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DEEPEN 3D PFA Weights for Exploration Datasets in Magmatic Environments

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
3 Resources
0 Stars
Publicly accessible

NREL GIS Data: Hawaii Low Resolution Concentrating Solar Power Resource

_Abstract:_ Monthly and annual average solar resource potential for Hawaii. _Purpose:_ Provide information on the solar resource potential for Hawaii. The insolation values represent the average solar energy available to a flat plate collector, such as a photovoltaic panel, o...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation

NREL GIS Data: Alaska Low Resolution Photovoltaic Solar Resource

_Abstract:_ Monthly and annual average solar resource potential for Alaska. _Purpose:_ Provide information on the solar resource potential for Alaska. The insolation values represent the average solar energy available to a flat plate collector, such as a photovoltaic panel, o...
Wood, J. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation

NREL GIS Data: Continental United States Photovoltaic Low Resolution

_Abstract:_ Monthly and annual average solar resource potential for the lower 48 states of the United States of America. _Purpose:_ Provide information on the solar resource potential for the United States of America lower 48 states. The insolation values represent the averag...
Wood, J. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation

NREL GIS Data: Hawaii Low Resolution Photovoltaic Solar Resource

_Abstract:_ Monthly and annual average solar resource potential for Hawaii. _Purpose:_ Provide information on the solar resource potential for Hawaii. The insolation values represent the average solar energy available to a flat plate collector, such as a photovoltaic panel, o...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation

StingRAY Updated WEC Risk Registers

Updated Risk Registers for major subsystems of the StingRAY WEC completed according to the methodology described in compliance with the DOE Risk Management Framework developed by NREL.
Rhinefrank, K. and Ondusko, M. Columbia Power Technologies, Inc.
Jun 27, 2018
17 Resources
0 Stars
Publicly accessible

NREL GIS Data: Alaska Low Resolution Concentrating Solar Power Resource

_Abstract:_ Monthly and annual average solar resource potential for Alaska. _Purpose:_ Provide information on the solar resource potential for Alaska. The insolation values represent the average solar energy available to a flat plate collector, such as a photovoltaic panel, o...
Wood, J. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation

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
Publicly accessible

Research Report of Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin

This is a final report summarizing a one-year (2014-15) DOE funded Geothermal Play Fairway Analysis of the Low-Temperature resources of the Appalachian Basin of New York, Pennsylvania and West Virginia. Collaborators included Cornell University, Southern Methodist University, and...
Jordan, T. et al Cornell University
Sep 30, 2015
22 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
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