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Merge pull request 'fix: small bug is cooling simulation and operational income are fixed' (#15) from cooling_system_simulation_fix into main

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Reviewed-on: https://nextgenerations-cities.encs.concordia.ca/gitea/s_ranjbar/energy_system_modelling_workflow/pulls/15
This commit is contained in:
Saeed Ranjbar 2024-07-22 17:43:18 -04:00
commit af988e28ed
7 changed files with 86 additions and 19 deletions
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2
hub/catalog_factories/cost/montreal_complete_cost_catalog.py
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@ -48,7 +48,7 @@ class MontrealNewCatalog(Catalog):
construction = float(archetype['incomes']['subsidies']['construction']['#text'])
hvac = float(archetype['incomes']['subsidies']['hvac']['#text'])
photovoltaic_system = float(archetype['incomes']['subsidies']['photovoltaic']['#text'])
electricity_exports = float(archetype['incomes']['electricity_export']['#text']) / 1000 / 3600
electricity_exports = float(archetype['incomes']['electricity_export']['#text'])
reduction_tax = float(archetype['incomes']['tax_reduction']['#text']) / 100
income = Income(construction_subsidy=construction,
hvac_subsidy=hvac,

3
scripts/costs/total_operational_incomes.py
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@ -33,12 +33,11 @@ class TotalOperationalIncomes(CostBase):
onsite_electricity_production = 0
else:
onsite_electricity_production = building.onsite_electrical_production[cte.YEAR][0]
for year in range(1, self._configuration.number_of_years + 1):
price_increase_electricity = math.pow(1 + self._configuration.electricity_price_index, year)
price_export = archetype.income.electricity_export # to account for unit change
self._yearly_operational_incomes.loc[year, 'Incomes electricity'] = (
(onsite_electricity_production / cte.WATTS_HOUR_TO_JULES) * price_export * price_increase_electricity
(onsite_electricity_production / 3.6e6) * price_export * price_increase_electricity
)
self._yearly_operational_incomes.fillna(0, inplace=True)

21
scripts/energy_system_retrofit_report.py
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@ -95,7 +95,6 @@ class EnergySystemRetrofitReport:
ax.bar(months, values, color=color, width=0.6, zorder=2)
ax.grid(which="major", axis='x', color='#DAD8D7', alpha=0.5, zorder=1)
ax.grid(which="major", axis='y', color='#DAD8D7', alpha=0.5, zorder=1)
ax.set_xlabel('Month', fontsize=12, labelpad=10)
ax.set_ylabel(ylabel, fontsize=14, labelpad=10)
ax.set_title(title, fontsize=14, weight='bold', alpha=.8, pad=40)
ax.xaxis.set_major_locator(MaxNLocator(integer=True))
@ -444,6 +443,8 @@ class EnergySystemRetrofitReport:
retrofitted_opex = 0
retrofitted_maintenance = 0
retrofitted_end_of_life = 0
current_status_operational_income = 0
retrofitted_operational_income = 0
for building in self.city.buildings:
current_status_capex += self.current_status_lcc[f'{building.name}']['capital_cost_per_sqm']
@ -454,25 +455,25 @@ class EnergySystemRetrofitReport:
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_operational_income += self.current_status_lcc[f'{building.name}']['operational_income_per_sqm']
retrofitted_operational_income += self.retrofitted_lcc[f'{building.name}']['operational_income_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),
'Operational Cost': (current_status_opex - current_status_operational_income) / 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)
'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),
'Operational Cost': (retrofitted_opex - retrofitted_operational_income) / len(self.city.buildings),
'Maintenance Cost': retrofitted_maintenance / len(self.city.buildings),
'End of Life Cost': retrofitted_end_of_life / 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']
colors = ['#2196f3', '#ff5a5f', '#4caf50', '#ffc107'] # Added new color
# Data preparation
bar_width = 0.35
@ -482,8 +483,8 @@ class EnergySystemRetrofitReport:
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)):
bottom = np.zeros(len(labels))
for category, color in 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

2
scripts/energy_system_retrofit_results.py
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@ -104,7 +104,7 @@ def consumption_data(city):
dhw_demand += building.domestic_hot_water_heat_demand[cte.MONTH][i] / 3.6e6
lighting_appliance_demand += building.lighting_electrical_demand[cte.MONTH][i] / 3.6e6
heating_consumption += building.heating_consumption[cte.MONTH][i] / 3.6e6
if building.cooling_demand[cte.YEAR][0] == 0:
if building.cooling_consumption[cte.YEAR][0] == 0:
cooling_consumption += building.cooling_demand[cte.MONTH][i] / (3.6e6 * 2)
else:
cooling_consumption += building.cooling_consumption[cte.MONTH][i] / 3.6e6

8
scripts/random_assignation.py
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@ -15,8 +15,8 @@ from hub.city_model_structure.building import Building
energy_systems_format = 'montreal_custom'
# parameters:
residential_systems_percentage = {'system 1 gas': 44,
'system 1 electricity': 6,
residential_systems_percentage = {'system 1 gas': 100,
'system 1 electricity': 0,
'system 2 gas': 0,
'system 2 electricity': 0,
'system 3 and 4 gas': 0,
@ -25,8 +25,8 @@ residential_systems_percentage = {'system 1 gas': 44,
'system 5 electricity': 0,
'system 6 gas': 0,
'system 6 electricity': 0,
'system 8 gas': 44,
'system 8 electricity': 6}
'system 8 gas': 0,
'system 8 electricity': 0}
residential_new_systems_percentage = {'PV+ASHP+GasBoiler+TES': 0,
'PV+4Pipe+DHW': 100,

2
scripts/system_simulation_models/archetype13.py
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@ -190,7 +190,7 @@ class Archetype13:
t_ret[0] = 13
for i in range(1, len(demand)):
if demand[i] > 0:
if demand[i] > 0.15 * self._cooling_peak_load:
m[i] = hp.nominal_cooling_output / (cte.WATER_HEAT_CAPACITY * 5)
if t_ret[i - 1] >= 13:
if demand[i] < 0.25 * self._cooling_peak_load:

67
simulation_result_test.py Normal file
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@ -0,0 +1,67 @@
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, 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, 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)
geojson_file_path = input_files_path / 'output_buildings.geojson'
output_path = (Path(__file__).parent / 'out_files').resolve()
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
ConstructionFactory('nrcan', city).enrich()
UsageFactory('nrcan', city).enrich()
WeatherFactory('epw', city).enrich()
energy_plus_workflow(city, energy_plus_output_path)
random_assignation.call_random(city.buildings, random_assignation.residential_systems_percentage)
EnergySystemsFactory('montreal_custom', city).enrich()
SystemSizing(city.buildings).montreal_custom()
for i in range(12):
monthly_cooling = 0
for building in city.buildings:
monthly_cooling += building.cooling_consumption[cte.MONTH][i] / (cte.WATTS_HOUR_TO_JULES * 1000)
print(monthly_cooling)
random_assignation.call_random(city.buildings, random_assignation.residential_new_systems_percentage)
EnergySystemsFactory('montreal_future', city).enrich()
for building in city.buildings:
if building.energy_systems_archetype_name == 'PV+4Pipe+DHW':
EnergySystemsSimulationFactory('archetype13', building=building, output_path=simulation_results_path).enrich()
for i in range(12):
monthly_cooling = 0
for building in city.buildings:
monthly_cooling += building.cooling_consumption[cte.MONTH][i] / (cte.WATTS_HOUR_TO_JULES * 1000)
print(monthly_cooling)