161 lines
7.1 KiB
Python
161 lines
7.1 KiB
Python
import helpers.library_codes
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import numpy as np
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from pathlib import Path
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import pandas as pd
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import csv
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from factories.weather_feeders.helpers.weather import Weather as wt
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class MonthlyEnergyBalance:
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@staticmethod
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def generate_meb_template(building, insel_outputs_path):
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lc = helpers.library_codes.LibraryCodes()
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file = ""
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file += "s 1 do\r\n"
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file += "p 1 1 12 1\r\n"
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file += "\r\n"
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file += "s 4 d18599 1.1 20.1 21.1\r\n"
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surfaces = building.surfaces
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for i in range(1, len(surfaces) + 1):
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file += str(100 + i) + '.1 % Radiation surface ' + str(i) + '\r\n'
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file += 'p 4' + '\r\n'
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# BUILDING PARAMETERS
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file += str(building.heated_volume) + ' % BP(1) Heated Volume (vBrutto)\r\n'
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file += str(building.average_storey_height) + ' % BP(2) Average storey height / m\r\n'
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file += str(building.storeys_above_ground) + ' % BP(3) Number of storeys above ground\r\n'
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file += str(building.attic_heated) + ' % BP(4) Attic heating type (0=no room, 1=unheated, 2=heated)\r\n'
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file += str(building.basement_heated) + ' % BP(5) Cellar heating type (0=no room, 1=unheated, ' \
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'2=heated, 99=invalid)\r\n'
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# todo: this method and the insel model have to be reviewed for more than one thermal zone
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thermal_zone = building.thermal_zones[0]
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file += str(thermal_zone.indirectly_heated_area_ratio) + ' % BP(6) Indirectly heated area ratio\r\n'
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file += str(thermal_zone.effective_thermal_capacity) + ' % BP(7) Effective heat capacity\r\n'
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file += str(thermal_zone.additional_thermal_bridge_u_value) + ' % BP(8) Additional U-value for heat bridge\r\n'
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file += '0 % BP(9) Usage type (0=standard, 1=IWU)\r\n'
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# ZONES AND SURFACES
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# todo: is this actually number of thermal zones or of usage zones?
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file += str(len(building.thermal_zones)) + ' % BP(10) Number $z$ of zones\r\n'
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i = 0
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for usage_zone in building.usage_zones:
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percentage_usage = 1
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file += str(float(building.foot_print.area) * percentage_usage) + ' % BP(11) #1 Area of zone ' + \
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str(i + 1) + ' (sqm)' + '\r\n'
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total_internal_gains = 0
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for ig in usage_zone.internal_gains:
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total_internal_gains += float(ig.average_internal_gain) * \
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(float(ig.convective_fraction) + float(ig.radiative_fraction))
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file += str(total_internal_gains) + ' % BP(12) #2 Internal gains of zone ' + str(i + 1) + '\r\n'
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file += str(usage_zone.heating_setpoint) + ' % BP(13) #3 Heating setpoint temperature zone ' + \
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str(i + 1) + ' (tSetHeat)' + '\r\n'
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file += str(usage_zone.heating_setback) + ' % BP(14) #4 Heating setback temperature zone ' + \
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str(i + 1) + ' (tSetbackHeat)' + '\r\n'
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file += str(usage_zone.cooling_setpoint) + ' % BP(15) #5 Cooling setpoint temperature zone ' + \
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str(i + 1) + ' (tSetCool)' + '\r\n'
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file += str(usage_zone.hours_day) + ' % BP(16) #6 Usage hours per day zone ' + str(i + 1) + '\r\n'
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file += str(usage_zone.days_year) + ' % BP(17) #7 Usage days per year zone ' + str(i + 1) + '\r\n'
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if usage_zone.mechanical_air_change is None:
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raise Exception('Ventilation air rate is not initialized')
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file += str(usage_zone.mechanical_air_change) + ' % BP(18) #8 Minimum air change rate zone ' + \
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str(i + 1) + ' (h^-1)' + '\r\n'
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i += 1
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file += str(len(surfaces)) + ' % Number of surfaces = BP(11+8z)\r\n'
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file += '% 1. Surface type (1=wall, 2=ground 3=roof, 4=flat roof)' + '\r\n'
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file += '% 2. Areas above ground' + '\r\n'
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file += '% 3. Areas below ground' + '\r\n'
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file += '% 4. U-value' + '\r\n'
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file += '% 5. Window area' + '\r\n'
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file += '% 6. Window frame fraction' + '\r\n'
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file += '% 7. Window U-value' + '\r\n'
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file += '% 8. Window g-value' + '\r\n'
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file += '% 9. Short-wave reflectance' + '\r\n'
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file += '% #1 #2 #3 #4 #5 #6 #7 #8 #9' + '\r\n'
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# todo: this method has to be reviewed for more than one thermal opening per thermal boundary
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for thermal_boundary in building.thermal_zones[0].bounded:
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type_code = lc.construction_types_to_code(thermal_boundary.type)
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string = type_code + ' ' + str(thermal_boundary.area_above_ground) + ' ' + \
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str(thermal_boundary.area_below_ground) + ' ' + str(thermal_boundary.u_value) + ' ' + \
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str(thermal_boundary.window_area) + ' '
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if thermal_boundary.window_area <= 0.001:
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string = string + '0 0 0 '
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else:
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string = string + str(thermal_boundary.thermal_openings[0].frame_ratio) + ' ' + \
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str(thermal_boundary.thermal_openings[0].overall_u_value) + ' ' + \
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str(thermal_boundary.thermal_openings[0].g_value) + ' '
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if thermal_boundary.outside_solar_absorptance is not None:
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string += str(thermal_boundary.shortwave_reflectance) + '\r\n'
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else:
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string += '0 \r\n'
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file += string
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file += '\r\n'
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file += 's 20 polyg 1\r\n'
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file += 'p 20 12 % Monthly ambient temperature\r\n'
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external_temperature = building.external_temperature['month']
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for i in range(0, len(external_temperature)):
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file += str(i+1) + ' ' + str(external_temperature.at[i, 'inseldb']) + '\r\n'
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file += '\r\n'
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file += 's 21 polyg 1\r\n'
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file += 'p 21 12 % Monthly sky temperature\r\n'
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i = 1
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sky_temperature = wt.sky_temperature(external_temperature[['inseldb']].to_numpy().T[0])
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for temperature in sky_temperature:
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file += str(i) + ' ' + str(temperature) + '\r\n'
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i += 1
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i = 0
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for surface in surfaces:
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file += '\r\n'
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file += 's ' + str(101 + i) + ' polyg 1 % Monthly surface radiation (W/sqm)\r\n'
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file += 'p ' + str(101 + i) + ' 12 % Azimuth ' + str(np.rad2deg(surface.azimuth)) + \
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', inclination ' + str(np.rad2deg(surface.inclination)) + ' degrees\r\n'
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if surface.type != 'Ground':
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global_irradiance = surface.global_irradiance['month']
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for j in range(0, len(global_irradiance)):
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file += str(j + 1) + ' ' + str(global_irradiance.at[j, 'sra']) + '\r\n'
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else:
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for j in range(0, 12):
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file += str(j + 1) + ' 0\r\n'
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i += 1
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file += '\r\n'
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file += '% ONE YEAR\r\n'
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file += 's 300 cum 4.1 4.2\r\n'
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file += 's 303 atend 300.1 300.2\r\n'
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file += '\r\n'
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file += 's ' + str(310) + ' WRITE\r\n'
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file += '4.1 4.2\r\n'
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file += 'p ' + str(310) + '\r\n'
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file += '1 % Mode\r\n'
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file += '0 % Suppress FNQ inputs\r\n'
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file += "'" + str(insel_outputs_path) + "' % File name\r\n"
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file += "'*' % Fortran format\r\n"
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return file
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@staticmethod
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def demand(insel_outputs_path):
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heating = []
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cooling = []
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with open(Path(insel_outputs_path).resolve()) as csv_file:
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csv_reader = csv.reader(csv_file)
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for line in csv_reader:
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demand = str(line).replace("['", '').replace("']", '').split()
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heating.append(demand[0])
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cooling.append(demand[1])
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monthly_heating = pd.DataFrame(heating, columns=['INSEL'])
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monthly_cooling = pd.DataFrame(cooling, columns=['INSEL'])
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return monthly_heating, monthly_cooling
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