17 partial refactor 2023-07-14 15:37:12 -04:00
d597ec41af partial refactor 2023-07-13 13:06:23 -04:00
df45fc056c partial refactor 2023-07-13 11:22:13 -04:00
43eb91c889 partial refactor 2023-06-01 14:07:41 -04:00
23 changed files with 1015 additions and 615 deletions

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

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@ -1,45 +1,9 @@
"""
Cost workflow initialization
"""
import glob
import os
from pathlib import Path
from .capital_costs import CapitalCosts
from .end_of_life_costs import EndOfLifeCosts
from .total_maintenance_costs import TotalMaintenanceCosts
from .total_operational_costs import TotalOperationalCosts
from .total_operational_incomes import TotalOperationalIncomes
# 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
]
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)

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@ -4,193 +4,3 @@ 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 energy_systems_sizing import EnergySystemsSizing
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 life_cycle_costs import LifeCycleCosts
# import constants
from costs import CLIMATE_REFERENCE_CITY, WEATHER_FILE, WEATHER_FORMAT, CONSTRUCTION_FORMAT, USAGE_FORMAT
from costs import ENERGY_SYSTEM_FORMAT, ATTIC_HEATED_CASE, BASEMENT_HEATED_CASE, 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 costs import file_path, tmp_folder, out_path
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()
print('[city creation start]')
city = GeometryFactory('geojson',
path=file_path,
height_field='heightmax',
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, file_name=WEATHER_FILE).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'
EnergySystemsFactory(ENERGY_SYSTEM_FORMAT, city).enrich()
print('enrich systems... done')
print('exporting:')
catalog = CostCatalogFactory('montreal_custom').catalog
print('costs catalog access... done')
sra_file = (tmp_folder / f'{city.name}_sra.xml').resolve()
SraEngine(city, sra_file, tmp_folder, WEATHER_FILE)
print(' sra processed...')
for building in city.buildings:
building.attic_heated = ATTIC_HEATED_CASE
building.basement_heated = BASEMENT_HEATED_CASE
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)
EnergySystemsSizing(city).enrich()
print(f'beginning costing scenario {retrofitting_scenario} systems... done')
for building in city.buildings:
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()
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')
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
)
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(life_cycle_results)
print(f'Scenario {retrofitting_scenario} {life_cycle_costs}')

236
costs/capital_costs.py Normal file
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@ -0,0 +1,236 @@
"""
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

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costs/configuration.py Normal file
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"""
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

11
costs/constants.py Normal file
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# 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
]

143
costs/cost.py Normal file
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"""
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

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costs/cost_base.py Normal file
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"""
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()

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# Ignore everything in this directory
*
# Except this file
!.gitignore

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"""
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

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@ -1,369 +0,0 @@
"""
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].values[0]/1000
peak_cooling = building.cooling_peak_load[cte.YEAR].values[0]/1000
# todo: change area pv when the variable exists
roof_area = 0
for roof in building.roofs:
roof_area += roof.solid_polygon.area
surface_pv = roof_area * 0.5
self._yearly_capital_costs.loc[0, 'B2010_opaque_walls'] = 0
self._yearly_capital_costs.loc[0]['B2020_transparent'] = 0
self._yearly_capital_costs.loc[0, 'B3010_opaque_roof'] = 0
self._yearly_capital_costs.loc[0]['B10_superstructure'] = 0
self._yearly_capital_costs.loc[0, 'D3020_heat_generating_systems'] = 0
self._yearly_capital_costs.loc[0, 'D3030_cooling_generation_systems'] = 0
self._yearly_capital_costs.loc[0, 'D3040_distribution_systems'] = 0
self._yearly_capital_costs.loc[0, 'D3080_other_hvac_ahu'] = 0
self._yearly_capital_costs.loc[0, 'D5020_lighting_and_branch_wiring'] = 0
self._yearly_capital_incomes.loc[0, 'Subsidies construction'] = 0
self._yearly_capital_incomes.loc[0, 'Subsidies HVAC'] = 0
self._yearly_capital_incomes.loc[0, 'Subsidies PV'] = 0
self._yearly_capital_costs.fillna(0, inplace=True)
if self._retrofitting_scenario in (SKIN_RETROFIT, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV):
chapter = chapters.chapter('B_shell')
capital_cost_opaque = 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

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# Ignore everything in this directory
*
# Except this file
!.gitignore

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# Ignore everything in this directory
*
# Except this file
!.gitignore

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"""
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

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"""
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

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"""
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

4
costs/version.py Normal file
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"""
Cost version number
"""
__version__ = '0.1.0.0'

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pyproject.toml Normal file
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# pyproject.toml
[build-system]
requires = ["setuptools>=61.0.0", "wheel"]
build-backend = "setuptools.build_meta"
[options.packages.find_namespace]
where = "costs"

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numpy_financial
cerc_hub
pandas

36
setup.py Normal file
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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'))
]
)

1
tests/data/test.geojson Normal file

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tests/output/.gitignore vendored Normal file
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*
!.gitignore

73
tests/unit_tests.py Normal file
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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)