142 lines
6.5 KiB
Python
142 lines
6.5 KiB
Python
"""
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Monthly energy balance using Insel workflow
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SPDX - License - Identifier: LGPL - 3.0 - or -later
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Copyright © 2022 Concordia CERC group
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Project Coder Pilar Monsalvete Alvarez de Uribarri pilar.monsalvete@concordia.ca
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"""
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from pathlib import Path
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import pandas as pd
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import helpers.constants as cte
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from helpers.monthly_values import MonthlyValues
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from exports.energy_building_exports_factory import EnergyBuildingsExportsFactory
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from insel.monthly_demand_calculation import MonthlyDemandCalculation
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_DAYS_A_MONTH = {cte.MONDAY: [5, 4, 4, 5, 4, 4, 5, 4, 4, 5, 4, 5],
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cte.TUESDAY: [5, 4, 4, 4, 5, 4, 5, 4, 4, 5, 4, 4],
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cte.WEDNESDAY: [5, 4, 4, 4, 5, 4, 4, 5, 4, 5, 4, 4],
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cte.THURSDAY: [4, 4, 5, 4, 5, 4, 4, 5, 4, 4, 5, 4],
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cte.FRIDAY: [4, 4, 5, 4, 4, 5, 4, 5, 4, 4, 5, 4],
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cte.SATURDAY: [4, 4, 5, 4, 4, 5, 4, 4, 5, 4, 4, 5],
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cte.SUNDAY: [4, 4, 4, 5, 4, 4, 5, 4, 5, 4, 4, 5],
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cte.HOLIDAY: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}
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class MonthlyEnergyBalance:
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def __init__(self, city, path, attic_heated_case, basement_heated_case, weather_format):
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self._city = city
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print(path)
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self._path = path
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self._weather_format = weather_format
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for building in self._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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self._sanity_check()
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self._workflow()
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def _sanity_check(self):
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levels_of_detail = self._city.level_of_detail
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if levels_of_detail.geometry is None:
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raise Exception(f'Level of detail of geometry not assigned')
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if levels_of_detail.geometry < 1:
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raise Exception(f'Level of detail of geometry = {levels_of_detail.geometry}. Required minimum level 1')
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if levels_of_detail.construction is None:
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raise Exception(f'Level of detail of construction not assigned')
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if levels_of_detail.construction < 1:
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raise Exception(f'Level of detail of construction = {levels_of_detail.construction}. Required minimum level 1')
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if levels_of_detail.usage is None:
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raise Exception(f'Level of detail of usage not assigned')
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if levels_of_detail.usage < 1:
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raise Exception(f'Level of detail of usage = {levels_of_detail.usage}. Required minimum level 1')
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for building in self._city.buildings:
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if cte.HOUR not in building.external_temperature:
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raise Exception(f'Building {building.name} does not have external temperature assigned')
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for surface in building.surfaces:
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if surface.type != cte.GROUND:
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if cte.HOUR not in surface.global_irradiance:
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raise Exception(f'Building {building.name} does not have global irradiance on surfaces assigned')
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def _workflow(self):
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for building in self._city.buildings:
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if cte.MONTH not in building.external_temperature:
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building.external_temperature[cte.MONTH] = MonthlyValues(). \
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get_mean_values(building.external_temperature[cte.HOUR][[self._weather_format]])
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for surface in building.surfaces:
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if surface.type != cte.GROUND:
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if cte.MONTH not in surface.global_irradiance:
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surface.global_irradiance[cte.MONTH] = MonthlyValues().get_mean_values(surface.global_irradiance[cte.HOUR])
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tmp_path = (Path(__file__).parent / 'tmp').resolve()
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EnergyBuildingsExportsFactory('insel_monthly_energy_balance', self._city, tmp_path).export()
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insel = MonthlyDemandCalculation(self._city, tmp_path, self._weather_format)
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insel.run()
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insel.results()
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self._dhw_demand()
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self._electrical_demand()
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self._print_results()
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def _print_results(self):
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print_results = None
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file = 'city name: ' + self._city.name + '\n'
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for building in self._city.buildings:
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heating_results = building.heating[cte.MONTH].rename(columns={'INSEL': f'{building.name} heating Wh'})
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cooling_results = building.cooling[cte.MONTH].rename(columns={'INSEL': f'{building.name} cooling Wh'})
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if print_results is None:
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print_results = heating_results
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else:
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print_results = pd.concat([print_results, heating_results], axis='columns')
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print_results = pd.concat([print_results, cooling_results, building.lighting_electrical_demand,
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building.appliances_electrical_demand], axis='columns')
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file += '\n'
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file += 'name: ' + building.name + '\n'
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file += 'year of construction: ' + str(building.year_of_construction) + '\n'
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file += 'function: ' + building.function + '\n'
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file += 'floor area: ' + str(building.floor_area) + '\n'
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file += 'storeys: ' + str(building.storeys_above_ground) + '\n'
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file += 'heated_volume: ' + str(0.85 * building.volume) + '\n'
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file += 'volume: ' + str(building.volume) + '\n'
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full_path_results = Path(self._path / 'demand.csv').resolve()
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print_results.to_csv(full_path_results)
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full_path_metadata = Path(self._path / 'metadata.csv').resolve()
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with open(full_path_metadata, 'w') as metadata_file:
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metadata_file.write(file)
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def _dhw_demand(self):
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for building in self._city.buildings:
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domestic_hot_water_demand = 0
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def _electrical_demand(self):
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for building in self._city.buildings:
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lighting_demand = []
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appliances_demand = []
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thermal_zone = building.internal_zones[0].thermal_zones[0]
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area = thermal_zone.total_floor_area
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for month in range(0, 12):
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total_lighting = 0
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for schedule in thermal_zone.lighting.schedules:
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total_day = 0
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for value in schedule.values:
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total_day += value
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for day_type in schedule.day_types:
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total_lighting += total_day * _DAYS_A_MONTH[day_type][month] * thermal_zone.lighting.density
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lighting_demand.append(total_lighting * area)
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total_appliances = 0
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for schedule in thermal_zone.appliances.schedules:
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total_day = 0
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for value in schedule.values:
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total_day += value
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for day_type in schedule.day_types:
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total_appliances += total_day * _DAYS_A_MONTH[day_type][month] * thermal_zone.appliances.density
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appliances_demand.append(total_appliances * area)
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building.lighting_electrical_demand = pd.DataFrame(lighting_demand,
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columns=[f'{building.name} lighting electrical demand Wh'])
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building.appliances_electrical_demand = pd.DataFrame(appliances_demand,
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columns=[f'{building.name} appliances electrical demand Wh'])
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