energy_system_modelling_wor.../scripts/CityBEM_run.py

390 lines
20 KiB
Python

import pandas as pd
import sys
import csv
import json
from shapely.geometry import Polygon
from pathlib import Path
import subprocess
from hub.exports.exports_factory import ExportsFactory
from hub.imports.weather.epw_weather_parameters import EpwWeatherParameters
sys.path.append('./')
def CityBEM_workflow(city):
"""
Main function to run the CityBEM under the CityLayer's hub.
:Note: City object contains necessary attributes for the CityBEM workflow.
"""
#general output path for the CityLayer's hub
out_path = Path(__file__).parent.parent / 'out_files'
#create a directory for running CityBEM under the main out_path
CityBEM_path = out_path / 'CityBEM_input_output'
if not CityBEM_path.exists():
CityBEM_path.mkdir(parents=True, exist_ok=True)
# Define the path to the GeoJSON file
file_path = Path(__file__).parent.parent / 'input_files' / 'output_buildings.geojson'
#load the geojson file (for now this is necessary, later, it should be removed to extract building usage type code, center lat and lon). Later, these should be added to the building class
with open(file_path, 'r') as f:
geojson_data = json.load(f)
#call functions to provide inputs for CityBEM and finally run CityBEM
export_geometry(city, CityBEM_path)
export_building_info(city, CityBEM_path,geojson_data)
export_weather_data(city, CityBEM_path)
export_comprehensive_building_data(city, CityBEM_path)
export_indoor_temperature_setpoint_data(city, CityBEM_path)
export_internal_heat_gain_data(city, CityBEM_path)
run_CityBEM(CityBEM_path)
def export_geometry(city, CityBEM_path):
"""
Export the STL geometry from the hub and rename the exported geometry to a proper name for CityBEM.
:param city: City object containing necessary attributes for the workflow.
:param CityBEM_path: Path where CityBEM input and output files are stored.
"""
ExportsFactory('stl', city, CityBEM_path).export()
hubGeometryName = city.name + '.stl'
#delete old files related to geometry if they exist
CityBEMGeometryPath1 = CityBEM_path / 'Input_City_scale_geometry_CityBEM.stl'
CityBEMGeometryPath2 = CityBEM_path / 'Input_City_scale_geometry_CityBEM.txt' #delete this file to ensure CityBEM generates a new one based on the new input geometry
if CityBEMGeometryPath1.exists():
CityBEMGeometryPath1.unlink()
if CityBEMGeometryPath2.exists():
CityBEMGeometryPath2.unlink()
(CityBEM_path / hubGeometryName).rename(CityBEM_path / CityBEMGeometryPath1)
print("CityBEM input geometry file named Input_City_scale_geometry_CityBEM.stl file has been created successfully")
def get_building_info(geojson_data, building_id):
for feature in geojson_data['features']:
if feature['id'] == building_id:
function_code = feature['properties']['function']
coordinates = feature['geometry']['coordinates'][0]
#calculate the center of the polygon
polygon = Polygon(coordinates)
center = polygon.centroid
return function_code, (center.x, center.y)
return None, None
def export_building_info(city, CityBEM_path, geojson_file):
"""
Generate the input building information file for CityBEM.
:param city: City object containing necessary attributes for the workflow.
:param CityBEM_path: Path where CityBEM input and output files are stored.
"""
buildingInfo_path = CityBEM_path / 'Input_City_scale_building_info.txt'
with open(buildingInfo_path, "w", newline="") as textfile: #here, "w" refers to write mode. This deletes everything inside the file if the file exists.
writer = csv.writer(textfile, delimiter="\t") #use tab delimiter for all CityBEM inputs
writer.writerow(["building_stl", "building_osm", "constructionYear", "codeUsageType", "centerLongitude", "centerLatitude"]) # Header
for building in city.buildings:
function_code, center_coordinates = get_building_info(geojson_file, int (building.name))
row = ["b" + building.name, "999999", str(building.year_of_construction), str(function_code), str(center_coordinates[0]), str(center_coordinates[1])]
#note: based on CityBEM legacy, using a number like "999999" means that the data is not known/available.
writer.writerow(row)
print("CityBEM input file named Input_City_scale_building_info.txt file has been created successfully")
def export_weather_data(city, CityBEM_path):
"""
Generate the input weather data file compatible to CityBEM.
:param city: City object containing necessary attributes for the workflow.
:param CityBEM_path: Path where CityBEM input and output files are stored.
"""
weatherParameters = EpwWeatherParameters(city)._weather_values
weatherParameters = pd.DataFrame(weatherParameters) #transfer the weather data to a DataFrame
with open(CityBEM_path / 'Input_weatherdata.txt', 'w') as textfile:
# write the header information
textfile.write('Weather_timestep(s)\t3600\n')
textfile.write('Weather_columns\t11\n') #so far, 11 columns can be extracted from the epw weather data.
textfile.write('Date\tTime\tGHI\tDNI\tDHI\tTa\tTD\tTG\tRH\tWS\tWD\n')
for _, row in weatherParameters.iterrows():
#form the Date and Time
Date = f"{int(row['year'])}-{int(row['month']):02d}-{int(row['day']):02d}"
Time = f"{int(row['hour']):02d}:{int(row['minute']):02d}"
#retrieve the weather data
GHI = row['global_horizontal_radiation_wh_m2']
DNI = row['direct_normal_radiation_wh_m2']
DHI = row['diffuse_horizontal_radiation_wh_m2']
Ta = row['dry_bulb_temperature_c']
TD = row['dew_point_temperature_c']
TG = row['dry_bulb_temperature_c']
RH = row['relative_humidity_perc']
WS = row['wind_speed_m_s']
WD = row['wind_direction_deg']
#write the data in tab-separated format into the text file
textfile.write(f"{Date}\t{Time}\t{GHI}\t{DNI}\t{DHI}\t{Ta}\t{TD}\t{TG}\t{RH}\t{WS}\t{WD}\n")
print("CityBEM input file named Input_weatherdata.txt file has been created successfully")
def export_comprehensive_building_data(city, CityBEM_path):
"""
Extract and export detailed individual building data from the hub to replace CityBEM input archetypes, including both physical and thermal properties.
:param city: City object containing necessary attributes for the workflow.
:param CityBEM_path: Path where CityBEM input and output files are stored.
"""
with open(CityBEM_path / 'Input_comprehensive_building_data_CityLayer.txt', 'w') as textfile:
writer = csv.writer(textfile, delimiter=',')
header_row="\t".join([
#building general information
"buildingName",
"constructionYear",
"function",
"roofType",
"maxHeight",
"storyHeight",
"storiesAboveGround",
"floorArea",
"volume",
"totalFloorArea",
#roof details
"roofThickness",
"roofExternalH",
"roofInternalH",
"roofUvalue",
"roofLongWaveEmittance",
"roofShortWaveReflectance",
"roofDensity",
"roofSpecificHeat",
"roofWWR",
#floor details
"floorThickness",
"floorExternalH",
"floorInternalH",
"floorUvalue",
"floorLongWaveEmittance",
"floorShortWaveReflectance",
"floorDensity",
"floorSpecificHeat",
"floorWWR",
#wall details
"wallThickness",
"wallExternalH",
"wallInternalH",
"wallUValue",
"wallLongWaveEmittance",
"wallShortWaveReflectance",
"wallDensity",
"wallSpecificHeat",
"wallWWRNorth",
"wallWWREast",
"wallWWRSouth",
"wallWWRWest",
#window details
"windowOverallUValue",
"windowGValue",
"windowFrameRatio",
#building thermal details
"thermalBridgesExtraLoses",
"infiltrationRateOff",
"infiltrationRateOn"
])
textfile.write(header_row + "\n") #write the header row
#extract and write comprehensive building data from the CityLayer's hub
for building in city.buildings:
#data should be appended based on the order of the headers.
row=[]
row.append("b" + building.name)
row.append(building.year_of_construction)
row.append(building.function)
row.append(building.roof_type)
row.append(building.max_height)
row.append(building._storeys_above_ground)
row.append(building.average_storey_height)
row.append(building.floor_area)
row.append(building.volume)
# Initialize boundary rows
row_roof = [None, None, None, None, None]
row_ground = [None, None, None, None, None]
row_wall = [None, None, None, None, None]
wallCount = 0 # so far, the data for one wall represents all the walls
for internal_zone in building.internal_zones:
totalFloorArea = internal_zone.thermal_zones_from_internal_zones[0].total_floor_area
row.append(totalFloorArea) #append the last item in "building general information"
WWR = internal_zone.thermal_archetype.constructions[0].window_ratio #window to wall ratio for the walls
northWWR = float(WWR['north'])/100. #the values from the hub is in percent. The conversion is needed.
eastWWR = float(WWR['east'])/100.
southWWR = float(WWR['south'])/100.
westWWR = float(WWR['west'])/100.
windowOverallUValue = internal_zone.thermal_archetype.constructions[0].window_overall_u_value
windowGValue = internal_zone.thermal_archetype.constructions[0].window_g_value
windowFrameRatio = internal_zone.thermal_archetype.constructions[0].window_frame_ratio
thermalBridgesExtraLoses = internal_zone.thermal_archetype.extra_loses_due_to_thermal_bridges
infiltrationRateOff = internal_zone.thermal_archetype.infiltration_rate_for_ventilation_system_off
infiltrationRateOn = internal_zone.thermal_archetype.infiltration_rate_for_ventilation_system_on
for boundary in internal_zone.thermal_zones_from_internal_zones:
for thermal_boundary in boundary.thermal_boundaries:
if thermal_boundary.type == "Roof":
layers = thermal_boundary.layers #access the roof construction layers
non_zero_layers = [layer for layer in layers if layer.thickness > 0] #filter out layers with zero thickness
total_thickness = thermal_boundary.thickness
if total_thickness > 0:
weighted_density = sum(layer.thickness * layer.density for layer in non_zero_layers) / total_thickness #weighted average represneting the entire layer.
weighted_specific_heat = sum(
layer.thickness * layer.specific_heat for layer in non_zero_layers) / total_thickness
else:
weighted_specific_heat = 0 #handle the case where total_thickness is zero to avoid division by zero
weighted_density = 0
row_roof = [
thermal_boundary.thickness,
thermal_boundary.he,
thermal_boundary.hi,
thermal_boundary.u_value,
thermal_boundary.external_surface.long_wave_emittance,
thermal_boundary.external_surface.short_wave_reflectance,
weighted_density,
weighted_specific_heat,
thermal_boundary.window_ratio
]
elif thermal_boundary.type == "Ground": #ground means floor in CityBEM based on the legacy in CityBEM.
layers = thermal_boundary.layers # access the roof construction layers
non_zero_layers = [layer for layer in layers if layer.thickness > 0] # filter out layers with zero thickness
total_thickness = thermal_boundary.thickness
if total_thickness > 0:
weighted_density = sum(
layer.thickness * layer.density for layer in non_zero_layers) / total_thickness
weighted_specific_heat = sum(
layer.thickness * layer.specific_heat for layer in non_zero_layers) / total_thickness
else:
weighted_specific_heat = 0 # Handle the case where total_thickness is zero to avoid division by zero
weighted_density = 0
row_ground = [
thermal_boundary.thickness,
thermal_boundary.he,
thermal_boundary.hi,
thermal_boundary.u_value,
thermal_boundary.external_surface.long_wave_emittance,
thermal_boundary.external_surface.short_wave_reflectance,
weighted_density,
weighted_specific_heat,
thermal_boundary.window_ratio
]
elif thermal_boundary.type == "Wall" and wallCount == 0:
wallCount += 1 #wall counter. So far, it is assumed that all the walls have a similar properties to be exported to CityBEM, except the WWR
layers = thermal_boundary.layers # access the roof construction layers
non_zero_layers = [layer for layer in layers if
layer.thickness > 0] # filter out layers with zero thickness
total_thickness = thermal_boundary.thickness
if total_thickness > 0:
weighted_density = sum(layer.thickness * layer.density for layer in non_zero_layers) / total_thickness
weighted_specific_heat = sum(
layer.thickness * layer.specific_heat for layer in non_zero_layers) / total_thickness
else:
weighted_specific_heat = 0 # Handle the case where total_thickness is zero to avoid division by zero
weighted_density = 0
row_wall = [
thermal_boundary.thickness,
thermal_boundary.he,
thermal_boundary.hi,
thermal_boundary.u_value,
thermal_boundary.external_surface.long_wave_emittance,
thermal_boundary.external_surface.short_wave_reflectance,
weighted_density,
weighted_specific_heat,
northWWR,
eastWWR,
southWWR,
westWWR
]
row.extend(row_roof)
row.extend(row_ground)
row.extend(row_wall)
#append window details
row.append(windowOverallUValue)
row.append(windowGValue)
row.append(windowFrameRatio)
#append building thermal details
row.append(thermalBridgesExtraLoses)
row.append(infiltrationRateOff)
row.append(infiltrationRateOn)
#convert each item in row to string (if needed) and join with tabs (tab separated data)
row_str = "\t".join(map(str, row))
#write the final row to the text file
textfile.write(row_str + "\n")
print("Individual building data is exported into a file named comprehensive_building_data.txt")
def export_indoor_temperature_setpoint_data(city, CityBEM_path):
"""
Extract and export individual building data on indoor temperature setpoints
:param city: City object containing necessary attributes for the workflow.
:param CityBEM_path: Path where CityBEM input and output files are stored.
"""
#open a text file in write mode (write mode removes the content if there is any)
with open(CityBEM_path /'Input_indoor_setpoint_temperature_CityLayer.txt', 'w') as textfile:
#iterate through each building
for building in city.buildings:
#write the building name
textfile.write("building"+building.name + '\t')
#iterate through each internal zone in the building
for internal_zone in building.internal_zones:
#iterate through each boundary in the internal zone
for boundary in internal_zone.thermal_zones_from_internal_zones:
#gather all indoor setpoint values for both cooling and heating
indoorSetpointValues = []
indoorSetpointValues.extend(boundary.thermal_control.cooling_set_point_schedules[0].values)#cooling on working days
indoorSetpointValues.extend(boundary.thermal_control.cooling_set_point_schedules[1].values)#cooling on Saturday
indoorSetpointValues.extend(boundary.thermal_control.cooling_set_point_schedules[2].values)#cooling on Sunday/holidays
indoorSetpointValues.extend(boundary.thermal_control.heating_set_point_schedules[0].values)#heating on working days
indoorSetpointValues.extend(boundary.thermal_control.heating_set_point_schedules[1].values)#heating on Saturday
indoorSetpointValues.extend(boundary.thermal_control.heating_set_point_schedules[2].values)#heating on Sunday/holidays
#convert values to a tab-separated strings
values_str = '\t'.join(map(str, indoorSetpointValues))
#write the values to the text file for this building
textfile.write(values_str + '\n')
print("Indoor temperature setpoints for every building is successfully exported into a text file named Input_indoor_setpoint_temperature_CityLayer.txt")
def export_internal_heat_gain_data(city, CityBEM_path):
"""
Extract and export individual building data on internal heat gains (occupant, lighting, and equipment)
:param city: City object containing necessary attributes for the workflow.
:param CityBEM_path: Path where CityBEM input and output files are stored.
"""
# open a text file in write mode (write mode removes the content if there is any)
with open(CityBEM_path / 'Input_internal_heat_gain_CityLayer.txt', 'w') as textfile:
# iterate through each building
for building in city.buildings:
# write the building name
textfile.write("building" + building.name + '\t') # (1) building name
# gather all internal heat gains for every building
internalHeatGains = []
# iterate through each internal zone in the building
for internal_zone in building.internal_zones:
# iterate through each internal usage in the internal zone
for usage in internal_zone.usages:
# iterate through internal heat gains
for internalGain in usage.internal_gains: # order: Occupancy, Lighting, and Appliances
internalHeatGains.append(internalGain.average_internal_gain) # (2) average_internal_gain
internalHeatGains.append(internalGain.convective_fraction) # (3) convective_fraction
internalHeatGains.append(internalGain.latent_fraction) # (4) latent_fraction
internalHeatGains.append(internalGain.radiative_fraction) # (5) radiative_fraction
internalHeatGains.extend(internalGain.schedules[0].values) # (6-29) Working day
internalHeatGains.extend(internalGain.schedules[1].values) # (30-54) Saturday
internalHeatGains.extend(internalGain.schedules[2].values) # (55-79)Sunday
# convert values to a tab-separated strings
values_str = '\t'.join(map(str, internalHeatGains))
# write the values to the text file for this building
textfile.write(values_str + '\n')
print("Internal heat gains for every building is successfully exported into a text file named Input_internal_heat_gain_CityLayer.txt")
def run_CityBEM(CityBEM_path):
"""
Run the CityBEM executable after all inputs are processed.
:param CityBEM_path: Path where CityBEM input and output files are stored.
"""
try:
print('CityBEM execution began:')
CityBEM_exe = CityBEM_path / 'CityBEM.exe' # path to the CityBEM executable
# check if the executable file exists
if not CityBEM_exe.exists():
print(f"Error: {CityBEM_exe} does not exist.")
subprocess.run(str(CityBEM_exe), check=True, cwd=str(CityBEM_path)) # execute the CityBEM executable
print("CityBEM executable has finished successfully.")
except Exception as ex:
print(ex)
print('error: ', ex)
print('[CityBEM simulation abort]')
sys.stdout.flush() #print all the running information on the screen