diff --git a/energy_system_retrofit.py b/energy_system_retrofit.py
index 2e49b382..b6b8cd31 100644
--- a/energy_system_retrofit.py
+++ b/energy_system_retrofit.py
@@ -1,4 +1,3 @@
-from scripts.geojson_creator import process_geojson
from pathlib import Path
import subprocess
from scripts.ep_run_enrich import energy_plus_workflow
@@ -8,57 +7,92 @@ from hub.imports.construction_factory import ConstructionFactory
from hub.imports.usage_factory import UsageFactory
from hub.imports.weather_factory import WeatherFactory
from hub.imports.results_factory import ResultFactory
-from scripts.energy_system_analysis_report import EnergySystemAnalysisReport
+from scripts.energy_system_retrofit_report import EnergySystemRetrofitReport
+from scripts.geojson_creator import process_geojson
from scripts import random_assignation
from hub.imports.energy_systems_factory import EnergySystemsFactory
from scripts.energy_system_sizing import SystemSizing
-from scripts.energy_system_retrofit_results import system_results, new_system_results
+from scripts.solar_angles import CitySolarAngles
+from scripts.pv_sizing_and_simulation import PVSizingSimulation
+from scripts.energy_system_retrofit_results import consumption_data, cost_data
from scripts.energy_system_sizing_and_simulation_factory import EnergySystemsSimulationFactory
from scripts.costs.cost import Cost
-from scripts.costs.constants import SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV, SYSTEM_RETROFIT_AND_PV
+from scripts.costs.constants import SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV, SYSTEM_RETROFIT_AND_PV, CURRENT_STATUS
import hub.helpers.constants as cte
from hub.exports.exports_factory import ExportsFactory
+from scripts.pv_feasibility import pv_feasibility
+
# Specify the GeoJSON file path
+input_files_path = (Path(__file__).parent / 'input_files')
+input_files_path.mkdir(parents=True, exist_ok=True)
geojson_file = process_geojson(x=-73.5681295982132, y=45.49218262677643, diff=0.0001)
-file_path = (Path(__file__).parent / 'input_files' / 'output_buildings.geojson')
-# Specify the output path for the PDF file
+geojson_file_path = input_files_path / 'output_buildings.geojson'
output_path = (Path(__file__).parent / 'out_files').resolve()
-# Create city object from GeoJSON file
-city = GeometryFactory('geojson',
- path=file_path,
+output_path.mkdir(parents=True, exist_ok=True)
+energy_plus_output_path = output_path / 'energy_plus_outputs'
+energy_plus_output_path.mkdir(parents=True, exist_ok=True)
+simulation_results_path = (Path(__file__).parent / 'out_files' / 'simulation_results').resolve()
+simulation_results_path.mkdir(parents=True, exist_ok=True)
+sra_output_path = output_path / 'sra_outputs'
+sra_output_path.mkdir(parents=True, exist_ok=True)
+cost_analysis_output_path = output_path / 'cost_analysis'
+cost_analysis_output_path.mkdir(parents=True, exist_ok=True)
+city = GeometryFactory(file_type='geojson',
+ path=geojson_file_path,
height_field='height',
year_of_construction_field='year_of_construction',
function_field='function',
function_to_hub=Dictionaries().montreal_function_to_hub_function).city
-# Enrich city data
ConstructionFactory('nrcan', city).enrich()
-
UsageFactory('nrcan', city).enrich()
WeatherFactory('epw', city).enrich()
-ExportsFactory('sra', city, output_path).export()
-sra_path = (output_path / f'{city.name}_sra.xml').resolve()
+ExportsFactory('sra', city, sra_output_path).export()
+sra_path = (sra_output_path / f'{city.name}_sra.xml').resolve()
subprocess.run(['sra', str(sra_path)])
-ResultFactory('sra', city, output_path).enrich()
-energy_plus_workflow(city)
+ResultFactory('sra', city, sra_output_path).enrich()
+pv_feasibility(-73.5681295982132, 45.49218262677643, 0.0001, selected_buildings=city.buildings)
+energy_plus_workflow(city, energy_plus_output_path)
+solar_angles = CitySolarAngles(city.name,
