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Author SHA1 Message Date
jgavalda
01cd52b29e Change of minimal.idf to include monthly summary of data to be able to compare with MEP. 
Commenting the EP-Workflow to solve the error given by the output reader. To be solved with Koa
 2023-04-04 17:59:19 -04:00
jgavalda
e17578bcba Revision of infiltration parameters 2023-03-31 12:25:07 -04:00
jgavalda
4ea93230eb Changes hub to incorporate change of units in infiltration 2023-03-31 08:28:49 -04:00
21 changed files with 1308613 additions and 6973 deletions
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65
README.md
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@ -1,25 +1,13 @@
# monthly_energy_balance_workflow
This tool calculates the monthly energy balance for each building in a given region.
It provides as results the energy demand and consumption separated in:
- Heating
- Cooling
- Domestic Hot Water
Also, electrical demand of:
- Lighting
- Other appliances
And heating and cooling peak loads.
All these results are provided both, monthly a yearly based.
The following assumptions are taken:
- No building in the region have attics
- All buildings have basement but those are not heated
- The construction details come from nrcan
- The usage details come from nrcan
- The system details come from the Montreal Custom catalog
- The construction details come from nrel
- The usage details come from comnet
- The heated volume is 85% of the total volume, assuming that the rest is occupied by internal walls
#### Dependencies
@ -30,3 +18,50 @@ You will need to install the following dependencies in your computer in order to
+ Simplified Radiosity Algorithm (mail to: guillermo.gutierrezmorote@concordia.ca)
After installing these tools you should include their paths in Path.
## installation
##### Linux / Mac
Open a terminal and run the following commands.
```
$ mkdir monthly_enery_balance_workflow
$ cd monthly_enery_balance_workflow
$ git clone https://binarycat.org/git/PMAU/monthly_enery_balance_workflow.git
MISSING CONNECTING TO HUB, SIMLPIFIED_RADIOSITY_ALGORITHM AND MONTHLYENERGYBALANCE!!!!!!!!!
$ python -m pip install -r ../requirements.txt
```
##### Windows
Open a terminal and run the following commands.
```
c:\> mkdir monthly_enery_balance_workflow
c:\> cd monthly_enery_balance_workflow
c:\> git clone https://binarycat.org/git/PMAU/monthly_enery_balance_workflow.git
MISSING CONNECTING TO HUB, SIMLPIFIED_RADIOSITY_ALGORITHM AND MONTHLYENERGYBALANCE!!!!!!!!!
c:\> python.exe -m pip install -r ../requirements.txt
```
#### usage
##### Linux / Mac
Open a terminal and run the following command
```
$ python main.py
```
##### Windows
Open a terminal and run the following command.
```
c:\> python.exe main.py
```

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311
input_files/selected_building_9526.geojson Normal file
View File

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2473
input_files/summerschool_all_buildings.geojson
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294
input_files/summerschool_one_building.geojson
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2473
input_files/test_buildings.geojson
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97
main.py
View File

@ -3,68 +3,63 @@ from pathlib import Path
from hub.imports.geometry_factory import GeometryFactory
from hub.imports.construction_factory import ConstructionFactory
from hub.imports.usage_factory import UsageFactory
from hub.imports.weather_factory import WeatherFactory
from hub.helpers.dictionaries import Dictionaries
from hub.imports.energy_systems_factory import EnergySystemsFactory
import hub.helpers.constants as cte
from results import Results
from monthly_energy_balance_engine import MonthlyEnergyBalanceEngine
from sra_engine import SraEngine
try:
file_path = (Path(__file__).parent / 'input_files' / 'output_buildings.geojson')
construction_format = 'nrcan'
usage_format = 'nrcan'
energy_systems_format = 'montreal_custom'
#try:
file_path = (Path(__file__).parent / 'input_files' / 'selected_building_1724.geojson')
climate_reference_city = 'Montreal'
weather_file = 'CAN_PQ_Montreal.Intl.AP.716270_CWEC.epw'
weather_format = 'epw'
construction_format = 'nrcan'
usage_format = 'nrcan'
attic_heated_case = 0
basement_heated_case = 1
out_path = (Path(__file__).parent / 'output_files')
tmp_folder = (Path(__file__).parent / 'tmp')
out_path = (Path(__file__).parent / 'output_files')
tmp_folder = (Path(__file__).parent / 'tmp')
print('[simulation start]')
city = GeometryFactory('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
print('[simulation start]')
city = GeometryFactory('geojson',
path=file_path,
height_field='heightmax',
year_of_construction_field='ANNEE_CONS',
function_field='CODE_UTILI',
function_to_hub=Dictionaries().montreal_function_to_hub_function).city
city.climate_reference_city = climate_reference_city
city.climate_file = (tmp_folder / f'{climate_reference_city}.cli').resolve()
print(f'city created from {file_path}')
WeatherFactory(weather_format, city, file_name=weather_file).enrich()
print('enrich weather... done')
ConstructionFactory(construction_format, city).enrich()
print('enrich constructions... done')
UsageFactory(usage_format, city).enrich()
print('enrich usage... done')
print(f'city created from {file_path}')
ConstructionFactory(construction_format, city).enrich()
print('enrich constructions... done')
UsageFactory(usage_format, city).enrich()
print('enrich usage... done')
i = 1
x = len(city.buildings)
for building in city.buildings:
if i < x:
building.energy_systems_archetype_name = 'system 1 gas'
else:
building.energy_systems_archetype_name = 'system 6 gas'
i = i + 1
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, weather_file)
# Assign radiation to the city
print(' sra processed...')
print('exporting:')
SraEngine(city, tmp_folder)
print(' sra processed...')
MonthlyEnergyBalanceEngine(city, tmp_folder)
print(' insel processed...')
for building in city.buildings:
building.attic_heated = attic_heated_case
building.basement_heated = basement_heated_case
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]
results = Results(city, out_path)
results.print()
print('importing results:')
results = Results(city, out_path)
results.print()
print('results printed...')
print('print results...')
print('[simulation end]')
print('[simulation end]')
except Exception as ex:
print(ex)
print('error: ', ex)
print('[simulation abort]')
#except Exception as ex:
# print(ex)
# print('error: ', ex)
#print('[simulation abort]')

3
monthly_energy_balance_engine.py
View File

@ -15,7 +15,7 @@ class MonthlyEnergyBalanceEngine:
self._file_path = file_path
EnergyBuildingsExportsFactory('insel_monthly_energy_balance', self._city, self._file_path).export()
self._run()
ResultFactory('insel_monthly_energy_balance', self._city, self._file_path).enrich()
ResultFactory('insel_meb', self._city, self._file_path).enrich()
def _run(self):
"""
@ -27,3 +27,4 @@ class MonthlyEnergyBalanceEngine:
subprocess.run(['insel', str(insel_file)], stdout=subprocess.DEVNULL)
except (SubprocessError, TimeoutExpired, CalledProcessError) as error:
raise Exception(error)

144
results.py
View File

@ -9,125 +9,34 @@ class Results:
self._path = path
def print(self):
print_results = None
file = 'city name: ' + self._city.name + '\n'
for building in self._city.buildings:
if cte.MONTH in building.heating_demand.keys():
heating_results = building.heating_demand[cte.MONTH]
if cte.MONTH in building.heating.keys():
heating_results = building.heating[cte.MONTH].rename(columns={cte.INSEL_MEB: f'{building.name} heating Wh'})
cooling_results = building.cooling[cte.MONTH].rename(columns={cte.INSEL_MEB: f'{building.name} cooling Wh'})
lighting_results = building.lighting_electrical_demand[cte.MONTH]\
.rename(columns={cte.INSEL_MEB: f'{building.name} lighting electrical demand Wh'})
appliances_results = building.appliances_electrical_demand[cte.MONTH]\
.rename(columns={cte.INSEL_MEB: f'{building.name} appliances electrical demand Wh'})
dhw_results = building.domestic_hot_water_heat_demand[cte.MONTH]\
.rename(columns={cte.INSEL_MEB: f'{building.name} domestic hot water demand Wh'})
else:
heating_results = [None] * 12
if cte.MONTH in building.cooling_demand.keys():
cooling_results = building.cooling_demand[cte.MONTH]
array = [None] * 12
heating_results = pd.DataFrame(array, columns=[f'{building.name} heating Wh'])
cooling_results = pd.DataFrame(array, columns=[f'{building.name} cooling Wh'])
lighting_results = pd.DataFrame(array, columns=[f'{building.name} lighting electrical demand Wh'])
appliances_results = pd.DataFrame(array, columns=[f'{building.name} appliances electrical demand Wh'])
dhw_results = pd.DataFrame(array, columns=[f'{building.name} domestic hot water demand Wh'])
if print_results is None:
print_results = heating_results
else:
cooling_results = [None] * 12
if cte.MONTH in building.lighting_electrical_demand.keys():
lighting_results = building.lighting_electrical_demand[cte.MONTH]
else:
lighting_results = [None] * 12
if cte.MONTH in building.appliances_electrical_demand.keys():
appliances_results = building.appliances_electrical_demand[cte.MONTH]
else:
appliances_results = [None] * 12
if cte.MONTH in building.domestic_hot_water_heat_demand.keys():
dhw_results = building.domestic_hot_water_heat_demand[cte.MONTH]
else:
dhw_results = [None] * 12
if cte.MONTH in building.heating_consumption.keys():
heating_consumption_results = building.heating_consumption[cte.MONTH]
else:
heating_consumption_results = [None] * 12
if cte.MONTH in building.cooling_consumption.keys():
cooling_consumption_results = building.cooling_consumption[cte.MONTH]
else:
cooling_consumption_results = [None] * 12
if cte.MONTH in building.domestic_hot_water_consumption.keys():
dhw_consumption_results = building.domestic_hot_water_consumption[cte.MONTH]
else:
dhw_consumption_results = [None] * 12
if cte.MONTH in building.heating_peak_load.keys():
heating_peak_load_results = building.heating_peak_load[cte.MONTH]
else:
heating_peak_load_results = [None] * 12
if cte.MONTH in building.cooling_peak_load.keys():
cooling_peak_load_results = building.cooling_peak_load[cte.MONTH]
else:
cooling_peak_load_results = [None] * 12
heating = 0
cooling = 0
for system in building.energy_systems:
for demand_type in system.demand_types:
if demand_type == cte.HEATING:
heating = 1
if demand_type == cte.COOLING:
cooling = 1
if cte.MONTH in building.heating_peak_load.keys() and cte.MONTH in building.cooling_peak_load.keys():
peak_lighting = 0
peak_appliances = 0
thermal_zone = building.thermal_zones_from_internal_zones[0]
lighting = thermal_zone.lighting
for schedule in lighting.schedules:
for value in schedule.values:
if value * lighting.density * thermal_zone.total_floor_area > peak_lighting:
peak_lighting = value * lighting.density * thermal_zone.total_floor_area
appliances = thermal_zone.appliances
for schedule in appliances.schedules:
for value in schedule.values:
if value * appliances.density * thermal_zone.total_floor_area > peak_appliances:
peak_appliances = value * appliances.density * thermal_zone.total_floor_area
monthly_electricity_peak = [0.9 * peak_lighting + 0.7 * peak_appliances] * 12
conditioning_peak = []
for i, value in enumerate(building.heating_peak_load[cte.MONTH]):
if cooling * building.cooling_peak_load[cte.MONTH][i] > heating * value:
conditioning_peak.append(cooling * building.cooling_peak_load[cte.MONTH][i])
else:
conditioning_peak.append(heating * value)
monthly_electricity_peak[i] += 0.8 * conditioning_peak[i]
electricity_peak_load_results = monthly_electricity_peak
else:
electricity_peak_load_results = [None] * 12
if cte.MONTH in building.onsite_electrical_production.keys():
monthly_onsite_electrical_production = building.onsite_electrical_production[cte.MONTH]
onsite_electrical_production = monthly_onsite_electrical_production
else:
onsite_electrical_production = [None] * 12
if cte.MONTH in building.distribution_systems_electrical_consumption.keys():
extra_electrical_consumption = building.distribution_systems_electrical_consumption[cte.MONTH]
else:
extra_electrical_consumption = [None] * 12
columns_names = [f'{building.name} heating demand J',
f'{building.name} cooling demand J',
f'{building.name} lighting demand J',
f'{building.name} appliances demand J',
f'{building.name} domestic hot water demand J',
f'{building.name} heating consumption J',
f'{building.name} cooling consumption J',
f'{building.name} domestic hot water consumption J',
f'{building.name} heating peak load W',
f'{building.name} cooling peak load W',
f'{building.name} electricity peak load W',
f'{building.name} onsite electrical production J',
f'{building.name} extra electrical consumption J'
]
print_results = pd.DataFrame([heating_results,
cooling_results,
lighting_results,
appliances_results,
dhw_results,
heating_consumption_results,
cooling_consumption_results,
dhw_consumption_results,
heating_peak_load_results,
cooling_peak_load_results,
electricity_peak_load_results,
onsite_electrical_production,
extra_electrical_consumption]).T
print_results.columns = columns_names
print_results = pd.concat([print_results, heating_results], axis='columns')
print_results = pd.concat([print_results,
cooling_results,
lighting_results,
appliances_results,
dhw_results], axis='columns')
file += '\n'
file += f'name: {building.name}\n'
file += f'year of construction: {building.year_of_construction}\n'
@ -137,10 +46,11 @@ class Results:
file += f'storeys: {int(building.eave_height / building.average_storey_height)}\n'
else:
file += f'storeys: n/a\n'
file += f'heated_volume: {0.85 * building.volume}\n'
file += f'volume: {building.volume}\n'
full_path_results = Path(self._path / f'demand_{building.name}.csv').resolve()
print_results.to_csv(full_path_results, na_rep='null')
full_path_results = Path(self._path / 'demand.csv').resolve()
print_results.to_csv(full_path_results, na_rep='null')
full_path_metadata = Path(self._path / 'metadata.csv').resolve()
with open(full_path_metadata, 'w') as metadata_file:
metadata_file.write(file)

