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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
Publicly accessible

Public Reference Data for Megawatt-Scale Hydrogen Electrolysis – Simulated Wave

The U.S. Department of Energy and the National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis, hydrogen compression and storage, and variable hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as part of the Advanced R...
Abel, R. et al National Laboratory of the Rockies
Dec 12, 2025
11 Resources
0 Stars
Publicly accessible

Public Reference Data for Megawatt-Scale Hydrogen Electrolysis NLR Historical Wind

The U.S. Department of Energy and the National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis from variable sources, hydrogen compression and storage, and  hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as par...
Abel, R. et al National Laboratory of the Rockies
Mar 23, 2026
6 Resources
0 Stars
Publicly accessible

Public Reference Data for Megawatt-Scale Hydrogen Electrolysis – Simulated Wind

The U.S. Department of Energy and the National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis, hydrogen compression and storage, and variable hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as part of the Advanced R...
Abel, R. et al National Laboratory of the Rockies
Dec 12, 2025
15 Resources
0 Stars
Publicly accessible

TEAMER: Field Demonstration of MarineSitu Marine Energy Monitoring Tools (Public)

This submission contains data collected during a four-month field demonstration (July-October 2024) of MarineSitu's Adaptable Monitoring Package (AMP) at the Pacific Northwest National Laboratory (PNNL) Marine and Coastal Research Laboratory (MCRL) in Sequim, WA. The project evalu...
Joslin, J. et al MarineSitu
Aug 21, 2026
6 Resources
0 Stars
Publicly accessible

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

Dataset for Evaluation of Extreme Weather Impacts on Utility-Scale Photovoltaic Plant Performance in the United States

This dataset is a fusion of three data types (operations and maintenance tickets, weather data, and production data) that was used to support machine learning analysis and evaluation of drivers for low performance at photovoltaic (PV) sites during compound, extreme weather events....
Gunda, T. and Jackson, N. Sandia National Laboratories
Apr 01, 2021
2 Resources
0 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
2 Stars
Publicly accessible

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...
Bush, B. National Renewable Energy Laboratory
Aug 01, 2020
2 Resources
0 Stars
Publicly accessible

Error-Level-Controlled Synthetic Forecasts for Renewable Generation

Renewable energy resources, including solar and wind energy, play a significant role in sustainable energy systems. However, the inherent uncertainty and intermittency of renewable generation pose challenges to the safe and efficient operation of power systems. Recognizing the imp...
Zhang, X. et al National Renewable Energy Laboratory (NREL)
Jun 01, 2021
3 Resources
0 Stars
Publicly accessible

Control-based optimization for tethered tidal kite

This submission includes three peer-reviewed (under review) papers from the researchers at North Carolina State University presenting control-based techniques to maximize effectiveness of a tethered tidal kite. Below are the abstracts of each file included in the submission. Cobb...
Vermillion, C. et al North Carolina State University
Mar 02, 2020
3 Resources
0 Stars
Publicly accessible

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

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

Fuel Cell Inverter Transition Between Modes of Operation (Grid-Forming and Grid-Following)

This dataset shows the operation of the fuel cell inverter under grid-forming mode of operation, grid-following mode of operation and transition between the two modes.
Nemsow, N. et al National Renewable Energy Laboratory
Dec 23, 2024
2 Resources
0 Stars
Publicly accessible

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
4 Resources
0 Stars
Publicly accessible

Automated Fish Detection and Wildlife Tracking for Marine Energy Applications: Final Report and Review

This submission contains two technical resources produced for the U.S. Department of Energy Water Power Technologies Office (WPTO) that evaluate and advance automated methods for underwater wildlife detection, tracking, and monitoring around marine energy systems. The project anal...
Slater, W. et al Booz Allen Hamilton Inc.
Dec 08, 2025
2 Resources
0 Stars
Publicly accessible

Fuel Cell Inverter Dataset

This data set contains the three phase AC voltage, three phase AC current, DC voltage and DC current. These data sets were captured during fuel cell inverter operation in grid-connected dispatch, islanded load changes, transition from grid-connected mode to islanded mode and vice-...
Prabakar, K. et al National Renewable Energy Laboratory
Oct 21, 2024
1 Resources
0 Stars
Publicly accessible

TEAMER: Experimental Validation and Analysis of Deep Reinforcement Learning Control for Wave Energy Converters

Through this TEAMER project, Michigan Technological University (MTU) collaborated with Oregon State University (OSU) to test the performance of a Deep Reinforcement Learning (DRL) control in the wave tank. Unlike model-based controls, DRL control is model-free and can directly max...
Zou, S. et al Michigan Technological University
Mar 07, 2025
7 Resources
0 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
Publicly accessible

Super-Resolution for Renewable Energy Resource Data with Wind from Reanalysis (Sup3rWind)

The Super-Resolution for Renewable Energy Resource Data with Wind from Reanalysis (Sup3rWind) data is a collection of high-resolution historical wind, temperature, humidity, and pressure fields. Sup3rWind data is produced by downscaling ECMWF Reanalysis Version 5 data (ERA5) to 2-...
Benton, B. et al National Renewable Energy Lab (NREL)
Mar 11, 2024
7 Resources
0 Stars
Publicly accessible

G2Aero Database of Airfoils Curated Airfoils

This dataset contains a curated set of 19,164 airfoil shapes from various applications and the data-driven design space of separable shape tensors (PGA space), which can be used as a parameter space for machine-learning applications focused on airfoil shapes. We constructed the a...
Doronina, O. et al National Renewable Energy Lab NREL
Sep 24, 2024
3 Resources
0 Stars
Publicly accessible

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
Publicly accessible

PV Inverter Experimental Dataset Version 2 with 100 Percent Power

The increase in power electronic based generation sources require accurate modeling of inverters. Accurate modeling requires experimental data over wider operation range. We used 20 kW off-the-shelf grid following PV inverter in the experiments. We used controllable AC supply and ...
Prabakar, K. et al National Renewable Energy Laboratory
Nov 10, 2023
2 Resources
0 Stars
Publicly accessible

PV Inverter Experimental Data

The increase in power electronic based generation sources require accurate modeling of inverters. Accurate modeling requires experimental data over wider operation range. We used 20 kW off-the-shelf grid following PV inverter in the experiments. We used controllable AC supply and ...
Prabakar, K. et al National Renewable Energy Laboratory
Jan 06, 2023
2 Resources
0 Stars
Publicly accessible

Battery Inverter Experimental Data

The increase in power electronic based generation sources require accurate modeling of inverters. Accurate modeling requires experimental data over wider operation range. We used 30 kW off-the-shelf grid following battery inverter in the experiments. We used controllable AC supply...
Prabakar, K. et al National Renewable Energy Laboratory
Jan 06, 2023
2 Resources
0 Stars
Publicly accessible
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