+ city.latitude,
+ city.longitude,
+ tilt_angle=45,
+ surface_azimuth_angle=180).calculate
random_assignation.call_random(city.buildings, random_assignation.residential_systems_percentage)
EnergySystemsFactory('montreal_custom', city).enrich()
SystemSizing(city.buildings).montreal_custom()
-current_system = new_system_results(city.buildings)
+current_status_energy_consumption = consumption_data(city)
+current_status_life_cycle_cost = {}
+for building in city.buildings:
+ cost_retrofit_scenario = CURRENT_STATUS
+ lcc_dataframe = Cost(building=building,
+ retrofit_scenario=cost_retrofit_scenario,
+ fuel_tariffs=['Electricity-D', 'Gas-Energir']).life_cycle
+ lcc_dataframe.to_csv(cost_analysis_output_path / f'{building.name}_current_status_lcc.csv')
+ current_status_life_cycle_cost[f'{building.name}'] = cost_data(building, lcc_dataframe, cost_retrofit_scenario)
random_assignation.call_random(city.buildings, random_assignation.residential_new_systems_percentage)
EnergySystemsFactory('montreal_future', city).enrich()
for building in city.buildings:
- EnergySystemsSimulationFactory('archetype1', building=building, output_path=output_path).enrich()
- print(building.energy_consumption_breakdown[cte.ELECTRICITY][cte.COOLING] +
- building.energy_consumption_breakdown[cte.ELECTRICITY][cte.HEATING] +
- building.energy_consumption_breakdown[cte.ELECTRICITY][cte.DOMESTIC_HOT_WATER])
-new_system = new_system_results(city.buildings)
-# EnergySystemAnalysisReport(city, output_path).create_report(current_system, new_system)
+ if 'PV' in building.energy_systems_archetype_name:
+ ghi = [x / cte.WATTS_HOUR_TO_JULES for x in building.roofs[0].global_irradiance[cte.HOUR]]
+ pv_sizing_simulation = PVSizingSimulation(building,
+ solar_angles,
+ tilt_angle=45,
+ module_height=1,
+ module_width=2,
+ ghi=ghi)
+ pv_sizing_simulation.pv_output()
+ if building.energy_systems_archetype_name == 'PV+4Pipe+DHW':
+ EnergySystemsSimulationFactory('archetype13', building=building, output_path=simulation_results_path).enrich()
+retrofitted_energy_consumption = consumption_data(city)
+retrofitted_life_cycle_cost = {}
for building in city.buildings:
- costs = Cost(building=building, retrofit_scenario=SYSTEM_RETROFIT_AND_PV).life_cycle
- costs.to_csv(output_path / f'{building.name}_lcc.csv')
- (costs.loc['global_operational_costs', f'Scenario {SYSTEM_RETROFIT_AND_PV}'].
- to_csv(output_path / f'{building.name}_op.csv'))
- costs.loc['global_capital_costs', f'Scenario {SYSTEM_RETROFIT_AND_PV}'].to_csv(
- output_path / f'{building.name}_cc.csv')
- costs.loc['global_maintenance_costs', f'Scenario {SYSTEM_RETROFIT_AND_PV}'].to_csv(
- output_path / f'{building.name}_m.csv')
\ No newline at end of file
+ cost_retrofit_scenario = SYSTEM_RETROFIT_AND_PV
+ lcc_dataframe = Cost(building=building,
+ retrofit_scenario=cost_retrofit_scenario,
+ fuel_tariffs=['Electricity-D', 'Gas-Energir']).life_cycle
+ lcc_dataframe.to_csv(cost_analysis_output_path / f'{building.name}_retrofitted_lcc.csv')
+ retrofitted_life_cycle_cost[f'{building.name}'] = cost_data(building, lcc_dataframe, cost_retrofit_scenario)
+(EnergySystemRetrofitReport(city, output_path, 'PV Implementation and System Retrofit',
+ current_status_energy_consumption, retrofitted_energy_consumption,
+ current_status_life_cycle_cost, retrofitted_life_cycle_cost).create_report())
+
diff --git a/hub/data/costs/montreal_costs_completed.xml b/hub/data/costs/montreal_costs_completed.xml
index fc23634a..6b3fc41f 100644
--- a/hub/data/costs/montreal_costs_completed.xml
+++ b/hub/data/costs/montreal_costs_completed.xml
@@ -187,7 +187,7 @@
1.5
3.6
- 0.07
+ 0.075
5
diff --git a/report_test.py b/report_test.py
deleted file mode 100644
index aa67926b..00000000
--- a/report_test.py
+++ /dev/null
@@ -1,71 +0,0 @@
-from pathlib import Path
-import subprocess
