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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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Description of the NSW Australia Electricity Network

Information about the New South Wales (NSW) electricity network is available. The information was taken from a line diagram of the NSW (Australia) Electricity network circa 2002 containing electrical bus and transmission line properties for use in load flow analysis. The results o...

Neale, D. and Management, M. National Renewable Energy Laboratory

Jan 01, 2002
1 Resources
0 Stars
In curation

NSW Australia Electricity Network Bus and Transmission Line Data: Snapshot from Mar 2011

[Moxy Knowledge Management](http://www.moxy.com.au/ "Moxy website") provides a general instance of the New South Wales (NSW), Australia, electricity network and an assessment of the robustness of the NSW electricity grid (e.g.,the results of several different outage scenarios). De...

Hallett, K. and Management, M. National Renewable Energy Laboratory

Dec 31, 2001
2 Resources
0 Stars
In curation

REopt Lite Geothermal Heat Pump Design Requirements

This document describes the design requirements for the geothermal heat pump (GHP) module being added to the existing REopt Lite web tool. This document describes the purpose, users, and functional requirements to which the modified web tool shall conform. This document will be re...

Olis, D. National Renewable Energy Laboratory

Mar 08, 2021
6 Resources
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BUTTER Empirical Deep Learning Dataset

The BUTTER Empirical Deep Learning Dataset represents an empirical study of the deep learning phenomena on dense fully connected networks, scanning across thirteen datasets, eight network shapes, fourteen depths, twenty-three network sizes (number of trainable parameters), four le...

Tripp, C. et al National Renewable Energy Laboratory

May 20, 2022
4 Resources
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2D Seismic Reflection Survey Crump Geyser Geothermal Prospect Warner Valley, Oregon

2D Seismic Reflection Survey from Crump Geyser Geothermal Prospect in Warner Valley, Oregon

Smith, N. and Company, N. National Renewable Energy Laboratory

Jun 10, 2015
4 Resources
0 Stars
In curation

BUTTER-E Energy Consumption Data for the BUTTER Empirical Deep Learning Dataset

The BUTTER-E Energy Consumption Data for the BUTTER Empirical Deep Learning Dataset adds node-level energy consumption data from watt-meters to the primary sweep of the BUTTER Empirical Deep Learning Dataset. This dataset contains energy consumption and performance data from 63,52...

Tripp, C. et al National Renewable Energy Laboratory

Dec 30, 2022
9 Resources
1 Stars
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Locations of water supplies serving Nairobi, Kenya.

This dataset portrays locations of water supplies serving Nairobi, Kenya. Locations of dam were approximately located by WRI based on SoK 1971, MoWD and JICA 1992a, 1992b, 1992c, Nyaoro 1999, and Wambua 2003. This data was used in Map 3.9 in Nature's Benefits in Kenya: An Atlas of...

S, L. National Renewable Energy Laboratory

Dec 26, 2018
1 Resources
0 Stars
In curation

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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Global innovation contest for future solar energy solutions

Stockholm Royal Seaport is one of Europe’s largest urban development projects and is a leader when it comes to next generation sustainable neighborhoods. As part of Stockholm Royal Seaport’s sustainability focus the competition is organized to find long-term solar energy solut...

Competitions, S. National Renewable Energy Laboratory

Dec 21, 2014
1 Resources
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POROTOMO Subtask 6.2 Deploy and Operate DAS DTS

Metadata for the surface Distributed Acoustic (DAS) array deployed the the POROTOMO's Natural Laboratory in Brady Hot Spring, Nevada during the March 2016 testing.

Fratta, D. National Renewable Energy Laboratory

Jun 30, 2016
0 Resources
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In curation

Exploration Best Practices on OpenEI

This is an electronic database detailing different types of, various phases of, best practices for, and cost and time associated with geothermal exploration techniques. The groups of exploration techniques included in the database are Data and Modeling Techniques, Downhole Techniq...

Young, K. National Renewable Energy Laboratory

Sep 20, 2013
2 Resources
0 Stars
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Sedimentary Geothermal Feasibility in Nevada, Western Utah, Colorado, and the Gulf Coast Region of Texas Final Report

The objectives of this project were to (1) perform a literature review of sedimentary geothermal resources, (2) identify data sources and develop data-collection methodologies that characterize selected resources, (3) screen sedimentary basins and formations for sedimentary geothe...

Johnston, H. et al National Renewable Energy Laboratory

Jul 01, 2020
1 Resources
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Low-Temperature Geothermal Geospatial Datasets: An Example from Alaska

This project is a component of a broader effort focused on geothermal heating and cooling (GHC) with the aim of illustrating the numerous benefits of incorporating GHC and geothermal heat exchange (GHX) into community energy planning and national decarbonization strategies. To bet...

Davalos Elizondo, E. et al National Renewable Energy Laboratory

Feb 06, 2023
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
0 Stars
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DEEPEN: Final 3D PFA Favorability Models and 2D Favorability Maps at Newberry Volcano

Part of the DEEPEN (DE-risking Exploration of geothermal Plays in magmatic ENvironments) project involved developing and testing a methodology for a 3D play fairway analysis (PFA) for multiple play types (conventional hydrothermal, superhot EGS, and supercritical). This was tested...

Taverna, N. et al National Renewable Energy Laboratory

Jan 24, 2024
14 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...