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Model America - Clark County (Vegas) extract from ORNL's AutoBEM
Oak Ridge National Laboratory (ORNL) has developed the Automatic Building Energy Modeling (AutoBEM) software suite to process multiple types of data, extract building-specific descriptors, generate building energy models, and simulate them on High Performance Computing (HPC) resources. For more information, see AutoBEM-related publications (bit.ly/AutoBEM). Critical note: Building multipliers and models will be updated soon. Two sets of data are provided for 589,586 buildings located within the boundary of Clark County (Las Vegas) in the United States: Data (185MB *.csv) - minimalist list of each building (rows) for the following fields (columns) County - county name State - state name CZ - ASHRAE Climate Zone designation Clim_Zone - text label of climate zone est_year - estimated year of construction est_commercial - estimated building type (0=residential, 1=commercial) Centroid - building center location in latitude/longitude (from Footprint2D) Footprint2D - building polygon of 2D footprint (lat1/lon1_lat2/lon2_.) Height - building height (meters) ID - unique building ID Area2D - footprint area (ft2) BuildingType - DOE prototype building designation (IECC=residential) as implemented by OpenStudio-standards WWR_surfaces - percent of each facade (pair of points from Footprint2D) covered by fenestration/windows (average 14.5% for residential, 40% for commercial buildings) NumFloors - number of floors (above-grade) Area - estimate of total conditioned floor area (ft2) Standard - building vintage Models (9.2GB *.tar.gz) - EnergyPlus building energy models named according to ID Each model has approximately 3,000 building input descriptors that can be extracted. Please see the EnergyPlus (v9.4) 2,784-page Input/Output Reference Guide for everything that can be retrieved or simulated from these models. ; Integrated Multisector Multiscale Modeling (IM3) project - https://im3.pnnl.gov/
Model America - Clark County (Vegas) extract from ORNL's AutoBEM
Oak Ridge National Laboratory (ORNL) has developed the Automatic Building Energy Modeling (AutoBEM) software suite to process multiple types of data, extract building-specific descriptors, generate building energy models, and simulate them on High Performance Computing (HPC) resources. For more information, see AutoBEM-related publications (bit.ly/AutoBEM). Critical note: Building multipliers and models will be updated soon. Two sets of data are provided for 589,586 buildings located within the boundary of Clark County (Las Vegas) in the United States: Data (185MB *.csv) - minimalist list of each building (rows) for the following fields (columns) County - county name State - state name CZ - ASHRAE Climate Zone designation Clim_Zone - text label of climate zone est_year - estimated year of construction est_commercial - estimated building type (0=residential, 1=commercial) Centroid - building center location in latitude/longitude (from Footprint2D) Footprint2D - building polygon of 2D footprint (lat1/lon1_lat2/lon2_.) Height - building height (meters) ID - unique building ID Area2D - footprint area (ft2) BuildingType - DOE prototype building designation (IECC=residential) as implemented by OpenStudio-standards WWR_surfaces - percent of each facade (pair of points from Footprint2D) covered by fenestration/windows (average 14.5% for residential, 40% for commercial buildings) NumFloors - number of floors (above-grade) Area - estimate of total conditioned floor area (ft2) Standard - building vintage Models (9.2GB *.tar.gz) - EnergyPlus building energy models named according to ID Each model has approximately 3,000 building input descriptors that can be extracted. Please see the EnergyPlus (v9.4) 2,784-page Input/Output Reference Guide for everything that can be retrieved or simulated from these models. ; Integrated Multisector Multiscale Modeling (IM3) project - https://im3.pnnl.gov/
Model America - Clark County (Vegas) extract from ORNL's AutoBEM
Joshua New (Autor:in) / Brett Bass (Autor:in) / Mark Adams (Autor:in) / Anne Berres (Autor:in)
16.02.2021
Forschungsdaten
Elektronische Ressource
Englisch
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