-from scripts.ep_run_enrich import energy_plus_workflow
-from hub.imports.geometry_factory import GeometryFactory
-from hub.helpers.dictionaries import Dictionaries
-from hub.imports.construction_factory import ConstructionFactory
-from hub.imports.usage_factory import UsageFactory
-from hub.imports.weather_factory import WeatherFactory
-from hub.imports.results_factory import ResultFactory
-from scripts.energy_system_retrofit_report import EnergySystemRetrofitReport
-from scripts.geojson_creator import process_geojson
-from scripts import random_assignation
-from hub.imports.energy_systems_factory import EnergySystemsFactory
-from scripts.energy_system_sizing import SystemSizing
-from scripts.solar_angles import CitySolarAngles
-from scripts.pv_sizing_and_simulation import PVSizingSimulation
-from scripts.energy_system_retrofit_results import consumption_data
-from scripts.energy_system_sizing_and_simulation_factory import EnergySystemsSimulationFactory
-from scripts.costs.cost import Cost
-from scripts.costs.constants import SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV, SYSTEM_RETROFIT_AND_PV
-import hub.helpers.constants as cte
-from hub.exports.exports_factory import ExportsFactory
-from scripts.pv_feasibility import pv_feasibility
-
-geojson_file = process_geojson(x=-73.5681295982132, y=45.49218262677643, diff=0.0001)
-file_path = (Path(__file__).parent / 'input_files' / 'output_buildings.geojson')
-output_path = (Path(__file__).parent / 'out_files').resolve()
-simulation_results_path = (Path(__file__).parent / 'out_files' / 'simulation_results').resolve()
-simulation_results_path.mkdir(parents=True, exist_ok=True)
-city = GeometryFactory(file_type='geojson',
- path=file_path,
- height_field='height',
- year_of_construction_field='year_of_construction',
- function_field='function',
- function_to_hub=Dictionaries().montreal_function_to_hub_function).city
-ConstructionFactory('nrcan', city).enrich()
-UsageFactory('nrcan', city).enrich()
-WeatherFactory('epw', city).enrich()
-ExportsFactory('sra', city, output_path).export()
-sra_path = (output_path / f'{city.name}_sra.xml').resolve()
-subprocess.run(['sra', str(sra_path)])
-ResultFactory('sra', city, output_path).enrich()
-pv_feasibility(-73.5681295982132, 45.49218262677643, 0.0001, selected_buildings=city.buildings)
-energy_plus_workflow(city)
-solar_angles = CitySolarAngles(city.name,
- city.latitude,
- city.longitude,
- tilt_angle=45,
- surface_azimuth_angle=180).calculate
-random_assignation.call_random(city.buildings, random_assignation.residential_systems_percentage)
-EnergySystemsFactory('montreal_custom', city).enrich()
-SystemSizing(city.buildings).montreal_custom()
-current_status_energy_consumption = consumption_data(city)
-random_assignation.call_random(city.buildings, random_assignation.residential_new_systems_percentage)
-EnergySystemsFactory('montreal_future', city).enrich()
-for building in city.buildings:
- if 'PV' in building.energy_systems_archetype_name:
- ghi = [x / cte.WATTS_HOUR_TO_JULES for x in building.roofs[0].global_irradiance[cte.HOUR]]
- pv_sizing_simulation = PVSizingSimulation(building,
- solar_angles,
- tilt_angle=45,
- module_height=1,
- module_width=2,
- ghi=ghi)
- pv_sizing_simulation.pv_output()
- if building.energy_systems_archetype_name == 'PV+4Pipe+DHW':
- EnergySystemsSimulationFactory('archetype13', building=building, output_path=simulation_results_path).enrich()
-retrofitted_energy_consumption = consumption_data(city)
-(EnergySystemRetrofitReport(city, output_path, 'PV Implementation and System Retrofit',
- current_status_energy_consumption, retrofitted_energy_consumption).create_report())
-
diff --git a/scripts/costs/total_operational_costs.py b/scripts/costs/total_operational_costs.py
index dc672fa1..60ed54a9 100644
--- a/scripts/costs/total_operational_costs.py
