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Author SHA1 Message Date
atiya
dc544eaadf Capital cost 2023-01-28 18:30:14 -05:00
atiya
d3fc2802ff Capital cost 2023-01-28 18:25:57 -05:00
atiya
666e11dd3d cost_workflow v2 2023-01-18 10:24:29 -05:00
atiya
f7e15a4284 cost_workflow v1 2023-01-11 04:56:02 -05:00
30 changed files with 208771 additions and 1241 deletions

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"""
CapitalCost calculates the Capital Cost of one building
SPDX - License - Identifier: LGPL - 3.0 - or -later
Copyright © 2022 Project Coder Atiya atiya.atiya@mail.concordia.ca
"""
class CapitalCost:
def calculate_capital_cost(building_area, municipality, building_volume, total_opaque_area, total_transparent_area, content, heating_load, cooling_load, floor_area):
for cost in content.costs:
if cost.municipality == municipality:
structural_cost = float(cost.capital_cost.structural_cost) * building_volume
sub_structural_cost = float(cost.capital_cost.sub_structural_cost) * building_area
envelop_cost = 0.0
for i in range(len(cost.capital_cost.envelop_cost)):
if cost.capital_cost.envelop_cost[i].type == 'opaque_cost':
opague_cost = float(cost.capital_cost.envelop_cost[i].reposition) * total_opaque_area + float(
cost.capital_cost.envelop_cost[i].initial_investment) * total_opaque_area
envelop_cost += opague_cost
if cost.capital_cost.envelop_cost[i].type == 'transparent_cost':
transparent_cost = float(cost.capital_cost.envelop_cost[i].reposition) * total_transparent_area + float(
cost.capital_cost.envelop_cost[i].initial_investment) * total_transparent_area
envelop_cost += transparent_cost
# print("envelop_cost ", envelop_cost)
hvac_cost = 0.0
for i in range(len(cost.capital_cost.system_cost.hvac_cost)):
if cost.capital_cost.system_cost.hvac_cost[i].type == 'heating_load_cost':
heating_load_cost = float(cost.capital_cost.system_cost.hvac_cost[i].reposition) * heating_load + float(
cost.capital_cost.system_cost.hvac_cost[i].initial_investment) * heating_load
hvac_cost += heating_load_cost
if cost.capital_cost.system_cost.hvac_cost[i].type == 'cooling_load_cost':
cooling_load_cost = float(cost.capital_cost.system_cost.hvac_cost[i].reposition) * cooling_load + float(
cost.capital_cost.system_cost.hvac_cost[i].initial_investment) * cooling_load
hvac_cost += cooling_load_cost
rest_cost = float(cost.capital_cost.system_cost.rest_cost.reposition) * floor_area
pv_cost = float(cost.capital_cost.system_cost.pv_cost.reposition) * floor_area
system_cost = hvac_cost + rest_cost + pv_cost
lighting_cost = float(cost.capital_cost.lighting_cost) * building_area
surface_finish_cost = float(cost.capital_cost.surface_finish_cost) * building_area
engineer_cost = (float(cost.capital_cost.engineer_cost) * (structural_cost + sub_structural_cost + envelop_cost + system_cost + lighting_cost + surface_finish_cost)) / 100
construction_subsidy = (float(cost.capital_cost.subsidy.construction_subsidy) * (structural_cost + sub_structural_cost + envelop_cost)) / 100
hvac_subsidy = (float(cost.capital_cost.subsidy.hvac_subsidy) * hvac_cost) / 100
pv_subsidy = (float(cost.capital_cost.subsidy.pv_subsidy) * pv_cost) / 100
subsidy = construction_subsidy + hvac_subsidy + pv_subsidy
capital_cost = structural_cost + sub_structural_cost + envelop_cost + system_cost + lighting_cost + surface_finish_cost + engineer_cost + subsidy
return capital_cost

