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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
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NREL 25-cm2 High-Pressure Low-Temperature Electrolysis Cell Hardware (Open Source)

This data resource describes an open-source cell hardware that enables low temperature electrolysis (LTE) testing at elevated pressures. Existing commercial options have several downsides when it comes to R&D testing. They are often not designed for repeated reassembly, may no...

Wrubel. . et al National Renewable Energy Laboratory

Nov 14, 2023
2 Resources
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2017 Western Passage Tidal Energy Resource Characterization Measurements

These data are from tidal resource characterization measurements collected between April and July 2017 in Western Passage near Eastport, Maine, USA. The dataset contains the following four sub-datasets, each of which is described in more detail in the README.pdf. 1. A bottom-mou...

Kilcher, L. et al National Renewable Energy Laboratory

Jul 31, 2017
33 Resources
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Ocean Thermal Energy Conversion (OTEC) Datasets

The data presented here were collected from the Ocean Thermal Extractable Energy Visualization (OTEEV) project. The OTEEV project focused on assessing the Maximum Practicably Extractable Energy (MPEE) from the world's ocean thermal resources. This project explored the feasibili...

Langle, N. et al National Renewable Energy Laboratory

Nov 25, 2014
10 Resources
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UNH TDP Concurrent Measurements of Inflow, Power Performance, and Loads for a Grid-Synchronized Vertical Axis Cross-Flow Turbine Operating in a Tidal Estuary

This data was collected between October 12 and December 15 of 2021 at the University of New Hampshire (UNH) and Atlantic Marine Energy Center (AMEC) turbine deployment platform (TDP). This data set includes over 29 days of grid connected turbine operation during this 65 day time f...

Wosnik, M. et al National Renewable Energy Laboratory

Dec 21, 2021
30 Resources
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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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Admiralty Inlet Advanced Turbulence Measurements: May 2015

This data is from measurements at Admiralty Head, in Admiralty Inlet (Puget Sound) in May of 2015. The measurements were made using Inertial Motion Unit (IMU) equipped ADVs mounted on a 'StableMoor' (Manufacturer: DeepWater Buoyancy) buoy and a Tidal Turbulence Mooring (TTM). Thes...

Kilcher, L. National Renewable Energy Laboratory

May 18, 2015
18 Resources
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Understanding the Evolution of Customer Motivations and Adoption Barriers in Residential Solar Markets: Survey Data

This research focused on accelerating solar photovoltaic (PV) diffusion by collecting new market data and developing predictive modeling frameworks to test and refine understandings of household level motivations for adopting solar. Three different household-level surveys were...

Sigrin. . et al National Renewable Energy Laboratory

May 22, 2017
13 Resources
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Admiralty Inlet Advanced Turbulence Measurements: June 2014

This data is from measurements at Admiralty Head, in Admiralty Inlet (Puget Sound) in June of 2014. The measurements were made using Inertial Motion Unit (IMU) equipped ADVs mounted on Tidal Turbulence Mooring's (TTMs). The TTM positions the ADV head above the seafloor to make mid...

Kilcher, L. National Renewable Energy Laboratory

Jun 30, 2014
26 Resources
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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...