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GRC 2019 Initial Results Presentation
The Report is being developed by NREL and the GRC, with financial support from the Geothermal Technologies Office of the U.S. DOE and the GRC. It is intended to provide geothermal policymakers, regulators, developers, researchers, and other stakeholders with up-to-date information...
Robins, J. National Renewable Energy Laboratory
Oct 01, 2020
1 Resources
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1 Resources
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DEEPEN Leapfrog Geodata Model Cleaned and Reformatted Exploration Datasets from Newberry Volcano
DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments.
As part of the DEEPEN 3D play fairway analysis (PFA) conducted at Newberry Volcano for multiple play types (conventional hydrothermal, superhot EGS, and supercritical), existing geoscientific e...
Pauling, H. et al National Renewable Energy Laboratory
Jun 30, 2023
22 Resources
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22 Resources
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2019 Geothermal Market Report Fact Sheet
The 2020 U.S. Geothermal Power Production and District Heating Market Report is being developed by the National Renewable Energy Laboratory and Geothermal Rising, previously Geothermal Resources Council (GRC), with support from the Geothermal Technologies Office of the U.S. Depart...
Robins, J. et al National Renewable Energy Laboratory
Oct 01, 2020
1 Resources
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1 Resources
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NREL MOIS Data for NWEI Azura July 2016
NREL Modular Ocean Instrumentation System (MOIS) data files for the Azura grid-connected deployment at the 30-meter berth of the US Navys Wave Energy Test Site (WETS 30m Site) at the Kaneohe Marine Corps Base Hawaii (MCBH) on the windward (northeast) coast of the island of Oahu, H...
Nelson, E. National Renewable Energy Laboratory
Sep 25, 2016
18 Resources
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18 Resources
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Hourly Energy Emission Factors for Electricity Generation in the United States
Monthly average hourly CO2, NOx, and SO2 emission factors for each U.S. eGRID subregion.
This project utilized GridViewTM, an electric grid dispatch software package, to estimate hourly emission factors for all of the [eGRID](https://www.epa.gov/egrid) subregions in the continenta...
Studer, D. National Renewable Energy Laboratory
Nov 25, 2014
25 Resources
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25 Resources
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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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1 Resources
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DEEPEN 3D PFA Favorability Models and 2D Favorability Maps at Newberry Volcano
DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments.
Part of the DEEPEN project involved developing and testing a methodology for a 3D play fairway analysis (PFA) for multiple play types (conventional hydrothermal, superhot EGS, and supercritical...
Taverna, N. et al National Renewable Energy Laboratory
Jun 30, 2023
27 Resources
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27 Resources
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