s_ranjbar/summer_course_2024
2
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

complete peak loads calculation

Browse Source
This commit is contained in:
Guille Gutierrez 2023-05-01 10:37:51 -04:00
parent e6486bc598
commit 949a6c268f
7 changed files with 103 additions and 45 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

30
hub/city_model_structure/building.py
View File

@ -374,14 +374,12 @@ class Building(CityObject):
:return: dict{DataFrame(float)}
"""
results = {}
if self.heating[cte.HOUR] is not None:
monthly_values = pl.peak_loads_from_hourly(self.heating[cte.HOUR][0])
results[cte.MONTH] = pd.DataFrame(monthly_values)
yearly_value = 0
for month_value in monthly_values:
if month_value >= yearly_value:
yearly_value = month_value
results[cte.YEAR] = yearly_value
if cte.HOUR in self.heating:
monthly_values = pl.peak_loads_from_hourly(self.heating[cte.HOUR][next(iter(self.heating[cte.HOUR]))].values)
else:
monthly_values = pl.heating_peak_loads_from_methodology(self)
results[cte.MONTH] = pd.DataFrame(monthly_values, columns=['heating peak loads'])
results[cte.YEAR] = pd.DataFrame([max(monthly_values)], columns=['heating peak loads'])
return results
@property
@ -391,15 +389,13 @@ class Building(CityObject):
:return: dict{DataFrame(float)}
"""
results = {}
if self.heating[cte.HOUR] is not None:
monthly_values = pl.peak_loads_from_hourly(self.cooling[cte.HOUR][0])
results[cte.MONTH] = pd.DataFrame(monthly_values)
yearly_value = 0
for month_value in monthly_values:
if month_value >= yearly_value:
yearly_value = month_value
results[cte.YEAR] = yearly_value
if cte.HOUR in self.cooling:
monthly_values = pl.peak_loads_from_hourly(self.cooling[cte.HOUR][next(iter(self.cooling[cte.HOUR]))])
else:
monthly_values = pl.cooling_peak_loads_from_methodology(self)
results[cte.MONTH] = pd.DataFrame(monthly_values, columns=['cooling peak loads'])
results[cte.YEAR] = pd.DataFrame([max(monthly_values)], columns=['cooling peak loads'])
return results
@property
def eave_height(self):

1
hub/exports/exports_factory.py
View File

@ -79,7 +79,6 @@ class ExportsFactory:
Export the city to Simplified Radiosity Algorithm xml format
:return: None
"""
print(self._weather_format, self._weather_file)
return SimplifiedRadiosityAlgorithm(self._city,
(self._path / f'{self._city.name}_sra.xml'),
self._weather_file,

1
hub/exports/formats/simplified_radiosity_algorithm.py
View File

@ -36,7 +36,6 @@ class SimplifiedRadiosityAlgorithm:
self._city = city
self._city.climate_file = str((Path(file_name).parent / f'{city.name}.cli').resolve())
self._city.climate_reference_city = city.location
print(city.location)
self._target_buildings = target_buildings
self._weather_format = weather_format
self._weather_file = weather_file

50
hub/helpers/peak_loads.py
View File

@ -1,6 +1,9 @@
import constants as cte
import math
_MONTH_STARTING_HOUR = [0, 744, 1416, 2160, 2880, 3624, 4344, 5088, 5832, 6552, 7296, 8016]
import hub.helpers.constants as cte
from hub.helpers.peak_calculation.loads_calculation import LoadsCalculation
_MONTH_STARTING_HOUR = [0, 744, 1416, 2160, 2880, 3624, 4344, 5088, 5832, 6552, 7296, 8016, math.inf]
def peak_loads_from_hourly(hourly_values):
month = 1
@ -10,18 +13,14 @@ def peak_loads_from_hourly(hourly_values):
month += 1
if value > peaks[month-1]:
peaks[month-1] = value
print(peaks)
return peaks
def peak_loads_from_methodology(building):
def heating_peak_loads_from_methodology(building):
monthly_heating_loads = []
monthly_cooling_loads = []
ambient_temperature = building.external_temperature[cte.HOUR][self._weather_format]
ambient_temperature = building.external_temperature[cte.HOUR]['epw']
for month in range(0, 12):
ground_temperature = building.ground_temperature[cte.MONTH]['2'][month]
heating_ambient_temperature = 100
cooling_ambient_temperature = -100
cooling_calculation_hour = -1
start_hour = _MONTH_STARTING_HOUR[month]
end_hour = 8760
if month < 11:
@ -30,30 +29,43 @@ def peak_loads_from_methodology(building):
temperature = ambient_temperature[hour]
if temperature < heating_ambient_temperature:
heating_ambient_temperature = temperature
if temperature > cooling_ambient_temperature:
cooling_ambient_temperature = temperature
cooling_calculation_hour = hour
loads = LoadsCalculation(building)
heating_load_transmitted = loads.get_heating_transmitted_load(heating_ambient_temperature, ground_temperature)
heating_load_ventilation_sensible = loads.get_heating_ventilation_load_sensible(heating_ambient_temperature)
heating_load_ventilation_latent = 0
heating_load = heating_load_transmitted + heating_load_ventilation_sensible + heating_load_ventilation_latent
if heating_load < 0:
heating_load = 0
monthly_heating_loads.append(heating_load)
return monthly_heating_loads
def cooling_peak_loads_from_methodology(building):
monthly_cooling_loads = []
ambient_temperature = building.external_temperature[cte.HOUR]['epw']
for month in range(0, 12):
ground_temperature = building.ground_temperature[cte.MONTH]['2'][month]
cooling_ambient_temperature = -100
cooling_calculation_hour = -1
start_hour = _MONTH_STARTING_HOUR[month]
end_hour = 8760
if month < 11:
end_hour = _MONTH_STARTING_HOUR[month + 1]
for hour in range(start_hour, end_hour):
temperature = ambient_temperature[hour]
if temperature > cooling_ambient_temperature:
cooling_ambient_temperature = temperature
cooling_calculation_hour = hour
loads = LoadsCalculation(building)
cooling_load_transmitted = loads.get_cooling_transmitted_load(cooling_ambient_temperature, ground_temperature)
cooling_load_renovation_sensible = loads.get_cooling_ventilation_load_sensible(cooling_ambient_temperature)
cooling_load_internal_gains_sensible = loads.get_internal_load_sensible()
cooling_load_radiation = loads.get_radiation_load(self._irradiance_format, cooling_calculation_hour)
cooling_load_radiation = loads.get_radiation_load('sra', cooling_calculation_hour)
cooling_load_sensible = cooling_load_transmitted + cooling_load_renovation_sensible - cooling_load_radiation \
- cooling_load_internal_gains_sensible
cooling_load_latent = 0
cooling_load = cooling_load_sensible + cooling_load_latent
if heating_load < 0:
heating_load = 0
if cooling_load > 0:
cooling_load = 0
monthly_heating_loads.append(heating_load)
monthly_cooling_loads.append(cooling_load)
{'monthly heating peak load': monthly_heating_loads,
'monthly cooling peak load': monthly_cooling_loads}
monthly_cooling_loads.append(abs(cooling_load))
return monthly_cooling_loads

1
hub/imports/weather/epw_weather_parameters.py
View File

@ -71,7 +71,6 @@ class EpwWeatherParameters:
except SystemExit:
sys.stderr.write(f'Error: wrong formatting of weather file {self._path}\n')
sys.exit()
for building in self._city.buildings:
building.ground_temperature[cte.MONTH] = ground_temperature
ground_temperature = {}

4
hub/imports/weather_factory.py
View File

@ -52,3 +52,7 @@ class WeatherFactory:
:return: None
"""
getattr(self, self._handler, lambda: None)()
def enrich_debug(self):
_path = Path(self._base_path / 'epw').resolve()
return EpwWeatherParameters(self._city, _path, self._file_name)

61
hub/unittests/test_imports.py
View File

@ -7,16 +7,17 @@ Project Coder Guille Gutierrez guillermo.gutierrezmorote@concordia.ca
import subprocess
from pathlib import Path
from unittest import TestCase
import pandas as pd
from hub.imports.geometry_factory import GeometryFactory
import hub.helpers.constants as cte
from hub.exports.energy_building_exports_factory import EnergyBuildingsExportsFactory
from hub.exports.exports_factory import ExportsFactory
from hub.helpers.dictionaries import Dictionaries
from hub.imports.construction_factory import ConstructionFactory
from hub.imports.usage_factory import UsageFactory
from hub.exports.exports_factory import ExportsFactory
from hub.exports.energy_building_exports_factory import EnergyBuildingsExportsFactory
from hub.imports.geometry_factory import GeometryFactory
from hub.imports.results_factory import ResultFactory
import hub.helpers.constants as cte
from hub.city_model_structure.city import City
from hub.imports.usage_factory import UsageFactory
class TestImports(TestCase):
@ -65,3 +66,51 @@ class TestImports(TestCase):
self.assertIsNotNone(building.cooling[cte.MONTH][cte.INSEL_MEB])
self.assertIsNotNone(building.heating[cte.YEAR][cte.INSEL_MEB])
self.assertIsNotNone(building.cooling[cte.YEAR][cte.INSEL_MEB])
def test_peak_loads(self):
# todo: this is not technically a import
# WeatherFactory('epw', self._city, file_name='CAN_PQ_Montreal.Intl.AP.716270_CWEC.epw').enrich()
weather_file = (self._example_path / 'CAN_PQ_Montreal.Intl.AP.716270_CWEC.epw').resolve()
ExportsFactory('sra', self._city, self._output_path, weather_file=weather_file, weather_format='epw').export()
sra_path = (self._output_path / f'{self._city.name}_sra.xml').resolve()
subprocess.run(['sra', str(sra_path)])
ResultFactory('sra', self._city, self._output_path).enrich()
for building in self._city.buildings:
self.assertIsNotNone(building.heating_peak_load)
self.assertIsNotNone(building.cooling_peak_load)
values = [0 for _ in range(8760)]
values[0] = 1000
expected_yearly = pd.DataFrame([1000], columns=['expected'])
expected_monthly_list = [0 for _ in range(12)]
expected_monthly_list[0] = 1000
expected_monthly = pd.DataFrame(expected_monthly_list, columns=['expected'])
for building in self._city.buildings:
building.heating[cte.HOUR] = pd.DataFrame(values, columns=['dummy'])
building.cooling[cte.HOUR] = pd.DataFrame(values, columns=['dummy'])
self.assertIsNotNone(building.heating_peak_load)
self.assertIsNotNone(building.cooling_peak_load)
pd.testing.assert_series_equal(
building.heating_peak_load[cte.YEAR]['heating peak loads'],
expected_yearly['expected'],
check_names=False
)
pd.testing.assert_series_equal(
building.cooling_peak_load[cte.YEAR]['cooling peak loads'],
expected_yearly['expected'],
check_names=False
)
pd.testing.assert_series_equal(
building.heating_peak_load[cte.MONTH]['heating peak loads'],
expected_monthly['expected'],
check_names=False
)
pd.testing.assert_series_equal(
building.cooling_peak_load[cte.MONTH]['cooling peak loads'],
expected_monthly['expected'],
check_names=False
)