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

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

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

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

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"""
LifeCycleCosts module calculates the life cycle costs of one building
SPDX - License - Identifier: LGPL - 3.0 - or -later
Copyright © 2022 Project Author Pilar Monsalvete Alvarez de Uribarri pilar_monsalvete@concordia.ca
Code contributor Oriol Gavalda Torrellas oriol.gavalda@concordia.ca
"""
import math
import pandas as pd
import numpy_financial as npf
import hub.helpers.constants as cte
from costs import SKIN_RETROFIT, SYSTEM_RETROFIT_AND_PV, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV, PERCENTAGE_CREDIT,INTEREST_RATE,CREDIT_YEARS
class LifeCycleCosts:
"""
Life cycle cost class
"""
def __init__(self, building, archetype, number_of_years, consumer_price_index, electricity_peak_index,
electricity_price_index, gas_price_index, discount_rate,
retrofitting_scenario, fuel_type):
self._building = building
self._number_of_years = number_of_years
self._consumer_price_index = consumer_price_index
self._electricity_peak_index = electricity_peak_index
self._electricity_price_index = electricity_price_index
self._gas_price_index = gas_price_index
self._discount_rate = discount_rate
self._archetype = archetype
self._end_of_life_cost = 0
self._capital_costs_at_year_0 = 0
self._items = 0
self._fuels = 0
self._concepts = 0
self._retrofitting_scenario = retrofitting_scenario
self._total_floor_area = 0
self._fuel_type = fuel_type
for internal_zone in building.internal_zones:
for thermal_zone in internal_zone.thermal_zones:
self._total_floor_area += thermal_zone.total_floor_area
# todo: revise if it works
rng = range(number_of_years)
self._yearly_capital_costs = pd.DataFrame(index=rng, columns=['B2010_opaque_walls', 'B2020_transparent',
'B3010_opaque_roof', 'B10_superstructure',
'D301010_photovoltaic_system',
'D3020_heat_generating_systems',
'D3030_cooling_generation_systems',
'D3040_distribution_systems',
'D3080_other_hvac_ahu',
'D5020_lighting_and_branch_wiring'],
dtype='float')
self._yearly_end_of_life_costs = pd.DataFrame(index=rng, columns=['End_of_life_costs'], dtype='float')
self._yearly_operational_costs = pd.DataFrame(index=rng, columns=['Fixed_costs_electricity_peak',
'Fixed_costs_electricity_monthly',
'Variable_costs_electricity', 'Fixed_costs_gas',
'Variable_costs_gas'],
dtype='float')
self._yearly_maintenance_costs = pd.DataFrame(index=rng, columns=['Heating_maintenance', 'Cooling_maintenance',
'PV_maintenance'], dtype='float')
self._yearly_operational_incomes = pd.DataFrame(index=rng, columns=['Incomes electricity'], dtype='float')
self._yearly_capital_incomes = pd.DataFrame(index=rng, columns=['Subsidies construction',
'Subsidies HVAC', 'Subsidies PV'], dtype='float')
def calculate_capital_costs(self):
"""
Calculate capital cost
:return: pd.DataFrame
"""
building = self._building
archetype = self._archetype
surface_opaque = 0
surface_transparent = 0
surface_roof = 0
surface_ground = 0
capital_cost_pv = 0
capital_cost_opaque = 0
capital_cost_ground = 0
capital_cost_transparent = 0
capital_cost_roof = 0
capital_cost_heating_equipment = 0
capital_cost_cooling_equipment = 0
capital_cost_distribution_equipment = 0
capital_cost_other_hvac_ahu = 0
capital_cost_lighting = 0
total_floor_area = self._total_floor_area
for internal_zone in building.internal_zones:
for thermal_zone in internal_zone.thermal_zones:
for thermal_boundary in thermal_zone.thermal_boundaries:
if thermal_boundary.type == 'Ground':
surface_ground += thermal_boundary.opaque_area
elif thermal_boundary.type == 'Roof':
surface_roof += thermal_boundary.opaque_area
elif thermal_boundary.type == 'Wall':
surface_opaque += thermal_boundary.opaque_area * (1 - thermal_boundary.window_ratio)
surface_transparent += thermal_boundary.opaque_area * thermal_boundary.window_ratio
chapters = archetype.capital_cost
peak_heating = building.heating_peak_load[cte.YEAR][0]/1000
peak_cooling = building.cooling_peak_load[cte.YEAR][0]/1000
# todo: change area pv when the variable exists
roof_area = 0
for roof in building.roofs:
roof_area += roof.solid_polygon.area
surface_pv = roof_area * 0.5
self._yearly_capital_costs.loc[0, 'B2010_opaque_walls'] = 0
self._yearly_capital_costs.loc[0]['B2020_transparent'] = 0
self._yearly_capital_costs.loc[0, 'B3010_opaque_roof'] = 0
self._yearly_capital_costs.loc[0]['B10_superstructure'] = 0
self._yearly_capital_costs.loc[0, 'D3020_heat_generating_systems'] = 0
self._yearly_capital_costs.loc[0, 'D3030_cooling_generation_systems'] = 0
self._yearly_capital_costs.loc[0, 'D3040_distribution_systems'] = 0
self._yearly_capital_costs.loc[0, 'D3080_other_hvac_ahu'] = 0
self._yearly_capital_costs.loc[0, 'D5020_lighting_and_branch_wiring'] = 0
self._yearly_capital_incomes.loc[0, 'Subsidies construction'] = 0
self._yearly_capital_incomes.loc[0, 'Subsidies HVAC'] = 0
self._yearly_capital_incomes.loc[0, 'Subsidies PV'] = 0
self._yearly_capital_costs.fillna(0, inplace=True)
if self._retrofitting_scenario in (SKIN_RETROFIT, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV):
chapter = chapters.chapter('B_shell')
capital_cost_opaque = surface_opaque * chapter.item('B2010_opaque_walls').refurbishment[0]
capital_cost_transparent = surface_transparent * chapter.item('B2020_transparent').refurbishment[0]
capital_cost_roof = surface_roof * chapter.item('B3010_opaque_roof').refurbishment[0]
capital_cost_ground = surface_ground * chapter.item('B10_superstructure').refurbishment[0]
self._yearly_capital_costs.loc[0, 'B2010_opaque_walls'] = capital_cost_opaque * (1-PERCENTAGE_CREDIT)
self._yearly_capital_costs.loc[0]['B2020_transparent'] = capital_cost_transparent * (1-PERCENTAGE_CREDIT)
