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INTEGRATE Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements

The INTEGRATE (Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements) project is developing a new inverse-design capability for the aerodynamic design of wind turbine rotors using invertible neural networks. This AI-based design techno...
Vijayakumar, G. et al National Renewable Energy Laboratory (NREL)
May 04, 2021
8 Resources
0 Stars
Publicly accessible

Bias Corrected Near-Surface Wind Data for Solar Field Siting

This dataset catalogs a long-term high-resolution data set characterizing the near-surface hourly wind speed variations at two solar sites in the Southwest U.S. This dataset demonstrates the potential for integrating improved near-surface wind data into CST and PV planning tools f...
Emes, M. et al National Laboratory of the Rockies (NLR)
Jun 12, 2026
2 Resources
0 Stars
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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
2 Stars
Publicly accessible

Artificial Intelligence for Robust Integration of AMI and Synchrophasor Data to Significantly Boost Solar Adoption

The overarching goal of the project is to create a highly efficient framework of machine learning (ML) methods that provide consistent and accurate real-time knowledge of system states from diverse advanced metering infrastructure (AMI) devices and phasor measurement units (PMUs) ...
Ayyanar, R. et al Arizona State University
Feb 01, 2025
12 Resources
0 Stars
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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
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Sup3rWind Data (CONUS)

This data contains paired European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) and the Wind Integration National Dataset Toolkit (WTK) images for 2007 and 2010 over two regions in the US, with domain sizes ~800x800 (latitudes from 25.89 to 41.58, and long...
Sinha, S. et al National Renewable Energy Laboratory (NREL)
Jul 16, 2024
6 Resources
0 Stars
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Sup3rLoad Dataset

Sup3rLoad is a dataset of hourly electricity load for the contiguous United States that varies jointly with electrification and weather. It spans 2 electrification scenarios, 5 CMIP6 Earth system models (Sup3rCC, SSP2-4.5), 6 scenario years between 2025 and 2050, 60 weather years ...
Jones, R. et al Evolved Energy Research
Dec 06, 2025
6 Resources
0 Stars
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