+++ b/scripts/costs/total_operational_costs.py
@@ -196,7 +196,7 @@ class TotalOperationalCosts(CostBase):
if cooling is not None:
hourly += cooling[i] / 3600
if dhw is not None:
- dhw += dhw[i] / 3600
+ hourly += dhw[i] / 3600
hourly_fuel_consumption.append(hourly)
else:
heating = None
diff --git a/scripts/costs/total_operational_incomes.py b/scripts/costs/total_operational_incomes.py
index 2a110761..66d789ed 100644
--- a/scripts/costs/total_operational_incomes.py
+++ b/scripts/costs/total_operational_incomes.py
@@ -36,11 +36,10 @@ class TotalOperationalIncomes(CostBase):
for year in range(1, self._configuration.number_of_years + 1):
price_increase_electricity = math.pow(1 + self._configuration.electricity_price_index, year)
- # todo: check the adequate assignation of price. Pilar
- price_export = archetype.income.electricity_export * cte.WATTS_HOUR_TO_JULES * 1000 # to account for unit change
+ price_export = archetype.income.electricity_export # to account for unit change
self._yearly_operational_incomes.loc[year, 'Incomes electricity'] = (
- onsite_electricity_production * price_export * price_increase_electricity
+ (onsite_electricity_production / cte.WATTS_HOUR_TO_JULES) * price_export * price_increase_electricity
)
self._yearly_operational_incomes.fillna(0, inplace=True)
- return self._yearly_operational_incomes
+ return self._yearly_operational_incomes
\ No newline at end of file
diff --git a/scripts/energy_system_retrofit_report.py b/scripts/energy_system_retrofit_report.py
index 60e82ece..fcfb764f 100644
--- a/scripts/energy_system_retrofit_report.py
+++ b/scripts/energy_system_retrofit_report.py
@@ -1,11 +1,8 @@
import os
import hub.helpers.constants as cte
import matplotlib.pyplot as plt
-import random
-import matplotlib.colors as mcolors
from matplotlib import cm
from scripts.report_creation import LatexReport
-import matplotlib as mpl
from matplotlib.ticker import MaxNLocator
import numpy as np
from pathlib import Path
@@ -14,10 +11,12 @@ import glob
class EnergySystemRetrofitReport:
def __init__(self, city, output_path, retrofit_scenario, current_status_energy_consumption_data,
- retrofitted_energy_consumption_data):
+ retrofitted_energy_consumption_data, current_status_lcc_data, retrofitted_lcc_data):
self.city = city
self.current_status_data = current_status_energy_consumption_data
self.retrofitted_data = retrofitted_energy_consumption_data
+ self.current_status_lcc = current_status_lcc_data
+ self.retrofitted_lcc = retrofitted_lcc_data
self.output_path = output_path
self.content = []
self.retrofit_scenario = retrofit_scenario
@@ -334,7 +333,7 @@ class EnergySystemRetrofitReport:
ax.spines['right'].set_linewidth(1.1)
# Plotting
- fig, axs = plt.subplots(3, 1, figsize=(20, 15), dpi=96)
+ fig, axs = plt.subplots(3, 1, figsize=(20, 25), dpi=96)
fig.suptitle(title, fontsize=16, weight='bold', alpha=.8)
plot_double_bar_chart(axs[0], 'heating', consumptions['Heating'][1], consumptions['Heating'][2],
@@ -356,11 +355,21 @@ class EnergySystemRetrofitReport:
return chart_path
-
def yearly_consumption_comparison(self):
- current_total_consumption = self.current_status_data['total_consumption']
- retrofitted_total_consumption = self.retrofitted_data['total_consumption']
-
+ current_total_consumption = round(self.current_status_data['total_consumption'], 2)
+ retrofitted_total_consumption = round(self.retrofitted_data['total_consumption'], 2)
+ text = (
+ f'The total yearly energy consumption before and after the retrofit are {current_total_consumption} MWh and '
+ f'{retrofitted_total_consumption} MWh, respectively.')
+ if retrofitted_total_consumption < current_total_consumption:
+ change = str(round((current_total_consumption - retrofitted_total_consumption) * 100 / current_total_consumption,
+ 2))
+ text += f'Therefore, the total yearly energy consumption decreased by {change} \%.'
