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NREL MOIS Data for NWEI Azura February 2016
NREL Modular Ocean Instrumentation System (MOIS) data files for the Azura grid-connected deployment at the 30-meter berth of the US Navy's 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, ...
Nelson, E. National Renewable Energy Laboratory
May 31, 2016
16 Resources
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16 Resources
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Oil and Gas Basins in Alaska
Oil and gas basins in Alaska, available as GIS shape files. Digitized by Alaska Department of Natural Resources (ADNR), Information Resource Management Section. Digitized from DGGS publication, Special Report 32, Oil and Gas Basins Map of Alaska 1983, by Arlen Ehm.
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Hallett, K. and (AEDI), A. National Renewable Energy Laboratory
Dec 30, 1983
2 Resources
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In curation
2 Resources
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In curation
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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FERC Form 1 Electric Utility Cost, Energy Sales, Peak Demand, and Customer Count Data 1994-2019
This spreadsheet contains information reported by over 200 investor-owned utilities to the Federal Energy Regulatory Commission in the annual filing FERC Form 1 for the years 1994-2019. It contains 1) annual capital costs for new transmission, distribution, and administrative infr...
Fares, R. and King, C. National Renewable Energy Laboratory
Jan 04, 2017
2 Resources
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2 Resources
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EGS Collab Experiment 1: TOUGH2-CSM Simulation of Embedded Natural Fractures and Chemical Tracer Transport and Sorption
The EGS Collab SIGMA-V project is a multi-lab and university collaborative research project that is being undertaken at the Sanford Underground Research Facility (SURF) in South Dakota. The project consists of studying stimulation, fluid-flow, and heat transfer processes at a scal...
Johnston, B. et al National Renewable Energy Laboratory
Jun 07, 2019
4 Resources
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4 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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High Resolution Ocean Surface Wave Hindcast (US Wave) Data
The development of this dataset was funded by the U.S. Department of Energy, Office of Energy Efficiency & Renewable Energy, Water Power Technologies Office to improve our understanding of the U.S. wave energy resource and to provide critical information for wave energy project de...
Yang, Z. et al National Renewable Energy Laboratory
Jul 01, 2020
6 Resources
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Publicly accessible
6 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...
Beckers, K. et al National Renewable Energy Laboratory
Oct 20, 2021
6 Resources
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6 Resources
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Publicly accessible