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Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI)
Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI) introduces machine learning methods to incorporate high-resolution Urban Heat Island (UHI) effects into low-resolution historical reanalysis and future climate model datasets. The dataset includes model...
Buster, G. et al National Renewable Energy Lab (NREL)
Oct 16, 2024
2 Resources
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2 Resources
0 Stars
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Bias Corrected NOAA HRRR Wind Resource Data for Grid Integration Applications
To address the need for regularly updated wind resource data, NREL has processed the High-Resolution Rapid Refresh (HRRR) outputs for use in grid integration modeling. The HRRR is an hourly-updated operational forecast product produced by the National Oceanic and Atmospheric Admin...
Buster, G. et al National Renewable Energy Lab (NREL)
Oct 15, 2024
7 Resources
0 Stars
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7 Resources
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Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts (Sup3rCC)
The Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts (Sup3rCC) data is a collection of 4km hourly wind, solar, temperature, humidity, and pressure fields for the contiguous United States under various climate change scenarios.
Sup3rCC is downscaled ...
Buster, G. et al National Renewable Energy Laboratory (NREL)
Apr 19, 2023
7 Resources
2 Stars
Publicly accessible
7 Resources
2 Stars
Publicly accessible
BUTTER Empirical Deep Learning Dataset
The BUTTER Empirical Deep Learning Dataset represents an empirical study of the deep learning phenomena on dense fully connected networks, scanning across thirteen datasets, eight network shapes, fourteen depths, twenty-three network sizes (number of trainable parameters), four le...
Tripp, C. et al National Renewable Energy Laboratory
May 20, 2022
4 Resources
0 Stars
Publicly accessible
4 Resources
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Publicly accessible