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Utility-Scale Solar, 2023 Edition: Analysis of Empirical Plant-level Data from U.S. Ground-mounted PV, PV+battery, and CSP Plants (exceeding 5 MWAC)

Berkeley Labs "Utility-Scale Solar", 2023 Edition presents analysis of empirical plant-level data from the U.S. fleet of ground-mounted photovoltaic (PV), PV+battery, and concentrating solar-thermal power (CSP) plants with capacities exceeding 5 MWAC. While focused on key developm...

Seel, J. et al Lawrence Berkeley National Lab

Sep 05, 2023
5 Resources
1 Stars
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M3 Wave DMP/APEX WEC Numerical Survivability Report Baseline Geometry

Summary of numerical survivability modeling method for the baseline geometry of the Delos-Reyes Morrow Pressure Device (DMP), commercialized by M3 Wave LLC as "APEX."

Roberts, J. et al M3 Wave

Aug 16, 2016
2 Resources
0 Stars
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Utah FORGE Project 2439: Machine Learning for Well 16A(78)-32 Stress Predictions

This report reviews the training of machine learning algorithms to laboratory triaxial ultrasonic velocity data for Utah FORGE Well 16A(78)-32. Three machine learning (ML) predictive models were developed for the prediction of vertical and two orthogonally oriented horizontal str...

Kelley, M. et al Battelle Memorial Institute

Jun 19, 2023
1 Resources
0 Stars
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Utility-Scale Solar, 2024 Edition: Analysis of Empirical Plant-level Data from U.S. Ground-mounted PV, PV+battery, and CSP Plants (exceeding 5 MWAC)

Berkeley Labs "Utility-Scale Solar", 2024 Edition presents analysis of empirical plant-level data from the U.S. fleet of ground-mounted photovoltaic (PV), PV+battery, and concentrating solar-thermal power (CSP) plants with capacities exceeding 5 MWAC. While focused on key developm...

Seel, J. et al Lawrence Berkeley National Lab

Sep 27, 2024
5 Resources
0 Stars
Curated

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
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Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs

Subsurface data analysis, reservoir modeling, and machine learning (ML) techniques have been applied to the Brady Hot Springs (BHS) geothermal field in Nevada, USA to further characterize the subsurface and assist with optimizing reservoir management. Hundreds of reservoir simulat...

Beckers, K. et al National Renewable Energy Laboratory

Feb 18, 2021
1 Resources
0 Stars
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Machine Learning-Assisted High-Temperature Reservoir Thermal Energy Storage Optimization: Numerical Modeling and Machine Learning Input and Output Files

This data set includes the numerical modeling input files and output files used to synthesize data, and the reduced-order machine learning models trained from the synthesized data for reservoir thermal energy storage site identification. In this study, a machine-learning-assiste...

Jin, W. et al Idaho National Laboratory

Apr 15, 2022
4 Resources
0 Stars
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Spatially Referenced Geodatabase for Coso Geothermal Area

Mineral, Temperature, Gravity, and Fault Density maps in the Coso Geothermal Field in California.

Demir, E. et al Colorado School of Mines

Dec 01, 2022
14 Resources
0 Stars
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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
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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
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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
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Geomechanical Modeling for Thermal Spallation Drilling

Wells for Engineered Geothermal Systems (EGS) typically occur in conditions presenting significant challenges for conventional rotary and percussive drilling technologies: granitic rocks that reduce drilling speeds and cause substantial equipment wear. Thermal spallation drilling,...

Walsh, S. et al Lawrence Livermore National Laboratory

Aug 24, 2011
1 Resources
0 Stars
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Altona Field Lab Inverse Model WRR 2020

Includes data for measured inert tracer breakthrough curves first reported in Hawkins (2020) (Water Resources Research). In addition, this submission includes the production well temperature measurements first reported in Hawkins et al. (2017a) (Water Resources Research, volume 53...