+ else:
+ change = str(round((retrofitted_total_consumption - current_total_consumption) * 100 /
+ retrofitted_total_consumption, 2))
+ text += f'Therefore, the total yearly energy consumption increased by {change} \%. \par'
+ self.report.add_text(text)
def pv_system(self):
self.report.add_text('The first step in PV assessments is evaluating the potential of buildings for installing '
@@ -425,6 +434,85 @@ class EnergySystemRetrofitReport:
self.report.add_table(pv_output_table, caption='PV System Simulation Results', first_column_width=3)
+ def life_cycle_cost_stacked_bar(self, file_name, title):
+ # Aggregate LCC components for current and retrofitted statuses
+ current_status_capex = 0
+ current_status_opex = 0
+ current_status_maintenance = 0
+ current_status_end_of_life = 0
+ retrofitted_capex = 0
+ retrofitted_opex = 0
+ retrofitted_maintenance = 0
+ retrofitted_end_of_life = 0
+
+ for building in self.city.buildings:
+ current_status_capex += self.current_status_lcc[f'{building.name}']['capital_cost_per_sqm']
+ retrofitted_capex += self.retrofitted_lcc[f'{building.name}']['capital_cost_per_sqm']
+ current_status_opex += self.current_status_lcc[f'{building.name}']['operational_cost_per_sqm']
+ retrofitted_opex += self.retrofitted_lcc[f'{building.name}']['operational_cost_per_sqm']
+ current_status_maintenance += self.current_status_lcc[f'{building.name}']['maintenance_cost_per_sqm']
+ retrofitted_maintenance += self.retrofitted_lcc[f'{building.name}']['maintenance_cost_per_sqm']
+ current_status_end_of_life += self.current_status_lcc[f'{building.name}']['end_of_life_cost_per_sqm']
+ retrofitted_end_of_life += self.retrofitted_lcc[f'{building.name}']['end_of_life_cost_per_sqm']
+
+ current_status_lcc_components_sqm = {
+ 'Capital Cost': current_status_capex / len(self.city.buildings),
+ 'Operational Cost': current_status_opex / len(self.city.buildings),
+ 'Maintenance Cost': current_status_maintenance / len(self.city.buildings),
+ 'End of Life Cost': current_status_end_of_life / len(self.city.buildings)
+ }
+ retrofitted_lcc_components_sqm = {
+ 'Capital Cost': retrofitted_capex / len(self.city.buildings),
+ 'Operational Cost': retrofitted_opex / len(self.city.buildings),
+ 'Maintenance Cost': retrofitted_maintenance / len(self.city.buildings),
+ 'End of Life Cost': retrofitted_end_of_life / len(self.city.buildings)
+ }
+
+ labels = ['Current Status', 'Retrofitted Status']
+ categories = ['Capital Cost', 'Operational Cost', 'Maintenance Cost', 'End of Life Cost']
+ current_values = list(current_status_lcc_components_sqm.values())
+ retrofitted_values = list(retrofitted_lcc_components_sqm.values())
+ colors = ['#2196f3', '#ff5a5f', '#4caf50', '#ffc107']
+
+ # Data preparation
+ bar_width = 0.35
+ r = np.arange(len(labels))
+
+ fig, ax = plt.subplots(figsize=(12, 8), dpi=96)
+ fig.suptitle(title, fontsize=16, weight='bold', alpha=.8)
+
+ # Plotting current status data
+ bottom = np.zeros(2)
+ for i, (category, color) in enumerate(zip(categories, colors)):
+ values = [current_status_lcc_components_sqm[category], retrofitted_lcc_components_sqm[category]]
+ ax.bar(r, values, bottom=bottom, color=color, edgecolor='white', width=bar_width, label=category)
+ bottom += values
+
+ # Adding summation annotations at the top of the bars
+ for idx, (x, total) in enumerate(zip(r, bottom)):
+ ax.text(x, total, f'{total:.1f}', ha='center', va='bottom', fontsize=12, fontweight='bold')
+
+ # Adding labels, title, and grid
+ ax.set_xlabel('LCC Components', fontsize=12, labelpad=10)
+ ax.set_ylabel('Average Cost (CAD/m²)', fontsize=14, labelpad=10)
+ ax.grid(which="major", axis='y', color='#DAD8D7', alpha=0.5, zorder=1)
+ ax.set_xticks(r)
+ ax.set_xticklabels(labels, rotation=45, ha='right')
+ ax.legend()
+
+ # Adding a white background
+ fig.patch.set_facecolor('white')
+
+ # Adjusting the margins around the plot area
+ plt.subplots_adjust(left=0.05, right=0.95, top=0.9, bottom=0.2)
+
+ # Save the plot
+ chart_path = self.charts_path / f'{file_name}.png'
+ plt.savefig(chart_path, bbox_inches='tight')
+ plt.close()
+
+ return chart_path
+
def create_report(self):
# Add sections and text to the report
self.report.add_section('Overview of the Current Status in Buildings')
@@ -448,6 +536,11 @@ class EnergySystemRetrofitReport:
title='Monthly Energy Consumptions')
current_consumption_breakdown_path = self.fuel_consumption_breakdown('City_Energy_Consumption_Breakdown',
self.current_status_data)
+ retrofitted_consumption_breakdown_path = self.fuel_consumption_breakdown(
+ 'fuel_consumption_breakdown_after_retrofit',
+ self.retrofitted_data)
+ life_cycle_cost_sqm_stacked_bar_chart_path = self.life_cycle_cost_stacked_bar('lcc_per_sqm',
+ 'LCC Analysis')
# Add current state of energy demands in the city
self.report.add_subsection('Current State of Energy Demands in the City')
self.report.add_text('The total monthly energy demands in the city are shown in Figure 1. It should be noted '
@@ -487,6 +580,15 @@ class EnergySystemRetrofitReport:
self.report.add_image(str(consumption_comparison).replace('\\', '/'),
caption='Comparison of Total Monthly Energy Consumption in City Buildings',
placement='H')
+ self.yearly_consumption_comparison()
+ self.report.add_text('Figure 7 shows the fuel consumption breakdown in the area after the retrofit.')
+ self.report.add_image(str(retrofitted_consumption_breakdown_path).replace('\\', '/'),
+ caption=f'Fuel Consumption Breakdown After {self.retrofit_scenario}',
+ placement='H')
+ self.report.add_subsection('Life Cycle Cost Analysis')
+ self.report.add_image(str(life_cycle_cost_sqm_stacked_bar_chart_path).replace('\\', '/'),
+ caption='Average Life Cycle Cost Components',
+ placement='H')
# Save and compile the report
self.report.save_report()
diff --git a/scripts/energy_system_retrofit_results.py b/scripts/energy_system_retrofit_results.py
index e1082908..9d85d0d9 100644
--- a/scripts/energy_system_retrofit_results.py
+++ b/scripts/energy_system_retrofit_results.py
@@ -1,15 +1,88 @@
import hub.helpers.constants as cte
+def hourly_electricity_consumption_profile(building):
+ hourly_electricity_consumption = []
+ energy_systems = building.energy_systems
+ appliance = building.appliances_electrical_demand[cte.HOUR]
+ lighting = building.lighting_electrical_demand[cte.HOUR]
+ elec_heating = 0
+ elec_cooling = 0
+ elec_dhw = 0
+ if cte.HEATING in building.energy_consumption_breakdown[cte.ELECTRICITY]:
+ elec_heating = 1
+ if cte.COOLING in building.energy_consumption_breakdown[cte.ELECTRICITY]:
+ elec_cooling = 1
+ if cte.DOMESTIC_HOT_WATER in building.energy_consumption_breakdown[cte.ELECTRICITY]:
+ elec_dhw = 1
+ heating = None
+ cooling = None
+ dhw = None
+ if elec_heating == 1:
+ for energy_system in energy_systems:
+ if cte.HEATING in energy_system.demand_types:
+ for generation_system in energy_system.generation_systems:
+ if generation_system.fuel_type == cte.ELECTRICITY:
+ if cte.HEATING in generation_system.energy_consumption:
+ heating = generation_system.energy_consumption[cte.HEATING][cte.HOUR]
+ else:
+ if len(energy_system.generation_systems) > 1:
+ heating = [x / 2 for x in building.heating_consumption[cte.HOUR]]
+ else:
+ heating = building.heating_consumption[cte.HOUR]
+ if elec_dhw == 1:
+ for energy_system in energy_systems:
+ if cte.DOMESTIC_HOT_WATER in energy_system.demand_types:
+ for generation_system in energy_system.generation_systems:
+ if generation_system.fuel_type == cte.ELECTRICITY:
+ if cte.DOMESTIC_HOT_WATER in generation_system.energy_consumption:
+ dhw = generation_system.energy_consumption[cte.DOMESTIC_HOT_WATER][cte.HOUR]
+ else:
+ if len(energy_system.generation_systems) > 1:
+ dhw = [x / 2 for x in building.domestic_hot_water_consumption[cte.HOUR]]
+ else:
+ dhw = building.domestic_hot_water_consumption[cte.HOUR]
+
+ if elec_cooling == 1:
+ for energy_system in energy_systems:
+ if cte.COOLING in energy_system.demand_types:
+ for generation_system in energy_system.generation_systems:
+ if cte.COOLING in generation_system.energy_consumption:
+ cooling = generation_system.energy_consumption[cte.COOLING][cte.HOUR]
+ else:
+ if len(energy_system.generation_systems) > 1:
+ cooling = [x / 2 for x in building.cooling_consumption[cte.HOUR]]
+ else:
+ cooling = building.cooling_consumption[cte.HOUR]
+
+ for i in range(len(building.heating_demand[cte.HOUR])):
+ hourly = 0
+ hourly += appliance[i] / 3600
+ hourly += lighting[i] / 3600
+ if heating is not None:
+ hourly += heating[i] / 3600
+ if cooling is not None:
+ hourly += cooling[i] / 3600
+ if dhw is not None:
+ hourly += dhw[i] / 3600
+ hourly_electricity_consumption.append(hourly)
+ return hourly_electricity_consumption
+
+
def consumption_data(city):
- current_status_energy_consumption_data = {}
+ energy_consumption_data = {}
for building in city.buildings:
- current_status_energy_consumption_data[f'{building.name}'] = {'heating_consumption': building.heating_consumption,
- 'cooling_consumption': building.cooling_consumption,
- 'domestic_hot_water_consumption':
