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BUTTER-E Energy Consumption Data for the BUTTER Empirical Deep Learning Dataset
The BUTTER-E Energy Consumption Data for the BUTTER Empirical Deep Learning Dataset adds node-level energy consumption data from watt-meters to the primary sweep of the BUTTER Empirical Deep Learning Dataset. This dataset contains energy consumption and performance data from 63,52...
Tripp, C. et al National Renewable Energy Laboratory
Dec 30, 2022
9 Resources
1 Stars
Publicly accessible
9 Resources
1 Stars
Publicly accessible
CloudCV 10-Second Sky Images and Irradiance Dataset
The CloudCV 10-Second Sky Image and Irradiance Dataset contains sky images and irradiance measurements recorded every 10 seconds during daylight hours for 90 days between September 5th to December 3rd, 2019. The dataset was collected at the National Renewable Energy Laboratory (NR...
Perr-Sauer, . et al National Renewable Energy Laboratory
Oct 01, 2024
9 Resources
0 Stars
Publicly accessible
9 Resources
0 Stars
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High Throughput Experimental Materials Database
The mission of the High Throughput Experimental Materials Database (HTEM DB) is to enable discovery of new materials with useful properties by releasing large amounts of high-quality experimental data to public. The HTEM DB contains information about materials obtained from high-t...
Zakutayev, . et al National Renewable Energy Laboratory
Oct 13, 2017
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
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Topology-Based Machine-Learning for Modeling Power-System Responses to Contingencies
This is the companion dataset to the presentation NREL/PR-6A20-77485, which was presented at the 2020 Joint Statistical Meeting on August 3, 2020. Developed for the machine-learning predictive modeling of power-system responses to disruptions, it contains results of power-system c...
BushNational Renewable Energy Laboratory
Aug 01, 2020
2 Resources
0 Stars
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2 Resources
0 Stars
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Caerbannog Point Clouds
The Caerbannog Point Clouds provide point-sampled 3D models occluded in clouds of points. We synthesized the 3D point clouds from polygonal models, point-sampling the models and surrounding them in a point cloud such that the shape of the model is occluded in any 2D projection. We...
Raghupathi, . et al National Renewable Energy Laboratory
Dec 01, 2020
6 Resources
0 Stars
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6 Resources
0 Stars
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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
0 Stars
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2 Resources
0 Stars
Publicly accessible