16
sra_engine.py
View File

@ -7,19 +7,21 @@ from hub.imports.results_factory import ResultFactory
class SraEngine:
def __init__(self, city, output_file_path):
def __init__(self, city, file_path, output_file_path, weather_file):
"""
SRA class
:param city: City
:param file_path: _sra.xml file path
:param output_file_path: path to output the sra calculation
"""
self._city = city
self._file_path = file_path
self._output_file_path = output_file_path
self._weather_file = weather_file
if platform.system() == 'Linux':
self._executable = 'sra'
self._executable = 'citysim_sra'
elif platform.system() == 'Windows':
self._executable = 'sra.exe'
ExportsFactory('sra', self._city, output_file_path).export()
self._executable = 'shortwave_integer'
ExportsFactory('sra', self._city, output_file_path, weather_file=self._weather_file, weather_format='epw').export()
self._run()
ResultFactory('sra', self._city, output_file_path).enrich()
@ -28,8 +30,6 @@ class SraEngine:
Calls the software
"""
try:
subprocess.run([self._executable,
(self._output_file_path / f'{self._city.name}_sra.xml')],
stdout=subprocess.DEVNULL)
subprocess.run([self._executable, str(self._file_path)], stdout=subprocess.DEVNULL)
except (SubprocessError, TimeoutExpired, CalledProcessError) as error:
raise Exception(error)

0
test_problems
View File