Tester, J. Cornell University

Jan 01, 2015
3 Resources
0 Stars
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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
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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

Deep Direct-Use Feasibility Study Computed Tomography (CT)-scanned data Analysis for the Tuscarora Sandstone at the National Energy Technology Laboratory

The computed tomography (CT) facilities at the National Energy Technology Laboratory (NETL) Morgantown, West Virginia site were used to characterize core of the Tuscarora Sandstone from a vertical well in Preston County WV, the Preston-119 from a depth of 7,165 to 7,438 ft. The pr...

Brown, S. et al West Virginia University

Jan 10, 2020
11 Resources
0 Stars
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Geothermal Mineral Alterations in Brady and Desert Peak

Results of the analysis of HyMap's spectra against know hydrothermally altered minerals in the Brady-Desert Peak Geothermal Areas. This is the post-processing results and final analysis results of applying target detection algorithms and then fusing the results.

Moraga, J. Colorado School of Mines

May 15, 2021
22 Resources
0 Stars
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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
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DEEPEN Global Standardized Categorical Exploration Datasets for Magmatic Plays

DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments. As part of the development of the DEEPEN 3D play fairway analysis (PFA) methodology for magmatic plays (conventional hydrothermal, superhot EGS, and supercritical), weights needed to be develop...

Taverna, N. et al National Renewable Energy Laboratory

Jun 30, 2023
4 Resources
0 Stars
Publicly accessible

Graph Theory for Analyzing Pair-wise Data: Application to Interferometric Synthetic Aperture Radar Data

Graph theory is useful for estimating time-dependent model parameters via weighted least-squares using interferometric synthetic aperture radar (InSAR) data. Plotting acquisition dates (epochs) as vertices and pair-wise interferometric combinations as edges defines an incidence gr...

Reinisch, E. University of Wisconsin

Jul 28, 2016
1 Resources
0 Stars
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Phased Retrofits in Existing Homes in Florida Phase I: Shallow and Deep Retrofits

The U.S. Department of Energy's Building America research team Building America Partnership for Improved Residential Construction is collaborating with Florida Power & Light (FPL) to conduct a phased residential energy-efficiency retrofit program. This research seeks to establish ...

Beal, D. et al University of Central Florida Florida Solar Energy Center

Apr 27, 2016
10 Resources
0 Stars
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Hydrothermal mineral alterations in the Brady and Desert Peak geothermal fields

Results of the analysis of HyMap's spectra against know hydrothermally altered minerals in the Brady-Desert Peak Geothermal Areas. The analysis was performed using ENVI's Target Detection process against USGS library spectra for Chalcedony, Kaolinite, Gypsum, Hematite and Epsomite...

Moraga, J. Colorado School of Mines

Oct 01, 2021
4 Resources
0 Stars
Publicly accessible

Utah FORGE: Deep Wells Temperature Surveys as of September 2022

This Excel spreadsheet contains temperature survey results for Utah FORGE wells 58-32, 78-32, 56-32, 16A(78)-32 and 78B-32. It also contains charts and comparisons, along with a "Data Summary" which provides links to previous GDR submissions with temperature data for each well.

Jones, C. Energy and Geoscience Institute at the University of Utah

Sep 16, 2022
1 Resources
0 Stars
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GEOPHIRES files for DDU techno-economic simulations

During 2017-2019, the U.S. Department of Energy funded six geothermal deep direct-use (DDU) projects to investigate feasibility of DDU for heating, cooling and thermal storage in the United States. In a follow-on study conducted at the National Renewable Energy Laboratory (NREL), ...

Beckers, K. and Kolker, A. National Renewable Energy Laboratory

Mar 31, 2021
1 Resources
0 Stars
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Dataset for Evaluating the Impact of Wildfire Smoke on Solar Photovoltaic Production

This dataset was used to support machine learning model development for wildfire impacts on utility-scale solar in the United States. The dataset includes information regarding energy generation, PM2.5, clearness index, temperature, wind speed, precipitation, and site size.

Gilletly, S. et al Sandia National Laboratories

May 15, 2023
3 Resources
0 Stars
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