Incorporation of outputs of all the variables in excel, and pandas dataframe data for yearly values in the cashflow (only capital and reposition, pending operational, end of life and maintenance)
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@ -2,17 +2,19 @@
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LifeCycleCosts calculates the life cycle costs of one building
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SPDX - License - Identifier: LGPL - 3.0 - or -later
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Copyright © 2022 Project Author Pilar Monsalvete Alvarez de Uribarri pilar_monsalvete@concordia.ca
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Project contributor 2023 Author Oriol Gavaldà Torrellas oriol.gavalda@concordia.ca
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Project contributor © 2023 Author Oriol Gavaldà Torrellas oriol.gavalda@concordia.ca
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"""
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import math
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import pandas as pd
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import numpy as np
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from datetime import date
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import hub.helpers.constants as cte
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class LifeCycleCosts:
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def __init__(self, building, archetype, number_of_years, consumer_price_index, discount_rate,
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retrofitting_scenario, heating_scop, cooling_seer, peak_electricity_demand, factor_pv):
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retrofitting_scenario, heating_scop, cooling_seer, peak_electricity_demand, factor_pv,factor_peak_lights):
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self._building = building
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self._number_of_years = number_of_years
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self._consumer_price_index = consumer_price_index
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@ -33,6 +35,16 @@ class LifeCycleCosts:
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self._cooling_seer = cooling_seer
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self._peak_electricity_demand = peak_electricity_demand
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self._factor_pv = factor_pv
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self._peak_lights = factor_peak_lights
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#todo: revise if it works
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rng = range(40)
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self._yearly_capital_costs = pd.DataFrame(index=rng , columns=['B2010_opaque_walls', 'B2020_transparent',
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'B3010_opaque_roof','B10_superstructure',
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'D301010_photovoltaic_system','D3020_heat_generating_systems',
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'D3030_cooling_generation_systems','D3040_distribution_systems',
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'D3080_other_hvac_ahu','D5020_lighting_and_branch_wiring',
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'D_services'], dtype='float')
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self._yearly_capital_costs.replace(np.nan,0)
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def calculate_capital_costs(self):
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building = self._building
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@ -45,6 +57,7 @@ class LifeCycleCosts:
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surface_ground = 0
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total_floor_area = self._total_floor_area
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for internal_zone in building.internal_zones:
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for thermal_zone in internal_zone.thermal_zones:
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for thermal_boundary in thermal_zone.thermal_boundaries:
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@ -55,15 +68,14 @@ class LifeCycleCosts:
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elif thermal_boundary.type == 'Wall':
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surface_opaque += thermal_boundary.opaque_area * (1-thermal_boundary.window_ratio)
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surface_transparent += thermal_boundary.opaque_area * thermal_boundary.window_ratio
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print(f'total floor area {total_floor_area}')
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chapters = archetype.capital_cost
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capital_cost_skin = 0
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capital_cost_services = 0
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reposition_cost_pv = 0
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peak_heating = building.heating_peak_load[cte.YEAR]['insel'][0]
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peak_cooling = building.cooling_peak_load[cte.YEAR]['insel'][0]
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peak_heating = 0.1*self._total_floor_area
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peak_cooling = 0.1*self._total_floor_area
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if self._retrofitting_scenario == 1 or self._retrofitting_scenario == 3:
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chapter = chapters.chapter('B_shell')
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@ -72,33 +84,39 @@ class LifeCycleCosts:
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capital_cost_roof = surface_roof * chapter.item('B3010_opaque_roof').refurbishment[0]
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capital_cost_ground = surface_ground * chapter.item('B10_superstructure').refurbishment[0]
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capital_cost_skin = capital_cost_opaque+capital_cost_transparent+capital_cost_roof+capital_cost_ground