self._yearly_capital_costs.loc[0, 'B3010_opaque_roof'] = capital_cost_roof * (1-PERCENTAGE_CREDIT)
self._yearly_capital_costs.loc[0]['B10_superstructure'] = capital_cost_ground * (1-PERCENTAGE_CREDIT)
if self._retrofitting_scenario in (SYSTEM_RETROFIT_AND_PV, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV):
chapter = chapters.chapter('D_services')
capital_cost_pv = surface_pv * chapter.item('D301010_photovoltaic_system').initial_investment[0]
self._yearly_capital_costs.loc[0]['D301010_photovoltaic_system'] = capital_cost_pv
capital_cost_heating_equipment = (
peak_heating * chapter.item('D3020_heat_generating_systems').initial_investment[0]
)
capital_cost_cooling_equipment = (
peak_cooling * chapter.item('D3030_cooling_generation_systems').initial_investment[0]
)
capital_cost_distribution_equipment = (
peak_cooling * chapter.item('D3040_distribution_systems').initial_investment[0]
)
capital_cost_other_hvac_ahu = peak_cooling * chapter.item('D3080_other_hvac_ahu').initial_investment[0]
capital_cost_lighting = total_floor_area * chapter.item('D5020_lighting_and_branch_wiring').initial_investment[0]
self._yearly_capital_costs.loc[0, 'D3020_heat_generating_systems'] = capital_cost_heating_equipment * (1-PERCENTAGE_CREDIT)
self._yearly_capital_costs.loc[0, 'D3030_cooling_generation_systems'] = capital_cost_cooling_equipment * (1-PERCENTAGE_CREDIT)
self._yearly_capital_costs.loc[0, 'D3040_distribution_systems'] = capital_cost_distribution_equipment * (1-PERCENTAGE_CREDIT)
self._yearly_capital_costs.loc[0, 'D3080_other_hvac_ahu'] = capital_cost_other_hvac_ahu * (1-PERCENTAGE_CREDIT)
self._yearly_capital_costs.loc[0, 'D5020_lighting_and_branch_wiring'] = capital_cost_lighting * (1-PERCENTAGE_CREDIT)
for year in range(1, self._number_of_years):
chapter = chapters.chapter('D_services')
costs_increase = math.pow(1 + self._consumer_price_index, year)
self._yearly_capital_costs.loc[year, 'B2010_opaque_walls'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS,
capital_cost_opaque * (PERCENTAGE_CREDIT))
self._yearly_capital_costs.loc[year, 'B2020_transparent'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS,
capital_cost_transparent * (PERCENTAGE_CREDIT)
)
self._yearly_capital_costs.loc[year, 'B3010_opaque_roof'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS,capital_cost_roof
* (PERCENTAGE_CREDIT))
self._yearly_capital_costs.loc[year, 'B10_superstructure'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS,
capital_cost_ground * (PERCENTAGE_CREDIT))
self._yearly_capital_costs.loc[year, 'D3020_heat_generating_systems'] = -npf.pmt(INTEREST_RATE,CREDIT_YEARS,
capital_cost_heating_equipment
* (PERCENTAGE_CREDIT))
self._yearly_capital_costs.loc[year, 'D3030_cooling_generation_systems'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS,
capital_cost_cooling_equipment
* (PERCENTAGE_CREDIT))
self._yearly_capital_costs.loc[year, 'D3040_distribution_systems'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS,
capital_cost_distribution_equipment
* (PERCENTAGE_CREDIT))
self._yearly_capital_costs.loc[year, 'D3080_other_hvac_ahu'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS,
capital_cost_other_hvac_ahu
* (PERCENTAGE_CREDIT))
self._yearly_capital_costs.loc[year, 'D5020_lighting_and_branch_wiring'] = -npf.pmt(INTEREST_RATE, CREDIT_YEARS,
capital_cost_lighting
* (PERCENTAGE_CREDIT))
if (year % chapter.item('D3020_heat_generating_systems').lifetime) == 0:
reposition_cost_heating_equipment = peak_heating * chapter.item('D3020_heat_generating_systems').reposition[0] \
* costs_increase
self._yearly_capital_costs.loc[year, 'D3020_heat_generating_systems'] += reposition_cost_heating_equipment
if (year % chapter.item('D3030_cooling_generation_systems').lifetime) == 0:
reposition_cost_cooling_equipment = peak_cooling \
* chapter.item('D3030_cooling_generation_systems').reposition[0] \
* costs_increase
self._yearly_capital_costs.loc[year, 'D3030_cooling_generation_systems'] += reposition_cost_cooling_equipment
if (year % chapter.item('D3080_other_hvac_ahu').lifetime) == 0:
reposition_cost_hvac_ahu = peak_cooling * chapter.item('D3080_other_hvac_ahu').reposition[0] * costs_increase
self._yearly_capital_costs.loc[year, 'D3080_other_hvac_ahu'] = reposition_cost_hvac_ahu
if (year % chapter.item('D5020_lighting_and_branch_wiring').lifetime) == 0:
reposition_cost_lighting = total_floor_area * chapter.item('D5020_lighting_and_branch_wiring').reposition[0] \
* costs_increase
self._yearly_capital_costs.loc[year, 'D5020_lighting_and_branch_wiring'] += reposition_cost_lighting
if self._retrofitting_scenario in (SYSTEM_RETROFIT_AND_PV, SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV):
if (year % chapter.item('D301010_photovoltaic_system').lifetime) == 0:
self._yearly_capital_costs.loc[year]['D301010_photovoltaic_system'] += surface_pv \
* chapter.item(
'D301010_photovoltaic_system').reposition[0] * costs_increase
capital_cost_skin = capital_cost_opaque + capital_cost_ground + capital_cost_transparent + capital_cost_roof
capital_cost_hvac = (
capital_cost_heating_equipment +
capital_cost_cooling_equipment +
capital_cost_distribution_equipment +
capital_cost_other_hvac_ahu + capital_cost_lighting
)
self._yearly_capital_incomes.loc[0, 'Subsidies construction'] = (
capital_cost_skin * archetype.income.construction_subsidy/100
)
self._yearly_capital_incomes.loc[0, 'Subsidies HVAC'] = capital_cost_hvac * archetype.income.hvac_subsidy/100
self._yearly_capital_incomes.loc[0, 'Subsidies PV'] = capital_cost_pv * archetype.income.photovoltaic_subsidy/100
self._yearly_capital_incomes.fillna(0, inplace=True)
return self._yearly_capital_costs, self._yearly_capital_incomes
def calculate_end_of_life_costs(self):
"""
Calculate end of life costs
:return: pd.DataFrame
"""