- building.domestic_hot_water_consumption,
- 'energy_consumption_breakdown':
- building.energy_consumption_breakdown}
+ hourly_electricity_consumption = hourly_electricity_consumption_profile(building)
+ energy_consumption_data[f'{building.name}'] = {'heating_consumption': building.heating_consumption,
+ 'cooling_consumption': building.cooling_consumption,
+ 'domestic_hot_water_consumption':
+ building.domestic_hot_water_consumption,
+ 'energy_consumption_breakdown':
+ building.energy_consumption_breakdown,
+ 'hourly_electricity_consumption': hourly_electricity_consumption}
+ peak_electricity_consumption = 0
+ for building in energy_consumption_data:
+ peak_electricity_consumption += max(energy_consumption_data[building]['hourly_electricity_consumption'])
heating_demand_monthly = []
cooling_demand_monthly = []
dhw_demand_monthly = []
@@ -54,14 +127,50 @@ def consumption_data(city):
yearly_heating = 0
yearly_cooling = 0
yearly_dhw = 0
+ yearly_appliance = 0
+ yearly_lighting = 0
for building in city.buildings:
- yearly_heating += building.heating_consumption[cte.YEAR][0] / 3.6e6
- yearly_cooling += building.cooling_consumption[cte.YEAR][0] / 3.6e6
- yearly_dhw += building.domestic_hot_water_consumption[cte.YEAR][0] / 3.6e6
+ yearly_appliance += building.appliances_electrical_demand[cte.YEAR][0] / 3.6e9
+ yearly_lighting += building.lighting_electrical_demand[cte.YEAR][0] / 3.6e9
+ yearly_heating += building.heating_consumption[cte.YEAR][0] / 3.6e9
+ yearly_cooling += building.cooling_consumption[cte.YEAR][0] / 3.6e9
+ yearly_dhw += building.domestic_hot_water_consumption[cte.YEAR][0] / 3.6e9
- total_consumption = yearly_heating + yearly_cooling + yearly_dhw
- current_status_energy_consumption_data['monthly_demands'] = monthly_demands
- current_status_energy_consumption_data['monthly_consumptions'] = monthly_consumptions
- current_status_energy_consumption_data['total_consumption'] = total_consumption
+ total_consumption = yearly_heating + yearly_cooling + yearly_dhw + yearly_appliance + yearly_lighting
+ energy_consumption_data['monthly_demands'] = monthly_demands
+ energy_consumption_data['monthly_consumptions'] = monthly_consumptions
+ energy_consumption_data['total_consumption'] = total_consumption
+ energy_consumption_data['maximum_hourly_electricity_consumption'] = peak_electricity_consumption
- return current_status_energy_consumption_data
+ return energy_consumption_data
+
+
+def cost_data(building, lcc_dataframe, cost_retrofit_scenario):
+ total_floor_area = 0
+ for thermal_zone in building.thermal_zones_from_internal_zones:
+ total_floor_area += thermal_zone.total_floor_area
+ capital_cost = lcc_dataframe.loc['total_capital_costs_systems', f'Scenario {cost_retrofit_scenario}']
+ operational_cost = lcc_dataframe.loc['total_operational_costs', f'Scenario {cost_retrofit_scenario}']
+ maintenance_cost = lcc_dataframe.loc['total_maintenance_costs', f'Scenario {cost_retrofit_scenario}']
+ end_of_life_cost = lcc_dataframe.loc['end_of_life_costs', f'Scenario {cost_retrofit_scenario}']
+ operational_income = lcc_dataframe.loc['operational_incomes', f'Scenario {cost_retrofit_scenario}']
+ total_life_cycle_cost = capital_cost + operational_cost + maintenance_cost + end_of_life_cost + operational_income
+ specific_capital_cost = capital_cost / total_floor_area
+ specific_operational_cost = operational_cost / total_floor_area
+ specific_maintenance_cost = maintenance_cost / total_floor_area
+ specific_end_of_life_cost = end_of_life_cost / total_floor_area
+ specific_operational_income = operational_income / total_floor_area
+ specific_life_cycle_cost = total_life_cycle_cost / total_floor_area
+ life_cycle_cost_analysis = {'capital_cost': capital_cost,
