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TEAMER: Experimental Characterization of a Laboratory-Scaled Oscillating Surge Wave Energy Converter
This data is a result of an experimental campaign to characterize the hydrodynamics and performance of a laboratory-scale oscillating surge wave energy converter (OSWEC). The device was 85 cm wide, 1.4 meters tall, and 14 cm thick and was tested in the Sea Wave Environmental Lab (...
Lydon, B. et al University of Washington
Apr 05, 2024
9 Resources
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9 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
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6 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
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6 Resources
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DAISY Benchmark Performance Data
This repository contains the underlying data from benchmark experiments for Drifting Acoustic Instrumentation SYstems (DAISYs) in waves and currents described in "Performance of a Drifting Acoustic Instrumentation SYstem (DAISY) for Characterizing Radiated Noise from Marine Energy...
Polagye, B. et al University of Washington
Sep 28, 2024
6 Resources
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6 Resources
0 Stars
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ATP3 Unified Field Study Data
ATP3 Unified Field Study DataThe Algae Testbed Public-Private Partnership ATP3 was established with the goal of investigating open pond algae cultivation across different geographic climatic seasonal and operational conditions while setting the benchmark for quality data collectio...
Wolfrum. . et al National Renewable Energy Laboratory
Oct 19, 2017
17 Resources
0 Stars
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17 Resources
0 Stars
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Tidal Energy Resource Characterization, Bottom Lander Measurements, Cook Inlet, AK, 2021
These datasets are from tidal resource characterization measurements collected on the Terrasond High Energy Oceanographic Mooring (THEOM) from 1 July 2021 to 30 August 2021 (60 days) in Cook Inlet, Alaska. The lander was deployed at 60.7207031 N, 151.4294998 W in ~50 m of water.
...
Kilcher, L. and McVey, J. National Renewable Energy Laboratory
Jul 01, 2021
25 Resources
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25 Resources
0 Stars
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Tidal Energy Resource Characterization, Velocity and Turbulence Measurements, Processed Data, Cook Inlet, AK, 2021
This submission contains processed datasets from a long-term deployment of 3 moorings and a transect survey of the proposed tidal energy site off the East Forelands in Cook Inlet, AK.
The long-term mooring datasets were created from 8 instruments mounted on a Terrasond High Ener...
McVey, J. and Kilcher, L. Pacific Northwest National Laboratory
Aug 31, 2021
28 Resources
0 Stars
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28 Resources
0 Stars
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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
Publicly accessible
29 Resources
0 Stars
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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
Publicly accessible
29 Resources
0 Stars
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ARPA-E Grid Optimization (GO) Competition Challenge 3
Synthetic Input Data and Team Results for the GO Competition Challenge 3 for Events 1 4 and the Sandbox, along with problem and format descriptions and code to validate data and solutions, are available here. Data for industry scenarios will not be made public.
The Grid Optimizat...
Elbert, S. et al Pacific Northwest National Laboratory
May 02, 2024
39 Resources
1 Stars
Publicly accessible
39 Resources
1 Stars
Publicly accessible