archetype = self._archetype
total_floor_area = self._total_floor_area
for year in range(1, self._number_of_years + 1):
price_increase = math.pow(1 + self._consumer_price_index, year)
if year == self._number_of_years:
self._yearly_end_of_life_costs.at[
year, 'End_of_life_costs'] = total_floor_area * archetype.end_of_life_cost * price_increase
self._yearly_end_of_life_costs.fillna(0, inplace=True)
return self._yearly_end_of_life_costs
def calculate_total_floor_area(self):
total_floor_area = self._total_floor_area
return total_floor_area
@property
def calculate_total_operational_costs(self):
"""
Calculate total operational costs
:return: pd.DataFrame
"""
building = self._building
archetype = self._archetype
total_floor_area = self._total_floor_area
factor_residential = total_floor_area / 80
# todo: split the heating between fuels
fixed_gas_cost_year_0 = 0
variable_gas_cost_year_0 = 0
electricity_heating = 0
domestic_hot_water_electricity = 0
if self._fuel_type == 1:
fixed_gas_cost_year_0 = archetype.operational_cost.fuels[1].fixed_monthly * 12 * factor_residential
variable_gas_cost_year_0 = (
(building.heating_consumption[cte.YEAR][0] + building.domestic_hot_water_consumption[cte.YEAR][0]) / 1000 *
archetype.operational_cost.fuels[1].variable[0]
)
if self._fuel_type == 0:
electricity_heating = building.heating_consumption[cte.YEAR][0] / 1000
domestic_hot_water_electricity = building.domestic_hot_water_consumption[cte.YEAR][0] / 1000
electricity_cooling = building.cooling_consumption[cte.YEAR][0] / 1000
electricity_lighting = building.lighting_electrical_demand[cte.YEAR]['insel meb'] / 1000
electricity_plug_loads = building.appliances_electrical_demand[cte.YEAR]['insel meb'] / 1000
electricity_distribution = 0
total_electricity_consumption = (
electricity_heating + electricity_cooling + electricity_lighting + domestic_hot_water_electricity +
electricity_plug_loads + electricity_distribution
)
print(f'electricity consumption {total_electricity_consumption}')
# todo: change when peak electricity demand is coded. Careful with factor residential
peak_electricity_demand = 0.1*total_floor_area # self._peak_electricity_demand
variable_electricity_cost_year_0 = total_electricity_consumption * archetype.operational_cost.fuels[0].variable[0]
peak_electricity_cost_year_0 = peak_electricity_demand * archetype.operational_cost.fuels[0].fixed_power * 12
monthly_electricity_cost_year_0 = archetype.operational_cost.fuels[0].fixed_monthly * 12 * factor_residential
for year in range(1, self._number_of_years + 1):
price_increase_electricity = math.pow(1 + self._electricity_price_index, year)
price_increase_peak_electricity = math.pow(1 + self._electricity_peak_index, year)
price_increase_gas = math.pow(1 + self._gas_price_index, year)
self._yearly_operational_costs.at[year, 'Fixed_costs_electricity_peak'] = (
peak_electricity_cost_year_0 * price_increase_peak_electricity
)
self._yearly_operational_costs.at[year, 'Fixed_costs_electricity_monthly'] = (
monthly_electricity_cost_year_0 * price_increase_peak_electricity
)
self._yearly_operational_costs.at[year, 'Variable_costs_electricity'] = float(
variable_electricity_cost_year_0 * price_increase_electricity
)
self._yearly_operational_costs.at[year, 'Fixed_costs_gas'] = fixed_gas_cost_year_0 * price_increase_gas
self._yearly_operational_costs.at[year, 'Variable_costs_gas'] = (
variable_gas_cost_year_0 * price_increase_peak_electricity
)
self._yearly_operational_costs.at[year, 'Variable_costs_gas'] = (
variable_gas_cost_year_0 * price_increase_peak_electricity
)
self._yearly_operational_costs.fillna(0, inplace=True)
return self._yearly_operational_costs
def calculate_total_operational_incomes(self, retrofitting_scenario):
"""
Calculate total operational incomes
:return: pd.DataFrame
"""
building = self._building
if cte.YEAR not in building.onsite_electrical_production:
onsite_electricity_production = 0
else:
if retrofitting_scenario == 0 or retrofitting_scenario == 1:
onsite_electricity_production = 0
else:
onsite_electricity_production = building.onsite_electrical_production[cte.YEAR][0]/1000
for year in range(1, self._number_of_years + 1):
price_increase_electricity = math.pow(1 + self._electricity_price_index, year)
# todo: check the adequate assignation of price. Pilar
price_export = 0.075 # archetype.income.electricity_export
self._yearly_operational_incomes.loc[year, 'Incomes electricity'] = (
onsite_electricity_production * price_export * price_increase_electricity
)
self._yearly_operational_incomes.fillna(0, inplace=True)
return self._yearly_operational_incomes
def calculate_total_maintenance_costs(self):
"""
Calculate total maintenance costs
:return: pd.DataFrame
"""
building = self._building
archetype = self._archetype
# todo: change area pv when the variable exists
roof_area = 0
for roof in building.roofs:
roof_area += roof.solid_polygon.area
surface_pv = roof_area * 0.5
peak_heating = building.heating_peak_load[cte.YEAR][0]/1000
peak_cooling = building.heating_peak_load[cte.YEAR][0]/1000
maintenance_heating_0 = peak_heating * archetype.operational_cost.maintenance_heating
maintenance_cooling_0 = peak_cooling * archetype.operational_cost.maintenance_cooling
maintenance_pv_0 = surface_pv * archetype.operational_cost.maintenance_pv
for year in range(1, self._number_of_years + 1):
costs_increase = math.pow(1 + self._consumer_price_index, year)
self._yearly_maintenance_costs.loc[year, 'Heating_maintenance'] = (
maintenance_heating_0 * costs_increase
)
self._yearly_maintenance_costs.loc[year, 'Cooling_maintenance'] = (
maintenance_cooling_0 * costs_increase
)
self._yearly_maintenance_costs.loc[year, 'PV_maintenance'] = (
maintenance_pv_0 * costs_increase
)
self._yearly_maintenance_costs.fillna(0, inplace=True)
return self._yearly_maintenance_costs

