-
Federal
U.S. Electric Utility Companies and Rates: Look-up by Zipcode (2023)
Department of Energy —
This dataset, compiled by NREL using data from ABB, the Velocity Suite (http://energymarketintel.com/) and the U.S. Energy Information Administration dataset 861... -
Federal
Photovoltaic Module Current-Voltage and Electroluminescence Image Data (PV-IV-EL)
Department of Energy —
This dataset consists of 613 sets of corresponding current-voltage trace (IV) flash test data and electroluminescence (EL) image data for commercial PV modules from... -
Federal
ARPA-E Grid Optimization (GO) Competition Challenge 3
Department of Energy —
Synthetic Input Data and Team Results for the GO Competition Challenge 3 for Events 1 - 4 and the Sandbox, along with problem and format descriptions and code to... -
Federal
2023 National Offshore Wind data set (NOW-23)
Department of Energy —
The 2023 National Offshore Wind data set (NOW-23) is the latest wind resource data set for offshore regions in the United States, which supersedes, for its offshore... -
Federal
Utah FORGE: Well 78B-32 Daily Drilling Reports and Logs
Department of Energy —
This data set includes the daily drilling reports and Pason data for well 78B-32 and Schlumberger logs acquired after drilling completion. This well was drilled... -
Federal
ARPA-E Grid Optimization (GO) Competition Challenge 1
Department of Energy —
The ARPA-E Grid Optimization (GO) Competition Challenge 1, from 2018 to 2019, focused on the basic Security Constrained AC Optimal Power Flow problem (SCOPF) for a... -
Federal
Castlegate Sandstone True Triaxial Test Data
Department of Energy —
Data set containing results from constant mean stress - constant Lode angle true triaxial compression tests performed on Castlegate Sandstone. From the test... -
Federal
Distributed Acoustic Sensing Experiment Data from Garner Valley, California
Department of Energy —
In September 2013, an experiment using Distributed Acoustic Sensing (DAS) was conducted at Garner Valley, a test site of the University of California Santa Barbara... -
Federal
ARPA-E Grid Optimization (GO) Competition Challenge 2
Department of Energy —
The ARPA-E Grid Optimization (GO) Competition Challenge 2, from 2020 to 2021, expanded upon the problem posed in Challenge 1 by adding adjustable transformer tap... -
Federal
Training dataset and results for geothermal exploration artificial intelligence, applied to Brady Hot Springs and Desert Peak
Department of Energy —
The submission includes the labeled datasets, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model: -... -
Federal
Geothermal Reservoir Simulation Results in support of Feasibility Study of Direct District Heating for the Cornell Campus Utilizing Deep Geothermal Energy
Department of Energy —
This dataset contains input data, code, ReadMe files, output data, and figures that summarize the results of a stochastic analysis of geothermal reservoir production... -
Federal
GOOML Big Kahuna Forecast Modeling and Genetic Optimization Files
Department of Energy —
This submission includes example files associated with the Geothermal Operational Optimization using Machine Learning (GOOML) Big Kahuna fictional power plant, which... -
Federal
EGS-Collab Experiment 1: Time-lapse ERT Data and E4D Inversion Files for 10-24-2018 through 11-07-2018 Flow Test
Department of Energy —
This data submission includes the raw time-lapse ERT (electrical resistivity tomography) monitoring data, flow system data, operator logs, E4D (https://e4d.pnnl.gov)... -
Federal
EGS Collab Experiment 1: Circulation Testing Processed data
Department of Energy —
This submission includes processed and reduced data for circulation testing that was conducted at the 164' fracture on the 4850 ft level of the Sanford Underground... -
Federal
TEAMER: Experimental Validation and Analysis of Deep Reinforcement Learning Control for Wave Energy Converters
Department of Energy —
Through this TEAMER project, Michigan Technological University (MTU) collaborated with Oregon State University (OSU) to test the performance of a Deep Reinforcement...