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GOOML Big Kahuna Forecast Modeling and Genetic Optimization Files
This submission includes example files associated with the Geothermal Operational Optimization using Machine Learning (GOOML) Big Kahuna fictional power plant, which uses synthetic data to model a fictional power plant. A forecast was produced using the GOOML data model framework ...
Buster, G. et al Upflow
Jun 30, 2021
11 Resources
0 Stars
Publicly accessible
11 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
1 Stars
Curated
9 Resources
1 Stars
Curated
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
4 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
16 Resources
0 Stars
Publicly accessible
ARPA-E Grid Optimization (GO) Competition Challenge 1
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 single time period. The Challenge utilized sets of unique datasets generated by the ARPA-E GRID DATA program. Each da...
Elbert, S. et al Pacific Northwest National Laboratory
Aug 05, 2024
29 Resources
0 Stars
Curated
29 Resources
0 Stars
Curated
Microearthquake Studies at the Salton Sea Geothermal Field
The objective of this project is to detect and locate microearthquakes to aid in the characterization of reservoir fracture networks. Accurate identification and mapping of the large numbers of microearthquakes induced in EGS is one technique that provides diagnostic information w...
Templeton, D. Lawrence Livermore National Laboratory
Oct 01, 2013
1 Resources
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible
Improved Microseismicity Detection During Newberry EGS Stimulations
Effective enhanced geothermal systems (EGS) require optimal fracture networks for efficient heat transfer between hot rock and fluid. Microseismic mapping is a key tool used to infer the subsurface fracture geometry. Traditional earthquake detection and location techniques are oft...
Templeton, D. Lawrence Livermore National Laboratory
Oct 01, 2013
1 Resources
0 Stars
Publicly accessible
1 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 The National Renewable Energy Lab (NREL)
Apr 19, 2023
7 Resources
1 Stars
Curated
7 Resources
1 Stars
Curated
ARPA-E Grid Optimization (GO) Competition Challenge 2
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 ratios, phase shifting transformers, switchable shunts, price-responsive demand, ramp rate constrained generators and l...
Elbert, S. et al Pacific Northwest National Laboratory
Sep 20, 2024
29 Resources
0 Stars
Curated
29 Resources
0 Stars
Curated
Improved Microseismicity Detection During Newberry EGS Stimulations
Effective enhanced geothermal systems (EGS) require optimal fracture networks for efficient heat transfer between hot rock and fluid. Microseismic mapping is a key tool used to infer the subsurface fracture geometry. Traditional earthquake detection and location techniques are oft...
Templeton, D. Lawrence Livermore National Laboratory
Nov 01, 2013
1 Resources
0 Stars
Publicly accessible
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
3 Resources
0 Stars
Publicly accessible
EGS Collab Experiment 1: 3D Seismic Velocity Model and Updated Microseismic Catalog Using Transfer-Learning Aided Double-Difference Tomography
This package contains a 3D Seismic velocity model and an updated microseismic catalog associated with a proceedings paper (Chai et al., 2020) published in the 45th Workshop on Geothermal Reservoir Engineering. The 3D_seismic_velocity_model text file contains x (m), y(m), z(m), P-w...
Chai, C. et al Oak Ridge National Laboratory
Apr 20, 2020
7 Resources
0 Stars
Publicly accessible
7 Resources
0 Stars
Publicly accessible
SMART-DS Synthetic Electrical Network Data OpenDSS Models for SFO, GSO, and AUS
The SMART-DS datasets (Synthetic Models for Advanced, Realistic Testing: Distribution systems and Scenarios) are realistic large-scale U.S. electrical distribution models for testing advanced grid algorithms and technology analysis. This document provides a user guide for the data...
Palmintier, B. et al National Renewable Energy Laboratory (NREL)
Dec 18, 2020
5 Resources
0 Stars
Publicly accessible
5 Resources
0 Stars
Publicly accessible
DEEPEN Leapfrog Geodata Model Cleaned and Reformatted Exploration Datasets from Newberry Volcano
DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments.
As part of the DEEPEN 3D play fairway analysis (PFA) conducted at Newberry Volcano for multiple play types (conventional hydrothermal, superhot EGS, and supercritical), existing geoscientific e...
Pauling, H. et al National Renewable Energy Laboratory
Jun 30, 2023
22 Resources
0 Stars
Publicly accessible
22 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