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

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

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

File diff suppressed because it is too large Load Diff

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data/FZK_Haus_LoD_0.gml Normal file
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<?xml version="1.0" encoding="utf-8"?><!-- Generated by: --><!-- IFC -> cityGML Converter --><!-- (C) - Institute for Applied Computer Science --><!-- Forschungszentrum Karlsruhe --><!-- Not for commercial use --><!-- Generated by: IfcExplorer--><!-- cityGML Schema: 1.0.0 --><!-- Level of Detail 1--><!-- Creation Date: Tuesday, 23 November 2010 - 10:37:59--><!-- Edited Manually in Oxygen 8.2 --><!-- Modified by GMLOffset.xslt at Mon Dec 6 2010 --><!-- Version 2 Building located in the area of KIT Campus North)--><!-- Modified by GMLOffset.xslt at Wed Dec 8 2010 --><!-- Modified by GMLOffset.xslt at Wed Mar 29 2017 --><core:CityModel xsi:schemaLocation="http://www.opengis.net/citygml/2.0 http://schemas.opengis.net/citygml/2.0/cityGMLBase.xsd http://www.opengis.net/citygml/appearance/2.0 http://schemas.opengis.net/citygml/appearance/2.0/appearance.xsd http://www.opengis.net/citygml/building/2.0 http://schemas.opengis.net/citygml/building/2.0/building.xsd http://www.opengis.net/citygml/generics/2.0 http://schemas.opengis.net/citygml/generics/2.0/generics.xsd" xmlns:core="http://www.opengis.net/citygml/2.0" xmlns="http://www.opengis.net/citygml/profiles/base/2.0" xmlns:bldg="http://www.opengis.net/citygml/building/2.0" xmlns:gen="http://www.opengis.net/citygml/generics/2.0" xmlns:grp="http://www.opengis.net/citygml/cityobjectgroup/2.0" xmlns:app="http://www.opengis.net/citygml/appearance/2.0" xmlns:gml="http://www.opengis.net/gml" xmlns:xAL="urn:oasis:names:tc:ciq:xsdschema:xAL:2.0" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<!-- Manually edited by KHH 23.01.2017, Address added, roof edge added -->
<gml:name>AC14-FZK-Haus</gml:name>
<gml:boundedBy>
<gml:Envelope srsDimension="3" srsName="urn:adv:crs:ETRS89_UTM32*DE_DHHN92_NH">
<gml:lowerCorner srsDimension="3">457842 5439083 111.8 </gml:lowerCorner>
<gml:upperCorner srsDimension="3">457854 5439093 118.317669 </gml:upperCorner>
</gml:Envelope>
</gml:boundedBy>
<core:cityObjectMember>
<bldg:Building gml:id="UUID_d281adfc-4901-0f52-540b-4cc1a9325f82">
<gml:description>FZK-Haus (Forschungszentrum Karlsruhe, now KIT), created by Karl-Heinz
Haefele </gml:description>
<gml:name>AC14-FZK-Haus</gml:name>
<core:creationDate>2017-01-23</core:creationDate>
<core:relativeToTerrain>entirelyAboveTerrain</core:relativeToTerrain>
<gen:measureAttribute name="GrossPlannedArea">
<gen:value uom="m2">120.00</gen:value>
</gen:measureAttribute>
<gen:stringAttribute name="ConstructionMethod">
<gen:value>New Building</gen:value>
</gen:stringAttribute>
<gen:stringAttribute name="IsLandmarked">
<gen:value>NO</gen:value>
</gen:stringAttribute>
<bldg:class codeSpace="http://www.sig3d.org/codelists/citygml/2.0/building/2.0/_AbstractBuilding_class.xml">1000</bldg:class>
<bldg:function codeSpace="http://www.sig3d.org/codelists/citygml/2.0/building/2.0/_AbstractBuilding_function.xml">1000</bldg:function>
<bldg:usage codeSpace="http://www.sig3d.org/codelists/citygml/2.0/building/2.0/_AbstractBuilding_usage.xml">1000</bldg:usage>
<bldg:yearOfConstruction>2020</bldg:yearOfConstruction>
<bldg:roofType codeSpace="http://www.sig3d.org/codelists/citygml/2.0/building/2.0/_AbstractBuilding_roofType.xml">1030</bldg:roofType>
<bldg:measuredHeight uom="m">6.52</bldg:measuredHeight>
<bldg:storeysAboveGround>2</bldg:storeysAboveGround>
<bldg:storeysBelowGround>0</bldg:storeysBelowGround>
<bldg:lod0FootPrint>
<gml:MultiSurface>
<gml:surfaceMember>
<gml:Polygon>
<gml:exterior>
<gml:LinearRing>
<gml:posList srsDimension="3">457842 5439083 111.8 457842 5439093 111.8 457854 5439093 111.8 457854 5439083 111.8 457842 5439083 111.8 </gml:posList>
</gml:LinearRing>
</gml:exterior>
</gml:Polygon>
</gml:surfaceMember>
</gml:MultiSurface>
</bldg:lod0FootPrint>
<bldg:lod0RoofEdge>
<gml:MultiSurface>
<gml:surfaceMember>
<gml:Polygon>
<gml:exterior>
<gml:LinearRing>
<gml:posList srsDimension="3">457841.5 5439082.5 111.8 457841.5 5439093.5 111.8 457854.5 5439093.5 111.8 457854.5 5439082.5 111.8 457841.5 5439082.5 111.8 </gml:posList>
</gml:LinearRing>
</gml:exterior>
</gml:Polygon>
</gml:surfaceMember>
</gml:MultiSurface>
</bldg:lod0RoofEdge>
<bldg:address>
<core:Address>
<core:xalAddress>
<xAL:AddressDetails>
<xAL:Locality Type="Town">
<xAL:LocalityName>Eggenstein-Leopoldshafen</xAL:LocalityName>
<xAL:Thoroughfare Type="Street">
<xAL:ThoroughfareNumber>4711</xAL:ThoroughfareNumber>
<xAL:ThoroughfareName>Spöcker Straße</xAL:ThoroughfareName>
</xAL:Thoroughfare>
<xAL:PostalCode>
<xAL:PostalCodeNumber>76344</xAL:PostalCodeNumber>
</xAL:PostalCode>
</xAL:Locality>
</xAL:AddressDetails>
</core:xalAddress>
</core:Address>
</bldg:address>
</bldg:Building>
</core:cityObjectMember>
</core:CityModel>

