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GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration and Development of Hidden Geothermal Resources
Geothermal exploration and production are challenging, expensive and risky. The GeoThermalCloud uses Machine Learning to predict the location of hidden geothermal resources. This submission includes a training dataset for the GeoThermalCloud neural network. Machine Learning for Di...
Ahmmed, B. Stanford University
Apr 04, 2022
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
GeoThermalCloud framework for fusion of big data and multi-physics models in Nevada and Southwest New Mexico
Our GeoThermalCloud framework is designed to process geothermal datasets using a novel toolbox for unsupervised and physics-informed machine learning called SmartTensors. More information about GeoThermalCloud can be found at the GeoThermalCloud GitHub Repository. More information...
Vesselinov, V. Los Alamos National Laboratory
Mar 29, 2021
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
Imperial Valley Dark Fiber Project Continuous DAS Data
The Imperial Valley Dark Fiber Project acquired Distributed Acoustic Sensing (DAS) seismic data on a ~28 km segment of dark fiber between the cities of Calipatria and Imperial in the Imperial Valley, Southern California. Dark fiber refers to unused optical fiber cables in telecomm...
Ajo-Franklin, J. et al Lawrence Berkeley National Laboratory
Nov 10, 2020
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
Matlab Scripts and Sample Data Associated with Water Resources Research Article
Scripts and data acquired at the Mirror Lake Research Site, cited by the article submitted to Water Resources Research:
Distributed Acoustic Sensing (DAS) as a Distributed Hydraulic Sensor in Fractured Bedrock
M. W. Becker(1), T. I. Coleman(2), and C. C. Ciervo(1)
1 California St...
Becker, M. and Coleman, T. California State University
Jul 18, 2015
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
Renewable Energy Potential Model: Priority Geothermal Leasing Areas ReEDs Results
This dataset contains the results of a study conducted by the National Renewable Energy Laboratory (NREL) to identify potential future priority geothermal leasing areas on Bureau of Land Management (BLM) and United States Forest Service (USFS) lands. The analysis uses the Regional...
Smith, F. et al National Renewable Energy Laboratory
May 20, 2024
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
Hourly Dynamic Line Ratings for Existing Transmission Across the Contiguous United States (Preliminary)
This dataset provides estimated hourly dynamic line ratings for ~84,000 transmission lines across the contiguous United States from 2007-2013. The calculation methods are described in the presentation linked below, and the associated open-source Python code repository is linked in...
Obika, K. et al National Renewable Energy Laboratory
Sep 25, 2024
16 Resources
0 Stars
Publicly accessible
16 Resources
0 Stars
Publicly accessible
Early Market Opportunity MHK Energy Site Identification Wave and Tidal Resources
This data was compiled for the 'Early Market Opportunity Hot Spot Identification' project. The data and scripts included were used in the 'MHK Energy Site Identification and Ranking Methodology' Reports (see resources below). The Python scripts will generate a set of results--base...
Kilcher, L. National Renewable Energy Laboratory
Apr 01, 2016
7 Resources
0 Stars
Publicly accessible
7 Resources
0 Stars
Publicly accessible
MHK Levelized Cost of Energy (LCOE) Guidance and Techno-Economic Analysis Materials
Useful information and tools for calculating the Levelized Cost of Energy (LCOE) and MHK Cost Breakdown Structure. Includes a structure for calculating the capital expenditures and operating costs of a marine energy technology or device, reference resource data for both wave and ...
Jenne, S. and Baca, E. National Renewable Energy Laboratory
Nov 08, 2019
7 Resources
0 Stars
Publicly accessible
7 Resources
0 Stars
Publicly accessible
2025 County-Level Hourly Renewable Capacity Factor Dataset for the ReEDS Model
This dataset contains hourly capacity factors for each renewable resource class and region (in this case, county). Technologies like large-scale utility PV (UPV), onshore (land-based) wind, offshore wind, and concentrating solar power (CSP) are included. Hourly profiles are provid...
Sergi, B. et al National Renewable Energy Laboratory (NREL)
Mar 25, 2025
6 Resources
0 Stars
In progress
6 Resources
0 Stars
In progress
County-Level Hourly Renewable Capacity Factor Dataset for the ReEDS Model
This dataset contains hourly capacity factors for each renewable resource class and region (in this case, county). Technologies like large-scale utility PV (UPV), onshore wind, offshore wind, and concentrating solar power (CSP) are included. The dataset contains 7 years of hourly ...
Cole, W. et al National Renewable Energy Laboratory (NREL)
Aug 01, 2023
5 Resources
2 Stars
Publicly accessible
5 Resources
2 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
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
3 Resources
0 Stars
Publicly accessible
Distributed Generation Market Demand (dGen) model
The Distributed Generation Market Demand (dGen) model simulates customer adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the United States or other countries through 2050. The dGen model can be used for identifying the sector...
Stanley, T. et al National Renewable Energy Laboratory (NREL)
Oct 16, 2020
4 Resources
1 Stars
Publicly accessible
4 Resources
1 Stars
Publicly accessible
TEAMER: OSU X Hinsdale & Sandia LUPA Uncertainty Testing
This processed data is from TEAMER testing through RFTS 7 at the O.H. Hinsdale Wave Research Laboratory in Corvallis, Oregon. This testing was conducted by Oregon State University (OSU) and Sandia National Laboratories in October and November 2023. The Laboratory Upgrade Point Abs...
Robertson, B. et al Oregon State University
Oct 19, 2023
6 Resources
0 Stars
Publicly accessible
6 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
In curation
12 Resources
0 Stars
In curation
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
6 Resources
0 Stars
Publicly accessible
Admiralty Inlet Hub-Height Turbulence Measurements from June 2012
This data is from measurements at Admiralty Head, in Admiralty Inlet. The measurements were made using an IMU equipped ADV mounted on a mooring, the 'Tidal Turbulence Mooring' or 'TTM'. The inertial measurements from the IMU allows for removal of mooring motion in post processing....
Kilcher, L. National Renewable Energy Laboratory
Jun 18, 2012
7 Resources
0 Stars
Publicly accessible
7 Resources
0 Stars
Publicly accessible
2023 National Offshore Wind data set (NOW-23)
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 component, the Wind Integration National Dataset (WIND) Toolkit, which was published about a decade ago and is curre...
Bodini, N. et al National Renewable Energy Laboratory
Jan 01, 2020
22 Resources
1 Stars
Publicly accessible
22 Resources
1 Stars
Publicly accessible
Demand-Side Grid Model (dsgrid) Data from the Electrification Futures Project (EFS)
This data set contains the full-resolution and state-level data described in the linked technical report (https://www.nrel.gov/docs/fy18osti/71492.pdf). It can be accessed with the NREL-dsgrid-legacy-efs-api, available on GitHub at https://github.com/dsgrid/dsgrid-legacy-efs-api a...
Hale, E. et al National Renewable Energy Laboratory
Jul 08, 2018
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
United States Land-based Wind Supply Curves 2023
This data packet contains supply curves, hourly generation profiles, and a composite siting exclusion TIFF for land-based wind across the contiguous United States. The supply curves offer comprehensive metrics such as capacity (MW), generation (MWh), levelized cost of energy (LCOE...
GDS, N. National Renewable Energy Laboratory
Jun 30, 2023
13 Resources
0 Stars
Publicly accessible
13 Resources
0 Stars
Publicly accessible
United States Utility-Scale PV Supply Curves 2023
This data packet contains supply curves, hourly generation profiles, and a composite siting exclusion TIFF for utility-scale PV across the contiguous United States. The supply curves offer comprehensive metrics such as capacity (MW), generation (MWh), levelized cost of energy (LCO...
GDS, N. National Renewable Energy Laboratory
Jun 30, 2023
13 Resources
1 Stars
Publicly accessible
13 Resources
1 Stars
Publicly accessible
United States Land-based Wind Supply Curves 2024
This data packet contains supply curves, hourly generation profiles, and a composite siting exclusion TIFF for land-based wind across the contiguous United States. The supply curves offer comprehensive metrics such as capacity (MW), generation (MWh), levelized cost of energy (LCOE...
Geospatial Data Science, N. National Renewable Energy Laboratory
Jan 01, 2025
12 Resources
0 Stars
In progress
12 Resources
0 Stars
In progress
United States Utility-Scale PV Supply Curves 2024
This data packet contains supply curves, hourly generation profiles, and a composite siting exclusion TIFF for utility-scale PV across the contiguous United States. The supply curves offer comprehensive metrics such as capacity (MW), generation (MWh), levelized cost of energy (LCO...
Geospatial Data Science, N. National Renewable Energy Laboratory
Jan 01, 2025
12 Resources
0 Stars
In progress
12 Resources
0 Stars
In progress
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
Programs and Code for Geothermal Exploration Artificial Intelligence
The scripts below are used to run the Geothermal Exploration Artificial Intelligence developed within the "Detection of Potential Geothermal Exploration Sites from Hyperspectral Images via Deep Learning" project. It includes all scripts for pre-processing and processing, including...
Moraga, J. Colorado School of Mines
Apr 27, 2021
11 Resources
0 Stars
Publicly accessible
11 Resources
0 Stars
Publicly accessible