163 lines
7.6 KiB
Python
163 lines
7.6 KiB
Python
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"""
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ComnetUsageParameters model the usage properties
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SPDX - License - Identifier: LGPL - 3.0 - or -later
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Copyright © 2021 Project Author Pilar Monsalvete Alvarez de Uribarri pilar.monsalvete@concordia.ca
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"""
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import sys
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from typing import Dict
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import pandas as pd
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import helpers.constants as cte
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from helpers.configuration_helper import ConfigurationHelper as ch
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from imports.geometry.helpers.geometry_helper import GeometryHelper
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from imports.usage.helpers.usage_helper import UsageHelper
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from city_model_structure.building_demand.usage_zone import UsageZone
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from city_model_structure.building_demand.internal_gains import InternalGains
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from imports.usage.data_classes.hft_usage_zone_archetype import HftUsageZoneArchetype as huza
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from imports.usage.data_classes.hft_internal_gains_archetype import HftInternalGainsArchetype as higa
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class ComnetUsageParameters:
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"""
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ComnetUsageParameters class
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"""
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def __init__(self, city, base_path):
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self._city = city
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self._base_path = str(base_path / 'comnet_archetypes.xlsx')
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self._usage_archetypes = []
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data = self._read_file()
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for item in data['lighting']:
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for usage in UsageHelper.usage_to_comnet:
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comnet_usage = UsageHelper.usage_to_comnet[usage]
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if comnet_usage == item:
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usage_archetype = self._parse_zone_usage_type(comnet_usage, data)
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self._usage_archetypes.append(usage_archetype)
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def _read_file(self) -> Dict:
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"""
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reads xlsx file containing usage information into a dictionary
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:return : Dict
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"""
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number_usage_types = 33
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xl_file = pd.ExcelFile(self._base_path)
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file_data = pd.read_excel(xl_file, sheet_name="Modeling Data", skiprows=[0, 1, 2],
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nrows=number_usage_types, usecols="A:Z")
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lighting_data = {}
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plug_loads_data = {}
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occupancy_data = {}
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ventilation_rate = {}
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water_heating = {}
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process_data = {}
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for j in range(0, number_usage_types):
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usage_parameters = file_data.iloc[j]
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usage_type = usage_parameters[0]
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lighting_data[usage_type] = usage_parameters[1:6].values.tolist()
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plug_loads_data[usage_type] = usage_parameters[8:13].values.tolist()
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occupancy_data[usage_type] = usage_parameters[17:20].values.tolist()
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ventilation_rate[usage_type] = usage_parameters[20:21].values.tolist()
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water_heating[usage_type] = usage_parameters[23:24].values.tolist()
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process_data[usage_type] = usage_parameters[24:26].values.tolist()
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return {'lighting': lighting_data,
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'plug loads': plug_loads_data,
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'occupancy': occupancy_data,
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'ventilation rate': ventilation_rate,
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'water heating': water_heating,
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'process': process_data}
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@staticmethod
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def _parse_zone_usage_type(usage, data):
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if data['occupancy'][usage][0] <= 0:
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occupancy_density = 0
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else:
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occupancy_density = 1 / data['occupancy'][usage][0]
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mechanical_air_change = data['ventilation rate'][usage][0]
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internal_gains = []
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# lighting
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latent_fraction = ch().comnet_lighting_latent
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convective_fraction = ch().comnet_lighting_convective
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radiative_fraction = ch().comnet_lighting_radiant
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average_internal_gain = data['lighting'][usage][4]
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internal_gains.append(higa(internal_gains_type=cte.LIGHTING, average_internal_gain=average_internal_gain,
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convective_fraction=convective_fraction, radiative_fraction=radiative_fraction,
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latent_fraction=latent_fraction))
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# occupancy
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latent_fraction = data['occupancy'][usage][2] / (data['occupancy'][usage][1] + data['occupancy'][usage][2])
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sensible_fraction = float(1 - latent_fraction)
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convective_fraction = sensible_fraction * ch().comnet_occupancy_sensible_convective
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radiative_fraction = sensible_fraction * ch().comnet_occupancy_sensible_radiant
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average_internal_gain = (data['occupancy'][usage][1] + data['occupancy'][usage][2]) \
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* occupancy_density * cte.BTU_H_TO_WATTS
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internal_gains.append(higa(internal_gains_type=cte.OCCUPANCY, average_internal_gain=average_internal_gain,
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convective_fraction=convective_fraction, radiative_fraction=radiative_fraction,
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latent_fraction=latent_fraction))
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# plug loads
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if data['plug loads'][usage][0] != 'n.a.':
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latent_fraction = ch().comnet_plugs_latent
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convective_fraction = ch().comnet_plugs_convective
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radiative_fraction = ch().comnet_plugs_radiant
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average_internal_gain = data['plug loads'][usage][0]
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internal_gains.append(higa(internal_gains_type=cte.RECEPTACLE, average_internal_gain=average_internal_gain,
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convective_fraction=convective_fraction, radiative_fraction=radiative_fraction,
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latent_fraction=latent_fraction))
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usage_zone_archetype = huza(usage=usage, internal_gains=internal_gains,
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occupancy_density=occupancy_density,
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mechanical_air_change=mechanical_air_change)
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return usage_zone_archetype
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def enrich_buildings(self):
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"""
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Returns the city with the usage parameters assigned to the buildings
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:return:
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"""
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city = self._city
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for building in city.buildings:
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usage = GeometryHelper.usage_from_function(building.function)
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height = building.average_storey_height
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if height is None:
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raise Exception('Average storey height not defined, ACH cannot be calculated')
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if height <= 0:
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raise Exception('Average storey height is zero, ACH cannot be calculated')
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archetype = self._search_archetype(UsageHelper.comnet_from_usage(usage))
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if archetype is None:
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sys.stderr.write(f'Building {building.name} has unknown archetype for building function:'
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f' {building.function}, that assigns building usage as '
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f'{GeometryHelper.usage_from_function(building.function)}\n')
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continue
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# just one usage_zone
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for thermal_zone in building.thermal_zones:
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usage_zone = UsageZone()
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usage_zone.usage = usage
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self._assign_values(usage_zone, archetype, height)
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usage_zone.volume = thermal_zone.volume
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thermal_zone.usage_zones = [usage_zone]
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def _search_archetype(self, building_usage):
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for building_archetype in self._usage_archetypes:
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if building_archetype.usage == building_usage:
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return building_archetype
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return None
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@staticmethod
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def _assign_values(usage_zone, archetype, height):
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# Due to the fact that python is not a typed language, the wrong object type is assigned to
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# usage_zone.internal_gains when writing usage_zone.internal_gains = archetype.internal_gains.
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# Therefore, this walk around has been done.
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internal_gains = []
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for archetype_internal_gain in archetype.internal_gains:
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internal_gain = InternalGains()
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internal_gain.type = archetype_internal_gain.type
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internal_gain.average_internal_gain = archetype_internal_gain.average_internal_gain * cte.METERS_TO_FEET**2
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internal_gain.convective_fraction = archetype_internal_gain.convective_fraction
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internal_gain.radiative_fraction = archetype_internal_gain.radiative_fraction
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internal_gain.latent_fraction = archetype_internal_gain.latent_fraction
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internal_gains.append(internal_gain)
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usage_zone.internal_gains = internal_gains
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usage_zone.occupancy_density = archetype.occupancy_density * cte.METERS_TO_FEET**2
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usage_zone.mechanical_air_change = archetype.mechanical_air_change * usage_zone.occupancy_density \
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* cte.HOUR_TO_MINUTES / cte.METERS_TO_FEET**3 / height
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