116
data/FZK_Haus_LoD_1.gml Normal file
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<?xml version="1.0" encoding="utf-8"?><!-- Generated by: --><!-- IFC -> cityGML Converter --><!-- (C) - Institute for Applied Computer Science --><!-- Forschungszentrum Karlsruhe --><!-- Not for commercial use --><!-- Generated by: IfcExplorer--><!-- cityGML Schema: 1.0.0 --><!-- Level of Detail 1--><!-- Creation Date: Tuesday, 23 November 2010 - 10:37:59--><!-- Edited Manually in Oxygen 8.2 --><!-- Modified by GMLOffset.xslt at Mon Dec 6 2010 --><!-- Version 2 Building located in the area of KIT Campus North)--><!-- Modified by GMLOffset.xslt at Wed Dec 8 2010 --><!-- Modified by GMLOffset.xslt at Wed Mar 29 2017 --><core:CityModel xsi:schemaLocation="http://www.opengis.net/citygml/2.0 http://schemas.opengis.net/citygml/2.0/cityGMLBase.xsd http://www.opengis.net/citygml/appearance/2.0 http://schemas.opengis.net/citygml/appearance/2.0/appearance.xsd http://www.opengis.net/citygml/building/2.0 http://schemas.opengis.net/citygml/building/2.0/building.xsd http://www.opengis.net/citygml/generics/2.0 http://schemas.opengis.net/citygml/generics/2.0/generics.xsd" xmlns:core="http://www.opengis.net/citygml/2.0" xmlns="http://www.opengis.net/citygml/profiles/base/2.0" xmlns:bldg="http://www.opengis.net/citygml/building/2.0" xmlns:gen="http://www.opengis.net/citygml/generics/2.0" xmlns:grp="http://www.opengis.net/citygml/cityobjectgroup/2.0" xmlns:app="http://www.opengis.net/citygml/appearance/2.0" xmlns:gml="http://www.opengis.net/gml" xmlns:xAL="urn:oasis:names:tc:ciq:xsdschema:xAL:2.0" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<!-- Manually edited by KHH 23.01.2017, CityGML 2.0, Address added, roof edge added -->
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Haefele </gml:description>
<gml:name>AC14-FZK-Haus</gml:name>
<core:creationDate>2017-01-23</core:creationDate>
<core:relativeToTerrain>entirelyAboveTerrain</core:relativeToTerrain>
<gen:measureAttribute name="GrossPlannedArea">
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</gen:measureAttribute>
<gen:stringAttribute name="ConstructionMethod">
<gen:value>New Building</gen:value>
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<gen:stringAttribute name="IsLandmarked">
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</gen:stringAttribute>
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<bldg:yearOfConstruction>2020</bldg:yearOfConstruction>
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<bldg:address>
<core:Address>
<core:xalAddress>
<xAL:AddressDetails>
<xAL:Locality Type="Town">
<xAL:LocalityName>Eggenstein-Leopoldshafen</xAL:LocalityName>
<xAL:Thoroughfare Type="Street">
<xAL:ThoroughfareNumber>4711</xAL:ThoroughfareNumber>
<xAL:ThoroughfareName>Spöcker Straße</xAL:ThoroughfareName>
</xAL:Thoroughfare>
<xAL:PostalCode>
<xAL:PostalCodeNumber>76344</xAL:PostalCodeNumber>
</xAL:PostalCode>
</xAL:Locality>
</xAL:AddressDetails>
</core:xalAddress>
</core:Address>
</bldg:address>
</bldg:Building>
</core:cityObjectMember>
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data/FZK_Haus_LoD_2.gml Normal file
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<!-- Manually edited by KHH 23.01.2017, CityGML 2.0, Address added, Codespaces added -->
<gml:name>AC14-FZK-Haus</gml:name>
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<core:cityObjectMember>
<bldg:Building gml:id="UUID_d281adfc-4901-0f52-540b-4cc1a9325f82">
<gml:description>FZK-Haus (Forschungszentrum Karlsruhe, now KIT), created by Karl-Heinz
Haefele </gml:description>
<gml:name>AC14-FZK-Haus</gml:name>
<core:creationDate>2017-01-23</core:creationDate>
<core:relativeToTerrain>entirelyAboveTerrain</core:relativeToTerrain>
<gen:measureAttribute name="GrossPlannedArea">
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<gen:stringAttribute name="ConstructionMethod">
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<gen:stringAttribute name="IsLandmarked">
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<bldg:class codeSpace="http://www.sig3d.org/codelists/citygml/2.0/building/2.0/_AbstractBuilding_class.xml">1000</bldg:class>
<bldg:function codeSpace="http://www.sig3d.org/codelists/citygml/2.0/building/2.0/_AbstractBuilding_function.xml">1000</bldg:function>
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<bldg:yearOfConstruction>2020</bldg:yearOfConstruction>
<bldg:roofType codeSpace="http://www.sig3d.org/codelists/citygml/2.0/building/2.0/_AbstractBuilding_roofType.xml">1030</bldg:roofType>
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<!--Outer Wall 1 (West) -->
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<!--Outer Wall 1 (West) -->
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3451
data/FZK_Haus_LoD_3.gml Normal file

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data/costs.xml Normal file
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<?xml version="1.0" encoding="utf-8"?>
<cost_catalogs>
<cost_catalog function="residential" municipality="montreal" id="1" currency="CAD">
<capital_cost>
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<sub_structural_cost cost_unit="currency/m2"> 9.8 </sub_structural_cost>
<envelop_cost>
<opaque_cost>
<reposition cost_unit="currency/m2"> 43.4 </reposition>
<initial_investment cost_unit="currency/m2"> 36 </initial_investment>
</opaque_cost>
<transparent_cost>
<reposition cost_unit="currency/m2"> 78 </reposition>
<initial_investment cost_unit="currency/m2"> 984.5 </initial_investment>
</transparent_cost>
</envelop_cost>
<system_cost>
<hvac_cost>
<heating_load_cost>
<reposition cost_unit="currency/kw"> 7839 </reposition>
<initial_investment cost_unit="currency/kw"> 363.5 </initial_investment>
</heating_load_cost>
<cooling_load_cost>
<reposition cost_unit="currency/kw"> 7839 </reposition>
<initial_investment cost_unit="currency/kw"> 363.5 </initial_investment>
</cooling_load_cost>
</hvac_cost>
<rest_cost>
<reposition cost_unit="currency/m2"> 1 </reposition>
<initial_investment cost_unit="currency/m2"> 365 </initial_investment>
</rest_cost>
<pv_cost>
<reposition cost_unit="currency/m2"> 98.98 </reposition>
<initial_investment cost_unit="currency/m2"> 17 </initial_investment>
</pv_cost>
</system_cost>
<lighting_cost cost_unit="currency/m2"> 36 </lighting_cost>
<surface_finish_cost cost_unit="currency/m2"> 88 </surface_finish_cost>
<engineer_cost cost_unit="%"> 2.5 </engineer_cost>
<subsidy>
<construction_subsidy cost_unit="%"> 2 </construction_subsidy>
<hvac_subsidy cost_unit="%"> 1.5 </hvac_subsidy>
<pv_subsidy cost_unit="%"> 3.6 </pv_subsidy>
</subsidy>
</capital_cost>
<operational_cost fuel_type="electricity">
<fuel_operational_cost cost_unit="currency/kwh"> 5.6 </fuel_operational_cost>
<maintenance_cost>
<systems_maintenance_cost cost_unit="currency/m2"> 4.6 </systems_maintenance_cost>
<pv_maintenance_cost cost_unit="currency/m2"> 888.9 </pv_maintenance_cost>
</maintenance_cost>
<peak_power_cost cost_unit="currency/kw"> 0.80 </peak_power_cost>
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</cost_catalogs>

View File

@ -0,0 +1,409 @@
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420
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98
life_cycle_costs.py Normal file
View File

@ -0,0 +1,98 @@
"""
LifeCycleCosts 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
"""
import math
from pathlib import Path
from imports.geometry_factory import GeometryFactory
from costs_workflow.capital_cost import CapitalCost
from catalog_factories.costs_catalog_factory import CostCatalogFactory
from imports.construction_factory import ConstructionFactory
class LifeCycleCosts:
number_of_years = 40
consumer_price_index = 0.1
catalog = CostCatalogFactory('montreal_catalog').catalog
content = catalog.entries()
construction_format = 'nrel'
usage_format = 'comnet'
base_path = Path(Path(__file__).parent / 'unittests/tests_data')
gml_file = str(base_path / 'one_building_in_kelowna.gml')
city = GeometryFactory('citygml', gml_file).city
for building in city.buildings:
building.year_of_construction = 2006
ConstructionFactory(construction_format, city).enrich()
# todo: this should be (city, costs_catalog) or similar
def __init__(self, building, number_of_years, consumer_price_index, discount_rate, end_of_life_cost,
capital_costs_at_year_0, items, fuels, concepts):
self._building = building
self._number_of_years = number_of_years
self._consumer_price_index = consumer_price_index
self._discount_rate = discount_rate
self._end_of_life_cost = end_of_life_cost
self._capital_costs_at_year_0 = capital_costs_at_year_0
self._items = items
self._fuels = fuels
self._concepts = concepts
def calculate_capital_costs(self):
total_capital_costs = self._capital_costs_at_year_0
for year in range(1, self._number_of_years + 1):
costs_increase = math.pow(1 + self._consumer_price_index, year) / math.pow(1 + self._discount_rate, year)
for item in self._items:
total_capital_costs += item.reposition_costs[year] * costs_increase
return total_capital_costs
def calculate_end_of_life_costs(self):
price_increase = 0
for year in range(1, self._number_of_years + 1):
price_increase += math.pow(1 + self._consumer_price_index, year) / math.pow(1 + self._discount_rate, year)
return self._end_of_life_cost * price_increase
def calculate_total_operational_costs(self):
total_operational_costs = 0
for year in range(1, self._number_of_years + 1):
for fuel in self._fuels:
total_operational_costs += fuel.operational_cost \
* math.pow(1 + fuel.energy_price_index, year) / math.pow(1 + self._discount_rate, year)
return total_operational_costs
def calculate_total_maintenance_costs(self):
total_maintenance_costs = 0
for year in range(1, self._number_of_years + 1):
costs_increase = math.pow(1 + self._consumer_price_index, year) / math.pow(1 + self._discount_rate, year)
for concept in self._concepts:
total_maintenance_costs += concept.mantainance_costs * costs_increase
return total_maintenance_costs
def calculate_capitalcost(self, city):
for building in city.buildings:
# municipality = "montreal"
lcc.calculate_capitalcost(building, municipality, content)
building_volume = 0.0
building_area = 0.0
total_opaque_area = 0.0
total_transparent_area = 0.0
for internal_zone in one_building.internal_zones:
for thermal_zone in internal_zone.thermal_zones:
for thermal_boundary in thermal_zone.thermal_boundaries:
if thermal_boundary.opaque_area is not None:
total_opaque_area += thermal_boundary.opaque_area
if thermal_boundary.windows_areas is not None:
total_transparent_area += thermal_boundary.windows_areas
building_area += internal_zone.area
building_volume += internal_zone.volume
# print("Total building_volume ", building_volume)
# print("Total building_area ", building_area)
# print("Total opaque_area ", total_opaque_area)
CapitalCost.calculate_capital_cost(building_area, municipality, building_volume, total_opaque_area, total_transparent_area, content)

12
operational_cost.py Normal file
View File

@ -0,0 +1,12 @@
"""
OperationalCost calculates the Operational Cost of one building
SPDX - License - Identifier: LGPL - 3.0 - or -later
Copyright © 2022 Project Coder Atiya atiya.atiya@mail.concordia.ca
"""
class OperationalCost:
def calculate_operational_cost(municipality, content):
for cost in content.costs:
if cost.municipality == municipality:
fuel_operational_cost = float(cost.operational_cost.fuel_operational_cost)

View File

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

View File

@ -1,2 +0,0 @@
numpy_financial
cerc_hub

View File

@ -0,0 +1,137 @@
"""
TestCostsWorkflow test
SPDX - License - Identifier: LGPL - 3.0 - or -later
Copyright © 2022 Concordia CERC group
Copyright © 2022 Project Coder Atiya atiya.atiya@mail.concordia.ca
"""
from pathlib import Path
from unittest import TestCase
import pandas as pd
import helpers.constants as cte
from helpers.monthly_values import MonthlyValues
from imports.geometry_factory import GeometryFactory
from imports.construction_factory import ConstructionFactory
from imports.usage_factory import UsageFactory
from imports.weather_factory import WeatherFactory
from peak_loads import PeakLoads
from costs_workflow.capital_cost import CapitalCost
from costs_workflow.life_cycle_costs import LifeCycleCosts
from catalog_factories.costs_catalog_factory import CostCatalogFactory
class TestPeakLoadsWorkflow(TestCase):
"""
TestPeakLoadsWorkflow class
"""
def setUp(self) -> None:
"""
Test setup
:return: None
"""
self._city = None
self._complete_city = None
self._example_path = (Path(__file__).parent / 'tests_data').resolve()
self._output_path = (Path(__file__).parent / 'tests_outputs').resolve()
def _get_citygml(self, file):
file_path = (self._example_path / file).resolve()
self._city = GeometryFactory('citygml', path=file_path).city
self.assertIsNotNone(self._city, 'city is none')
return self._city
@property
def _read_sra_file(self) -> []:
path = (self._example_path / "one_building_in_kelowna_sra_SW.out").resolve()
_results = pd.read_csv(path, sep='\s+', header=0)
id_building = ''
header_building = []
_radiation = []
for column in _results.columns.values:
if id_building != column.split(':')[1]:
id_building = column.split(':')[1]
if len(header_building) > 0:
_radiation.append(pd.concat([MonthlyValues().month_hour, _results[header_building]], axis=1))
header_building = [column]
else:
header_building.append(column)
_radiation.append(pd.concat([MonthlyValues().month_hour, _results[header_building]], axis=1))
return _radiation
def _set_irradiance_surfaces(self, city, irradiance_format):
"""
saves in building surfaces the correspondent irradiance at different time-scales depending on the mode
if building is None, it saves all buildings' surfaces in file, if building is specified, it saves only that
specific building values
:parameter city: city
:return: none
"""
for radiation in self._read_sra_file:
city_object_name = radiation.columns.values.tolist()[1].split(':')[1]
building = city.city_object(city_object_name)
for column in radiation.columns.values:
if column == cte.MONTH:
continue
header_id = column
surface_id = header_id.split(':')[2]
surface = building.surface_by_id(surface_id)
new_value = pd.DataFrame(radiation[[header_id]].to_numpy(), columns=[irradiance_format])
surface.global_irradiance[cte.HOUR] = new_value
def _enrich_city(self, city, weather_file, weather_format, irradiance_format, construction_format, usage_format):
WeatherFactory(weather_format, city, file_name=weather_file).enrich()
self._set_irradiance_surfaces(city, irradiance_format)
for building in city.buildings:
building.year_of_construction = 2006
if building.function is None:
building.function = cte.LARGE_OFFICE
ConstructionFactory(construction_format, city).enrich()
UsageFactory(usage_format, city).enrich()
def test_workflow(self):
outputs_path = (Path(__file__).parent / 'tests_outputs').resolve()
gml_file = 'one_building_in_kelowna.gml'
city = self._get_citygml(gml_file)
weather_file = 'CAN_PQ_Montreal.Intl.AP.716270_CWEC.epw'
weather_format = 'epw'
irradiance_format = 'sra'
construction_format = 'nrel'
usage_format = 'comnet'
number_of_years = 40
consumer_price_index = 0.1
discount_rate = 2.5
self._enrich_city(city, weather_file, weather_format, irradiance_format, construction_format, usage_format)
municipality = "montreal"
catalog = CostCatalogFactory('montreal_catalog').catalog
content = catalog.entries()
for building in city.buildings:
building_volume = 0.0
building_area = 0.0
total_opaque_area = 0.0
total_transparent_area = 0.0
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.opaque_area is not None:
total_opaque_area += thermal_boundary.opaque_area
if thermal_boundary.windows_areas is not None:
total_transparent_area += thermal_boundary.windows_areas
building_area += internal_zone.area
building_volume += internal_zone.volume
bulding_name, heating_load, cooling_load = PeakLoads(city, outputs_path, weather_format, irradiance_format)._results[0]
capital_costs_at_year_0 = CapitalCost.calculate_capital_cost(building_area, municipality, building_volume, total_opaque_area, total_transparent_area, content, heating_load, cooling_load, building.floor_area)
# end_of_life_cost = 0.0
# items = []
# fuels = city.fuels
# concepts = []
# LifeCycleCosts(city, number_of_years, consumer_price_index, discount_rate, end_of_life_cost,
# capital_costs_at_year_0, items, fuels, concepts).calculate_capital_costs

View File

@ -0,0 +1,409 @@
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File diff suppressed because it is too large Load Diff

View File

@ -0,0 +1,9 @@
city name: Kelowna
name: BLD109438
year of construction: 2006
function: residential
floor area: 272.08909526467323
storeys: 1
heated_volume: 995.0080033651222
volume: 1170.597651017791
1 city name: Kelowna
2 name: BLD109438
3 year of construction: 2006
4 function: residential
5 floor area: 272.08909526467323
6 storeys: 1
7 heated_volume: 995.0080033651222
8 volume: 1170.597651017791

View File

@ -0,0 +1,2 @@
Peak loads in W
BLD109438, 33882.32144209778, -10503.805886306322
1 Peak loads in W
2 BLD109438, 33882.32144209778, -10503.805886306322