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Sodar Vaisala Triton Wind Profiler, AON8 Raw Data

**Overview** This dataset contains measurements from eight different Vaisala Triton Wind Profiler instruments. The Triton Wind Profiler is a sodar wind profiler that measures wind speed, direction, and turbulence intensity at heights from 30 m to 200 m above ground every 10 minut...

Stoelinga, M. Wind Energy Technologies Office (WETO)

Dec 06, 2015
1 Resources
0 Stars
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Sodar Vaisala Triton Wind Profiler, AON9 Raw Data

Stoelinga, M. Wind Energy Technologies Office (WETO)

Nov 27, 2016
1 Resources
0 Stars
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Sodar Vaisala Triton Wind Profiler, AON9 Reviewed Data

Stoelinga, M. Wind Energy Technologies Office (WETO)

Nov 14, 2016
1 Resources
0 Stars
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Sodar Vaisala Triton Wind Profiler, AON2 Raw Data

Stoelinga, M. Wind Energy Technologies Office (WETO)

Jul 06, 2015
1 Resources
0 Stars
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Sodar Vaisala Triton Wind Profiler, AON2 Reviewed Data

Stoelinga, M. Wind Energy Technologies Office (WETO)

Sep 30, 2015
1 Resources
0 Stars
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Sodar Vaisala Triton Wind Profiler, AON3 Raw Data

Stoelinga, M. Wind Energy Technologies Office (WETO)

Sep 07, 2015
1 Resources
0 Stars
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Sodar Vaisala Triton Wind Profiler, AON4 Raw Data

Stoelinga, M. Wind Energy Technologies Office (WETO)

Jan 12, 2016
1 Resources
0 Stars
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Sodar Vaisala Triton Wind Profiler, AON4 Reviewed Data

Stoelinga, M. Wind Energy Technologies Office (WETO)

Sep 30, 2015
1 Resources
0 Stars
Publicly accessible

Sodar Vaisala Triton Wind Profiler, AON5 Raw Data

Stoelinga, M. Wind Energy Technologies Office (WETO)

Sep 07, 2015
1 Resources
0 Stars
Publicly accessible

Sodar Vaisala Triton Wind Profiler, AON6 Reviewed Data

Stoelinga, M. Wind Energy Technologies Office (WETO)

Sep 30, 2015
1 Resources
0 Stars
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Sodar Vaisala Triton Wind Profiler, AON7 Reviewed Data

Stoelinga, M. Wind Energy Technologies Office (WETO)

Sep 30, 2015
1 Resources
0 Stars
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Sodar Vaisala Triton Wind Profiler, AON8 Reviewed Data

Stoelinga, M. Wind Energy Technologies Office (WETO)

Sep 30, 2015
1 Resources
0 Stars
Publicly accessible

Cape EGS: Frisco 2-P Well Stimulation Microseismic Data

This dataset contains microseismic data acquired during the Frisco 2-P well stimulation project led by Fervo Energy, conducted between June 1 and June 11, 2024, near the Utah FORGE geothermal site. The microseismic data was collected from various Utah FORGE wells: via Distributed ...

Dadi, S. and Titov, A. Fervo Energy

Sep 19, 2024
26 Resources
0 Stars
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Dynamic Earth Energy Storage: Terawatt-Year, Grid-Scale Energy Storage using Planet Earth as a Thermal Battery (GeoTES): Seedling Project Final Report

Grid-scale energy storage has been identified as a needed technology to support the continued build-out of intermittent renewable energy resources. As of April 2017, the U.S. had approximately 24.2 GW of energy storage on line, compared to 1,081 GW of installed generation capacity...

McLing, T. et al Idaho National Laboratory

May 31, 2019
11 Resources
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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
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Comparative Analysis of Alternative Means for Removing Noncondensable Gases from Flashed-Steam Geothermal Power Plants:April 1999 March 2000

This dataset corresponds to the final report on a screening study to compare six methods of removing noncondensable gases from direct-use geo-thermal steam power plants. This report defines the study methodologies and compares the performance and economics of selected gas-removal ...

Hallett, K. and Laboratory, N. National Renewable Energy Laboratory

Nov 25, 2014
3 Resources
0 Stars
In curation

Quantifying and Monetizing Renewable Energy Resiliency

As part of the seed LDRD in 2017 we generated catastrophe models to look at the value of resiliency from an insurance perspective. These data sets reflect the inputs and outputs of that analysis.

Lisell. . et al National Renewable Energy Laboratory

Mar 13, 2018
3 Resources
0 Stars
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Sodar Vaisala Triton Wind Profiler, AON8 Raw Data

Sodar Vaisala Triton Wind Profiler, AON9 Raw Data

Sodar Vaisala Triton Wind Profiler, AON9 Reviewed Data

Sodar Vaisala Triton Wind Profiler, AON2 Raw Data

Sodar Vaisala Triton Wind Profiler, AON2 Reviewed Data

Sodar Vaisala Triton Wind Profiler, AON3 Raw Data

Sodar Vaisala Triton Wind Profiler, AON4 Raw Data

Sodar Vaisala Triton Wind Profiler, AON4 Reviewed Data

Sodar Vaisala Triton Wind Profiler, AON5 Raw Data

Sodar Vaisala Triton Wind Profiler, AON6 Reviewed Data

Sodar Vaisala Triton Wind Profiler, AON7 Reviewed Data

Sodar Vaisala Triton Wind Profiler, AON8 Reviewed Data

Cape EGS: Frisco 2-P Well Stimulation Microseismic Data

Dynamic Earth Energy Storage: Terawatt-Year, Grid-Scale Energy Storage using Planet Earth as a Thermal Battery (GeoTES): Seedling Project Final Report

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

Comparative Analysis of Alternative Means for Removing Noncondensable Gases from Flashed-Steam Geothermal Power Plants:April 1999 March 2000

Quantifying and Monetizing Renewable Energy Resiliency

Sodar Vaisala Triton Wind Profiler, AON9 Processed Data

Sodar Vaisala Triton Wind Profiler, AON3 Processed Data

Sodar Vaisala Triton Wind Profiler, AON4 Processed Data

Sodar Vaisala Triton Wind Profiler, AON5 Processed Data

Sodar Vaisala Triton Wind Profiler, AON2 Processed Data

Sodar Vaisala Triton Wind Profiler, AON1 Processed Data

Sodar Vaisala Triton Wind Profiler, AON6 Processed Data

Sodar Vaisala Triton Wind Profiler, AON7 Processed Data