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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
Publicly accessible
6 Resources
0 Stars
Publicly accessible
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
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible
Air Pollutant Emissions Inventory of Large-Scale Production of Selected Biofuels Feedstocks in 2022 supporting data
Data provided are numeric results used to plot the maps/figures presented in the paper “Air Pollutant Emissions Inventory of Large-Scale Production of Selected Biofuels Feedstocks in 2022” ([DOI: 10.1002/bbb.1620](http://onlinelibrary.wiley.com/doi/10.1002/bbb.1620/full)).
...
Zhang, Y. National Renewable Energy Laboratory
Oct 05, 2015
13 Resources
0 Stars
In curation
13 Resources
0 Stars
In curation
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
0 Stars
In curation
0 Resources
0 Stars
In curation
Solar Home System Jharkhand India
Script in MATLAB and data sets in .csv for over 6 months of minute-by-minute resolution of household level energy consumption based off of three solar home systems with lights and a fan installed in Jharkhand, India.
The files herein include original spreadsheets with the raw dat...
Mehra, V. National Renewable Energy Laboratory
Aug 09, 2016
1 Resources
0 Stars
In curation
1 Resources
0 Stars
In curation
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
0 Stars
Curated
4 Resources
0 Stars
Curated
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
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
U.S. Solar Siting Regulation and Zoning Ordinances
A machine readable collection of documented solar siting ordinances at the state and local (e.g., county, township) level throughout the United States. The data were compiled based on a locality-by-locality review zoning ordinances after completing an initial review of scholarly l...
Lopez, A. et al National Renewable Energy Laboratory
Jun 30, 2022
1 Resources
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible
U.S. Wind Siting Regulation and Zoning Ordinances
A machine readable collection of documented wind siting ordinances at the state and local (e.g., county, township) level throughout the United States. The data were compiled from several sources including, DOE's Wind Exchange Ordinance Database (Linked in the submission), National...
Lopez, A. et al National Renewable Energy Laboratory
Jun 30, 2022
4 Resources
1 Stars
Publicly accessible
4 Resources
1 Stars
Publicly accessible
Ocean Thermal Energy Conversion (OTEC) | Seawater Cooling Depth Profile 14ºC (Annual Average)
This shapefile represents the annual average depth profile to reach water at a temperature of 14ºC.
Sea water cooling can be used for industrial or residential cooling needs where heat must be rejected. A typical resource for direct air-conditioning applications is no warmer t...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation
2 Resources
0 Stars
In curation
Ocean Thermal Energy Conversion (OTEC) | Seawater Cooling Depth Profile 14ºC (Summer Average)
This shapefile represents the seasonal summer depth profile to reach water at a temperature of 14ºC.
Sea water cooling can be used for industrial or residential cooling needs where heat must be rejected. A typical resource for direct air-conditioning applications is no warmer ...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation
2 Resources
0 Stars
In curation
Ocean Thermal Energy Conversion (OTEC) | Seawater Cooling Depth Profile 14ºC (Winter Average)
This shapefile represents the seasonal winter depth profile to reach water at a temperature of 14ºC.
Sea water cooling can be used for industrial or residential cooling needs where heat must be rejected. A typical resource for direct air-conditioning applications is no warmer ...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation
2 Resources
0 Stars
In curation
Ocean Thermal Energy Conversion (OTEC) | Seawater Cooling Depth Profile 20ºC (Annual Average)
This shapefile represents the annual average depth profile to reach water at a temperature of 20ºC.
Sea water cooling can be used for industrial or residential cooling needs where heat must be rejected. A typical resource for direct air-conditioning applications is no warmer t...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation
2 Resources
0 Stars
In curation
Ocean Thermal Energy Conversion (OTEC) | Seawater Cooling Depth Profile 20ºC (Summer Average)
This shapefile represents the seasonal summer depth profile to reach water at a temperature of 20ºC.
Sea water cooling can be used for industrial or residential cooling needs where heat must be rejected. A typical resource for direct air-conditioning applications is no warmer ...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation
2 Resources
0 Stars
In curation
Ocean Thermal Energy Conversion (OTEC) | Seawater Cooling Depth Profile 20ºC (Winter Average)
This shapefile represents the seasonal winter depth profile to reach water at a temperature of 20ºC.
Sea water cooling can be used for industrial or residential cooling needs where heat must be rejected. A typical resource for direct air-conditioning applications is no warmer ...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation
2 Resources
0 Stars
In curation
Ocean Thermal Energy Conversion (OTEC) | Seawater Cooling Depth Profile 8ºC (Annual Average)
This shapefile represents the annual average depth profile to reach water at a temperature of 8ºC.
Sea water cooling can be used for industrial or residential cooling needs where heat must be rejected. A typical resource for direct air-conditioning applications is no warmer th...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation
2 Resources
0 Stars
In curation
Ocean Thermal Energy Conversion (OTEC) | Seawater Cooling Depth Profile 8ºC (Summer Average)
This shapefile represents the seasonal summer depth profile to reach water at a temperature of 8ºC.
Sea water cooling can be used for industrial or residential cooling needs where heat must be rejected. A typical resource for direct air-conditioning applications is no warmer t...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation
2 Resources
0 Stars
In curation
Ocean Thermal Energy Conversion (OTEC) | Seawater Cooling Depth Profile 8ºC (Winter Average)
This shapefile represents the seasonal winter depth profile to reach water at a temperature of 8ºC.
Sea water cooling can be used for industrial or residential cooling needs where heat must be rejected. A typical resource for direct air-conditioning applications is no warmer t...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation
2 Resources
0 Stars
In curation
Admiralty Inlet Advanced Turbulence Measurements: Final Data and Code Archive
Data and code that is not already in a public location that is used in Kilcher, Thomson, Harding, and Nylund (2017) "Turbulence Measurements from Compliant Moorings Part II: Motion Correction" doi: 10.1175/JTECH-D-16-0213.1.
The links point to Python source code used in the publi...
Kilcher, L. et al National Renewable Energy Laboratory
Feb 01, 2011
11 Resources
0 Stars
Publicly accessible
11 Resources
0 Stars
Publicly accessible
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
21 Resources
0 Stars
Publicly accessible
21 Resources
0 Stars
Publicly accessible
Geothermal Case Studies on OpenEI
This submission contains links to Geothermal Areas on OpenEI that were completed as part of an effort to gather clean, unbiased information on which to build geothermal drilling prospects. The specific areas that were part of this focused effort, or *case studies*, are linked ind...
Young, K. National Renewable Energy Laboratory
Sep 30, 2014
19 Resources
0 Stars
Publicly accessible
19 Resources
0 Stars
Publicly accessible
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
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible
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
4 Resources
0 Stars
In curation
Geothermal Development and the Use of Categorical Exclusions Under NEPA
This study focuses primarily on the Categorial Exclusions (CX) process and its applicability to geothermal exploration. In this paper, we:
Provide generalized background information on CXs, including previous NEPA reports addressing CXs, the process for developing CXs, and the ro...
Young, K. and Levine, A. National Renewable Energy Laboratory
Sep 30, 2014
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
US Geothermal Electricity and Heat Market Analysis and Report
The power production data from FY19 is provided for U.S. geothermal power plants. The spreadsheet includes the plant name and type, nameplate capacity, summer capacity, winter capacity, and net generation for each power plant.
Robins, J. et al National Renewable Energy Laboratory
Jun 30, 2020
1 Resources
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible