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PV Rooftop Database
The National Renewable Energy Laboratory's (NREL) Photovoltaic (PV) Rooftop Database (PVRDB) is a lidar-derived, geospatially-resolved dataset of suitable roof surfaces and their PV technical potential for 128 metropolitan regions in the United States. The PVRDB data are organized...
Mooney, M. National Renewable Energy Laboratory (NREL)
Jan 01, 2016
5 Resources
0 Stars
Publicly accessible
5 Resources
0 Stars
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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
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5 Resources
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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
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
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5 Resources
0 Stars
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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
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6 Resources
0 Stars
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GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration and Development of Hidden Geothermal Resources
Geothermal exploration and production are challenging, expensive and risky. The GeoThermalCloud uses Machine Learning to predict the location of hidden geothermal resources. This submission includes a training dataset for the GeoThermalCloud neural network. Machine Learning for Di...
Ahmmed, B. Stanford University
Apr 04, 2022
3 Resources
0 Stars
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3 Resources
0 Stars
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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
PoroTomo Natural Laboratory Horizontal and Vertical Distributed Acoustic Sensing Data
This dataset includes links to the PoroTomo DAS data in both SEG-Y and hdf5 (via h5py and HSDS with h5pyd) formats with tutorial notebooks for use. Data are hosted on Amazon Web Services (AWS) Simple Storage Service (S3) through the Open Energy Data Initiative (OEDI). Also include...
Feigl, K. et al University of Wisconsin
Mar 29, 2016
20 Resources
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20 Resources
0 Stars
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