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BuildingsBench: A Large-Scale Dataset of 900K Buildings and Benchmark for Short-Term Load Forecasting
The BuildingsBench datasets consist of:
Buildings-900K: A large-scale dataset of 900K buildings for pretraining models on the task of short-term load forecasting (STLF). Buildings-900K is statistically representative of the entire U.S. building stock.
7 real residential and com...
Emami, P. and Graf, P. National Renewable Energy Laboratory
Dec 31, 2018
6 Resources
1 Stars
Publicly accessible
6 Resources
1 Stars
Publicly accessible
SMART-DS Synthetic Electrical Network Data OpenDSS Models for SFO, GSO, and AUS
The SMART-DS datasets (Synthetic Models for Advanced, Realistic Testing: Distribution systems and Scenarios) are realistic large-scale U.S. electrical distribution models for testing advanced grid algorithms and technology analysis. This document provides a user guide for the data...
Palmintier, B. et al National Renewable Energy Laboratory (NREL)
Dec 18, 2020
5 Resources
1 Stars
Publicly accessible
5 Resources
1 Stars
Publicly accessible
Hourly Dynamic Line Ratings for Existing Transmission Across the Contiguous United States (Preliminary)
This dataset provides estimated hourly dynamic line ratings for ~84,000 transmission lines across the contiguous United States from 2007-2013. The calculation methods are described in the presentation linked below, and the associated open-source Python code repository is linked in...
Obika, K. et al National Renewable Energy Laboratory
Sep 25, 2024
16 Resources
0 Stars
Publicly accessible
16 Resources
0 Stars
Publicly accessible
National Climate Database (NCDB)
The National Climate Database (NCDB) is a high resolution, bias-corrected climate dataset consisting of the three most widely used variables of solar radiation global horizontal (GHI), direct normal (DNI), and diffuse horizontal irradiance (DHI) as well as other meteorological dat...
Yang, J. et al National Renewable Energy Laboratory (NREL)
Sep 30, 2024
5 Resources
0 Stars
Publicly accessible
5 Resources
0 Stars
Publicly accessible
Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results
Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells increasing or decreasing the fluid flow rates across the wells and drilling new wells at appropriate locations. Th...
Beckers, K. et al National Renewable Energy Laboratory
Oct 20, 2021
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
AlphaBuilding Synthetic Buildings Operation Dataset
This is a synthetic building operation dataset which includes HVAC, lighting, miscellaneous electric loads (MELs) system operating conditions, occupant counts, environmental parameters, end-use and whole-building energy consumptions at 10-minute intervals. The data is created with...
Li, H. et al Lawrence Berkeley National Laboratory
Dec 21, 2020
5 Resources
0 Stars
Publicly accessible
5 Resources
0 Stars
Publicly accessible
National Solar Radiation Database (NSRDB)
The National Solar Radiation Database (NSRDB) is a serially complete collection of meteorological and solar irradiance data sets for the United States and a growing list of international locations for 1998-2023. The NSRDB is updated annually and provides foundational information t...
Sengupta, M. et al National Renewable Energy Laboratory
Sep 28, 2018
7 Resources
2 Stars
Publicly accessible
7 Resources
2 Stars
Publicly accessible
Wind Integration National Dataset (WIND) Toolkit
Wind resource data for North America was produced using the Weather Research and Forecasting Model (WRF). The WRF model was initialized with the European Centre for Medium Range Weather Forecasts Interim Reanalysis (ERA-Interm) data set with an initial grid spacing of 54 km. Thre...
Maclaurin, G. et al National Renewable Energy Laboratory
Sep 26, 2014
6 Resources
1 Stars
Publicly accessible
6 Resources
1 Stars
Publicly accessible
Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk
In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity producti...
Siler, D. et al United States Geological Survey
Oct 01, 2021
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible