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"transfer learning"×

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...
BushNational Renewable Energy Laboratory
Aug 01, 2020
2 Resources
0 Stars
Publicly accessible

Utah FORGE: Optimization of a Plug-and-Perf Stimulation (Fervo Energy)

Information around the plug-and-perf treatment design at Utah FORGE by Fervo Energy. Objective and Purpose: Develop a multistage hydraulic stimulation approach designed specifically to target the top three factors that control the technical and commercial viability of an EGS sys...
Norbeck, J. et al Fervo Energy
Feb 08, 2023
3 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

Utah FORGE 6-3712: Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks 2024 Annual Workshop Presentation

This is a presentation on the Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks by GTC Analytics, presented by Jesse Williams. This video slide presentation discusses the development of machine learning-based predictive tools to estimate...
Williams, J. Energy and Geoscience Institute at the University of Utah
Sep 17, 2024
1 Resources
0 Stars
Publicly accessible

Processed Lab Data for Neural Network-Based Shear Stress Level Prediction

Machine learning can be used to predict fault properties such as shear stress, friction, and time to failure using continuous records of fault zone acoustic emissions. The files are extracted features and labels from lab data (experiment p4679). The features are extracted with a n...
Marone, C. et al Pennsylvania State University
May 14, 2021
3 Resources
0 Stars
Publicly accessible

Hybrid machine learning model to predict 3D in-situ permeability evolution

Enhanced geothermal systems (EGS) can provide a sustainable and renewable solution to the new energy transition. Its potential relies on the ability to create a reservoir and to accurately evaluate its evolving hydraulic properties to predict fluid flow and estimate ultimate therm...
Elsworth, D. and Marone, C. Pennsylvania State University
Nov 22, 2022
4 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

Training dataset and results for geothermal exploration artificial intelligence, applied to Brady Hot Springs and Desert Peak

The submission includes the labeled datasets, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model: brady_som_output.gri, brady_som_output.grd, brady_som_output.* desert_som_output.gri, desert_som_output.grd, desert_som_outpu...
Moraga, J. et al Colorado School of Mines
Sep 01, 2020
16 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

Utah FORGE 2-2439v2: Characterizing In-Situ Stress with Laboratory Modelling and Field Measurements 2024 Annual Workshop Presentation

This is a presentation on A Multi-Component Approach to Characterizing In-Situ Stress at the Utah FORGE Site: Laboratory Modelling and Field Measurements project by The University of Pittsburgh, presented by Andrew Bunger. The project characterizes the stress in the Utah FORGE EGS...
Bunger, A. Energy and Geoscience Institute at the University of Utah
Sep 04, 2024
1 Resources
0 Stars
Publicly accessible

EGS Collab Experiment 1: SIMFIP Notch-164 GRL Paper

Characterizing the stimulation mode of a fracture is critical to assess the hydraulic efficiency and the seismic risk related to deep fluid manipulations. We have monitored the three-dimensional displacements of a fluid-driven fracture during water injections in a borehole at ~1.5...
Guglielmi, Y. Lawrence Berkeley National Laboratory
Sep 24, 2020
9 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

Geothermal Drilling and Completions: Petroleum Practices Technology Transfer

NREL and the Colorado School of Mines (SURGE) conducted research in FY14 to identify petroleum drilling and completion practices (methods and technologies) that can be transferred to geothermal drilling and completion, to provide the geothermal industry with more effective, lower ...
Visser, C. et al National Renewable Energy Laboratory
Sep 30, 2014
1 Resources
0 Stars
Publicly accessible

Magnetotelluric Data from Mountain Home, ID

This dataset includes magnetotelluric transfer functions in the form of EDI files for 16 stations collected by the USGS and 40 stations collected by Quantec Geoscience for Lawerence Berkeley National Lab around the Mountain Home area in Idaho. A 3D electrical resistivity model is ...
Peacock, J. and Gasperikova, E. United States Geological Survey
Sep 18, 2020
2 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

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

This data set 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. . et al National Renewable Energy Laboratory
Dec 23, 2024
2 Resources
0 Stars
Publicly accessible

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

Desert Peak Geodatabase for Geothermal Exploration Artificial Intelligence

These files contain the geodatabases related to the Desert Peak Geothermal Field. It includes all input and output files used in the project. The files include data categories of raw data, pre-processed data, and analysis (post-processed data). In each of these categories there ar...
Moraga, J. et al Colorado School of Mines
Apr 27, 2021
3 Resources
0 Stars
Publicly accessible

Brady Geodatabase for Geothermal Exploration Artificial Intelligence

These files contain the geodatabases related to Brady's Geothermal Field. It includes all input and output files for the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (post-proces...
Moraga, J. et al Colorado School of Mines
Apr 27, 2021
3 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. . et al National Renewable Energy Laboratory
Oct 21, 2024
1 Resources
0 Stars
Publicly accessible

Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence

These files contain the geodatabases related to Salton Sea Geothermal Field. It includes all input and output files used with the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (po...
Moraga, J. et al Colorado School of Mines
Apr 27, 2021
3 Resources
0 Stars
Publicly accessible

Weatherization Assistance Program

The U.S. Department of Energy's Weatherization Assistance Program (WAP) was created in 1976 to assist low-income families who lacked resources to invest in energy efficiency. WAP is operated in all 50 states, the District of Columbia, Native American tribes, and U.S. Territories. ...
Adams, R. and (EERE), O. Office of Energy Efficiency & Renewable Energy
Nov 25, 2014
1 Resources
0 Stars
In curation

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

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

Drilling Monitoring Program: Computer Program on Heat Transfer Temperature Distribution Hydraulic Calculations for Abrasive Jet Drilling

A program was created to evaluate the downhole conditions occurring in a FLASH ASJ drilling system. the program is meant to aid the operator of a coiled tubing rig in maintaining optimum drilling conditions.
Ozbayoglu, E. Impact Technologies LLC
Jan 01, 2011
1 Resources
0 Stars
Publicly accessible
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