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print(f'capital cost skin {capital_cost_skin}')
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self._yearly_capital_costs.loc[0]['B2010_opaque_walls'],self._yearly_capital_costs.loc[0]['B2020_transparent'], \
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self._yearly_capital_costs.loc[0]['B3010_opaque_roof'],self._yearly_capital_costs.loc[0]['B10_superstructure'],\
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self._yearly_capital_costs.loc[0]['B_Shell']\
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=[capital_cost_opaque , capital_cost_transparent , capital_cost_roof , capital_cost_ground , capital_cost_skin]
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if self._retrofitting_scenario == 2 or self._retrofitting_scenario == 3:
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chapter = chapters.chapter('D_services')
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capital_cost_pv = surface_roof * factor_pv * chapter.item('D301010_photovoltaic_system').initial_investment[0]
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self._yearly_capital_costs.loc[0]['D301010_photovoltaic_system']=capital_cost_pv
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for year in range(1, self._number_of_years + 1):
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costs_increase = math.pow(1 + self._consumer_price_index, year) / math.pow(1 + self._discount_rate, year)
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if (year % chapter.item('D301010_photovoltaic_system').lifetime) == 0:
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reposition_cost_pv += surface_roof * factor_pv * chapter.item('D301010_photovoltaic_system').reposition[
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0] * costs_increase
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self._yearly_capital_costs.loc[year]['D301010_photovoltaic_system'] = surface_roof * \
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factor_pv * chapter.item('D301010_photovoltaic_system').reposition[0] * costs_increase
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capital_cost_heating_equipment = peak_heating \
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* chapter.item('D3020_heat_generating_systems').initial_investment[0]
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capital_cost_cooling_equipment = peak_cooling \
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* chapter.item('D3030_cooling_generation_systems').initial_investment[0]
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capital_cost_distribution_equipment = peak_cooling \
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* chapter.item('D3040_distribution_systems').initial_investment[0]
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capital_cost_other_hvac_ahu = peak_cooling * chapter.item('D3080_other_hvac_ahu').initial_investment[0]
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capital_cost_lighting = total_floor_area * factor_pv \
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capital_cost_lighting = total_floor_area * self._peak_lights \
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* chapter.item('D5020_lighting_and_branch_wiring').initial_investment[0]
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capital_cost_services = capital_cost_pv + capital_cost_heating_equipment + capital_cost_cooling_equipment\
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+ capital_cost_distribution_equipment + capital_cost_other_hvac_ahu \
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+ capital_cost_lighting
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self._yearly_capital_costs.loc[0]['D3020_heat_generating_systems'], self._yearly_capital_costs.loc[0]['D3030_cooling_generation_systems'], \
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self._yearly_capital_costs.loc[0]['D3040_distribution_systems'], self._yearly_capital_costs.loc[0]['D3080_other_hvac_ahu'], \
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self._yearly_capital_costs.loc[0]['D5020_lighting_and_branch_wiring'], self._yearly_capital_costs.loc[0]['D_services'] \
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= [capital_cost_heating_equipment, capital_cost_cooling_equipment, capital_cost_distribution_equipment,
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capital_cost_other_hvac_ahu, capital_cost_lighting, capital_cost_services]
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reposition_cost_heating_equipment = 0
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reposition_cost_cooling_equipment = 0
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@ -111,16 +129,19 @@ class LifeCycleCosts:
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if (year % chapter.item('D3020_heat_generating_systems').lifetime) == 0:
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reposition_cost_heating_equipment = peak_heating * chapter.item('D3020_heat_generating_systems').reposition[0] \
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* costs_increase
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self._yearly_capital_costs.loc[year]['D3020_heat_generating_systems'] = reposition_cost_heating_equipment
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if (year % chapter.item('D3030_cooling_generation_systems').lifetime) == 0:
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reposition_cost_cooling_equipment = peak_cooling \
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* chapter.item('D3030_cooling_generation_systems').reposition[0] \
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* costs_increase
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self._yearly_capital_costs.loc[year]['D3030_cooling_generation_systems'] = reposition_cost_cooling_equipment
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if (year % chapter.item('D3080_other_hvac_ahu').lifetime) == 0:
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reposition_cost_hvac_ahu = peak_cooling * chapter.item('D3080_other_hvac_ahu').reposition[0] * costs_increase
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self._yearly_capital_costs.loc[year]['D3080_other_hvac_ahu'] = reposition_cost_hvac_ahu
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if (year % chapter.item('D5020_lighting_and_branch_wiring').lifetime) == 0:
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reposition_cost_lighting = total_floor_area * chapter.item('D5020_lighting_and_branch_wiring').reposition[0] \
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* costs_increase
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self._yearly_capital_costs.loc[year]['D5020_lighting_and_branch_wiring'] = reposition_cost_lighting
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capital_cost_subtotal = capital_cost_skin + capital_cost_services
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capital_cost_total = capital_cost_subtotal * (1+chapters.design_allowance) * (1+chapters.overhead_and_profit)
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@ -132,6 +153,7 @@ class LifeCycleCosts:
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reposition_cost_total = reposition_cost_subtotal * (1+chapters.design_allowance) * (1+chapters.overhead_and_profit)
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life_cycle_cost_capital_total = capital_cost_total + reposition_cost_total
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self._yearly_capital_costs.fillna(0,inplace=True)
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return life_cycle_cost_capital_total
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@ -157,14 +179,16 @@ class LifeCycleCosts:
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variable_cost = 0
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total_floor_area = self._total_floor_area
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electricity_heating = building.heating[cte.YEAR]['insel'][0] / self._heating_scop
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electricity_cooling = building.cooling[cte.YEAR]['insel'][0] / self._cooling_seer
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electricity_lighting = building.lighting_electrical_demand[cte.YEAR]['insel'][0]
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domestic_hot_water_demand = building.domestic_hot_water_heat_demand[cte.YEAR]['insel'][0]
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electricity_plug_loads = building.appliances_electrical_demand[cte.YEAR]['insel'][0]
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total_electricity_consumption = electricity_cooling + electricity_heating + electricity_lighting \
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electricity_heating = building.heating[cte.YEAR]['insel meb'] / (self._heating_scop*1000)
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electricity_cooling = building.cooling[cte.YEAR]['insel meb'] / (self._cooling_seer*1000)
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electricity_lighting = building.lighting_electrical_demand['month']['insel meb'].sum()/1000
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domestic_hot_water_demand = building.domestic_hot_water_heat_demand['month']['insel meb'].sum()/1000
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electricity_plug_loads = building.appliances_electrical_demand['month']['insel meb'].sum()/1000
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total_electricity_consumption = electricity_cooling[0] + electricity_heating[0] + electricity_lighting \
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+ domestic_hot_water_demand + electricity_plug_loads
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print(f'total electricity consumption: {total_electricity_consumption}')
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peak_electricity_demand = self._peak_electricity_demand
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operational_cost_year_0 = total_electricity_consumption * archetype.operational_cost.fuels[0].variable[0]
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@ -189,14 +213,12 @@ class LifeCycleCosts:
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building = self._building
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archetype = self._archetype
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factor_pv = self._factor_pv
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surface_roof = 0
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maintenance_pv = 0
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maintenance_heating = 0
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maintenance_cooling = 0
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peak_heating = building.heating_peak_load[cte.YEAR]['insel'][0]
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peak_cooling = building.cooling_peak_load[cte.YEAR]['insel'][0]
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peak_heating = 0.1 * self._total_floor_area
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peak_cooling = 0.1 * self._total_floor_area
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for internal_zone in building.internal_zones:
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for thermal_zone in internal_zone.thermal_zones:
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147
main.py
147
main.py
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@ -8,13 +8,19 @@ import glob
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import os
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from pathlib import Path
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import sys
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import pandas as pd
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from hub.imports.construction_factory import ConstructionFactory
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from hub.helpers.dictionaries import Dictionaries
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from hub.hub_logger import logger
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from hub.imports.geometry_factory import GeometryFactory
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from hub.imports.usage_factory import UsageFactory
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from hub.imports.weather_factory import WeatherFactory
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from hub.catalog_factories.costs_catalog_factory import CostCatalogFactory
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import hub.helpers.constants as cte
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from monthly_energy_balance_engine import MonthlyEnergyBalanceEngine
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from sra_engine import SraEngine
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from life_cycle_costs import LifeCycleCosts
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@ -26,42 +32,78 @@ def _search_archetype(costs_catalog, building_function):
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return building_archetype
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raise KeyError('archetype not found')
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file_path = (Path(__file__).parent.parent/'costs_workflow'/'input_files'/'selected_building_2864.geojson')
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file_path2 = (Path(__file__).parent.parent/'costs_workflow'/'input_files'/'selected_building_2864_2.geojson')
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climate_reference_city = 'Montreal'
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weather_file = 'CAN_PQ_Montreal.Intl.AP.716270_CWEC.epw'
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weather_format = 'epw'
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construction_format = 'nrcan'
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usage_format = 'nrcan'
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attic_heated_case = 0
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basement_heated_case = 1
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tmp_folder = (Path(__file__).parent.parent/'monthly_energy_balance_workflow'/'tmp')
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out_path = (Path(__file__).parent.parent / 'costs_workflow' / 'out_files')
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files = glob.glob(f'{out_path}/*')
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for file in files:
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if file != '.gitignore':
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os.remove(file)
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number_of_years = 30
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consumer_price_index = 0.04
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discount_rate = 0.03
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peak_electricity_demand = 33
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factor_pv = 0.5
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factor_peak_lights = 0.07
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retrofitting_scenarios = [0, 1, 2, 3]
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life_cycle_results = pd.DataFrame()
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for retrofitting_scenario in retrofitting_scenarios:
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if retrofitting_scenario == 2 or retrofitting_scenario==3:
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heating_scop = 3
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cooling_seer = 4.5
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else:
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heating_scop = 1
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cooling_seer = 2.8
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if retrofitting_scenario == 0 or retrofitting_scenario == 2:
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print('[simulation start]')
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city = GeometryFactory('geojson',
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path=file_path,
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height_field='heightmax',
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year_of_construction_field='ANNEE_CONS',
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name_field='OBJECTID_12',
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year_of_construction_field='ANNEE_CONS',
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function_field='CODE_UTILI',
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function_to_hub=Dictionaries().montreal_function_to_hub_function).city
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print(f'city created from {file_path}')
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ConstructionFactory('nrcan', city).enrich()
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city.climate_reference_city = climate_reference_city
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city.climate_file = (tmp_folder / f'{climate_reference_city}.cli').resolve()
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print(f'city created from {file_path}')
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WeatherFactory(weather_format, city, file_name=weather_file).enrich()
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print('enrich weather... done')
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ConstructionFactory(construction_format, city).enrich()
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print('enrich constructions... done')
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UsageFactory(usage_format, city).enrich()
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print('enrich usage... done')
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catalog = CostCatalogFactory('montreal_custom').catalog
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print('costs catalog access... done')
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number_of_years = 30
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consumer_price_index = 0.04
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discount_rate = 0.03
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# sra + monthly running
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print('exporting:')
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sra_file = (tmp_folder / f'{city.name}_sra.xml').resolve()
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SraEngine(city, sra_file, tmp_folder, weather_file)
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# Assign radiation to the city
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print(' sra processed...')
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for building in city.buildings:
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building.heating[cte.YEAR]['insel'] = [23]
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building.cooling[cte.YEAR]['insel'] = [13]
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building.lighting_electrical_demand[cte.YEAR]['insel'] = [58]
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building.appliances_electrical_demand[cte.YEAR]['insel'] = [32]
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building.domestic_hot_water_heat_demand[cte.YEAR]['insel'] = [22]
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building.attic_heated = attic_heated_case
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building.basement_heated = basement_heated_case
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peak_electricity_demand = 33
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factor_pv = 0.5
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retrofitting_scenarios = [0, 1, 2, 3]
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MonthlyEnergyBalanceEngine(city, tmp_folder)
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for building in city.buildings:
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try:
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@ -73,25 +115,70 @@ for building in city.buildings:
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sys.stderr.write(f'Building {building.name} has unknown costs archetype for building function: '
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f'{building.function}\n')
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continue
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for retrofitting_scenario in retrofitting_scenarios:
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if retrofitting_scenario == 2 or retrofitting_scenario == 3:
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heating_scop = 3
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cooling_seer = 4.5
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else:
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heating_scop = 1
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cooling_seer = 2
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lcc = LifeCycleCosts(building, archetype, number_of_years, consumer_price_index,
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discount_rate, retrofitting_scenario, heating_scop, cooling_seer,
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peak_electricity_demand, factor_pv)
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peak_electricity_demand, factor_pv,factor_peak_lights)
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else:
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print('[simulation start]')
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city = GeometryFactory('geojson',
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path=file_path2,
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height_field='heightmax',
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name_field='OBJECTID_12',
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year_of_construction_field='ANNEE_CONS',
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function_field='CODE_UTILI',
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function_to_hub=Dictionaries().montreal_function_to_hub_function).city
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print(f'city created from {file_path}')
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city.climate_reference_city = climate_reference_city
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city.climate_file = (tmp_folder / f'{climate_reference_city}.cli').resolve()
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print(f'city created from {file_path}')
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WeatherFactory(weather_format, city, file_name=weather_file).enrich()
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print('enrich weather... done')
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ConstructionFactory(construction_format, city).enrich()
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print('enrich constructions... done')
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UsageFactory(usage_format, city).enrich()
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print('enrich usage... done')
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catalog = CostCatalogFactory('montreal_custom').catalog
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print('costs catalog access... done')
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# sra + monthly running
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print('exporting:')
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sra_file = (tmp_folder / f'{city.name}_sra.xml').resolve()
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SraEngine(city, sra_file, tmp_folder, weather_file)
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# Assign radiation to the city
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print(' sra processed...')
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for building in city.buildings:
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building.attic_heated = attic_heated_case
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building.basement_heated = basement_heated_case
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MonthlyEnergyBalanceEngine(city, tmp_folder)
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for building in city.buildings:
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try:
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function = Dictionaries().hub_function_to_montreal_custom_costs_function[building.function]
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archetype = _search_archetype(catalog, function)
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except KeyError:
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logger.error(f'Building {building.name} has unknown costs archetype for building function: '
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f'{building.function}\n')
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sys.stderr.write(f'Building {building.name} has unknown costs archetype for building function: '
|
||||
f'{building.function}\n')
|
||||
continue
|
||||
lcc = LifeCycleCosts(building, archetype, number_of_years, consumer_price_index,
|
||||
discount_rate, retrofitting_scenario, heating_scop, cooling_seer,
|
||||
peak_electricity_demand, factor_pv,factor_peak_lights)
|
||||
|
||||
total_capital_costs = lcc.calculate_capital_costs()
|
||||
print(f'total capital costs scenario {retrofitting_scenario} are {total_capital_costs}')
|
||||
end_of_life_costs = lcc.calculate_end_of_life_costs()
|
||||
print(f'end_of_life_costs scenario {retrofitting_scenario} are {end_of_life_costs}')
|
||||
total_operational_costs = lcc.calculate_total_operational_costs()
|
||||
print(f'total_operational_costs scenario {retrofitting_scenario} are {total_operational_costs}')
|
||||
total_maintenance_costs = lcc.calculate_total_maintenance_costs()
|
||||
print(f'total_maintenance_costs scenario {retrofitting_scenario} are {total_maintenance_costs}')
|
||||
life_cycle_costs = total_capital_costs + end_of_life_costs + total_operational_costs + total_maintenance_costs
|
||||
print(f'life_cycle_costs scenario {retrofitting_scenario} are {life_cycle_costs}')
|
||||
life_cycle_results[f'Scenario {retrofitting_scenario}'] = [total_capital_costs, end_of_life_costs,
|
||||
total_operational_costs, total_maintenance_costs,
|
||||
life_cycle_costs]
|
||||
life_cycle_results.index = ['total_capital_costs','end_of_life_costs', 'total_operational_costs',
|
||||
'total_maintenance_costs','life_cycle_costs']
|
||||
life_cycle_results.to_excel(Path(__file__).parent/'out_files'/'Results.xlsx', index=True)
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user