+ 'capital_cost_per_sqm': specific_capital_cost,
+ 'operational_cost': operational_cost,
+ 'operational_cost_per_sqm': specific_operational_cost,
+ 'maintenance_cost': maintenance_cost,
+ 'maintenance_cost_per_sqm': specific_maintenance_cost,
+ 'end_of_life_cost': end_of_life_cost,
+ 'end_of_life_cost_per_sqm': specific_end_of_life_cost,
+ 'operational_income': operational_income,
+ 'operational_income_per_sqm': specific_operational_income,
+ 'total_life_cycle_cost': total_life_cycle_cost,
+ 'total_life_cycle_cost_per_sqm': specific_life_cycle_cost}
+ return life_cycle_cost_analysis
diff --git a/scripts/ep_run_enrich.py b/scripts/ep_run_enrich.py
index 24ee4b11..68c24c8c 100644
--- a/scripts/ep_run_enrich.py
+++ b/scripts/ep_run_enrich.py
@@ -9,10 +9,10 @@ from hub.imports.results_factory import ResultFactory
sys.path.append('./')
-def energy_plus_workflow(city):
+def energy_plus_workflow(city, output_path):
try:
# city = city
- out_path = (Path(__file__).parent.parent / 'out_files')
+ out_path = output_path
files = glob.glob(f'{out_path}/*')
# for file in files:
diff --git a/scripts/pv_feasibility.py b/scripts/pv_feasibility.py
index 00488e39..034a5efb 100644
--- a/scripts/pv_feasibility.py
+++ b/scripts/pv_feasibility.py
@@ -9,10 +9,13 @@ from hub.exports.exports_factory import ExportsFactory
def pv_feasibility(current_x, current_y, current_diff, selected_buildings):
+ input_files_path = (Path(__file__).parent.parent / 'input_files')
+ output_path = (Path(__file__).parent.parent / 'out_files').resolve()
+ sra_output_path = output_path / 'sra_outputs' / 'extended_city_sra_outputs'
+ sra_output_path.mkdir(parents=True, exist_ok=True)
new_diff = current_diff * 5
geojson_file = process_geojson(x=current_x, y=current_y, diff=new_diff, expansion=True)
- file_path = (Path(__file__).parent.parent / 'input_files' / 'output_buildings_expanded.geojson')
- output_path = (Path(__file__).parent.parent / 'out_files').resolve()
+ file_path = input_files_path / 'output_buildings.geojson'
city = GeometryFactory('geojson',
path=file_path,
height_field='height',
@@ -20,10 +23,10 @@ def pv_feasibility(current_x, current_y, current_diff, selected_buildings):
function_field='function',
function_to_hub=Dictionaries().montreal_function_to_hub_function).city
WeatherFactory('epw', city).enrich()
- ExportsFactory('sra', city, output_path).export()
- sra_path = (output_path / f'{city.name}_sra.xml').resolve()
+ ExportsFactory('sra', city, sra_output_path).export()
+ sra_path = (sra_output_path / f'{city.name}_sra.xml').resolve()
subprocess.run(['sra', str(sra_path)])
- ResultFactory('sra', city, output_path).enrich()
+ ResultFactory('sra', city, sra_output_path).enrich()
for selected_building in selected_buildings:
for building in city.buildings:
if selected_building.name == building.name:
diff --git a/scripts/system_simulation_models/archetype13.py b/scripts/system_simulation_models/archetype13.py
index 892b9f3f..77b52da6 100644
--- a/scripts/system_simulation_models/archetype13.py
+++ b/scripts/system_simulation_models/archetype13.py
@@ -377,8 +377,8 @@ class Archetype13:
self._building.domestic_hot_water_consumption[cte.HOUR] = dhw_consumption
self._building.domestic_hot_water_consumption[cte.MONTH] = (
MonthlyValues.get_total_month(self._building.domestic_hot_water_consumption[cte.HOUR]))
- self._building.domestic_hot_water_consumption[cte.YEAR] = (
- sum(self._building.domestic_hot_water_consumption[cte.MONTH]))
+ self._building.domestic_hot_water_consumption[cte.YEAR] = [
+ sum(self._building.domestic_hot_water_consumption[cte.MONTH])]
file_name = f'energy_system_simulation_results_{self._name}.csv'
with open(self._output_path / file_name, 'w', newline='') as csvfile:
output_file = csv.writer(csvfile)