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High Resolution Ocean Surface Wave Hindcast (US Wave) Data
The development of this dataset was funded by the U.S. Department of Energy, Office of Energy Efficiency & Renewable Energy, Water Power Technologies Office to improve our understanding of the U.S. wave energy resource and to provide critical information for wave energy project de...
Yang, Z. et al National Renewable Energy Laboratory
Jul 01, 2020
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
National Climate Database (NCDB)
The National Climate Database (NCDB) is a high resolution, bias-corrected climate dataset consisting of the three most widely used variables of solar radiation global horizontal (GHI), direct normal (DNI), and diffuse horizontal irradiance (DHI) as well as other meteorological dat...
Yang, J. et al National Renewable Energy Laboratory (NREL)
Sep 30, 2024
5 Resources
0 Stars
Curated
5 Resources
0 Stars
Curated
NREL Eagle supercomputer jobs
High performance computing dataset with 11M+ jobs from NREL's Eagle supercomputer. These jobs were submitted to run on Eagle between Nov 2018 and Feb 2023. The data are sufficiently anonymized and do not include sensitive user or project data. HPC research community does not have ...
Duplyakin, D. and Menear, K. National Renewable Energy Laboratory
Feb 28, 2023
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results
Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells increasing or decreasing the fluid flow rates across the wells and drilling new wells at appropriate locations. Th...
Beckers, K. et al National Renewable Energy Laboratory
Oct 20, 2021
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
Transient Data Library of Solar Grid Integrated Distributed System
This submission contains an open-source library of transient events in distributed system with high solar PV. The library includes the collected data, related documents and scripts for loading the data. The data library is built for transient event detection and machine learning b...
Kuruganti, T. and Dong, Y. Oak Ridge National Laboratory
Nov 10, 2022
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
Wind and Structural Loads on Parabolic Trough Solar Collectors at Nevada Solar One
Wind loading is a main contributor to structural design costs of Concentrating Solar Power (CSP) collectors, such as heliostats and parabolic troughs. These structures must resist the mechanical forces generated by turbulent wind. At the same time, the reflector surfaces must exhi...
Egerer, U. et al National Renewable Energy Laboratory (NREL)
Oct 01, 2021
4 Resources
0 Stars
Publicly accessible
4 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
Curated
3 Resources
0 Stars
Curated
PoroTomo Natural Laboratory Horizontal and Vertical Distributed Acoustic Sensing Data
This dataset includes links to the PoroTomo DAS data in both SEG-Y and hdf5 (via h5py and HSDS with h5pyd) formats with tutorial notebooks for use. Data are hosted on Amazon Web Services (AWS) Simple Storage Service (S3) through the Open Energy Data Initiative (OEDI). Also include...
Feigl, K. et al University of Wisconsin
Mar 29, 2016
18 Resources
0 Stars
Publicly accessible
18 Resources
0 Stars
Publicly accessible
Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk
In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity producti...
Siler, D. et al United States Geological Survey
Oct 01, 2021
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible