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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
0 Stars
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1 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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6 Resources
0 Stars
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Topology-Based Machine-Learning for Modeling Power-System Responses to Contingencies
This is the companion dataset to the presentation NREL/PR-6A20-77485, which was presented at the 2020 Joint Statistical Meeting on August 3, 2020. Developed for the machine-learning predictive modeling of power-system responses to disruptions, it contains results of power-system c...
BushNational Renewable Energy Laboratory
Aug 01, 2020
2 Resources
0 Stars
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2 Resources
0 Stars
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Fuel Cell Inverter Transition Between Modes of Operation (Grid-Forming and Grid-Following)
This data set shows the operation of the fuel cell inverter under grid-forming mode of operation, grid-following mode of operation and transition between the two modes.
Nemsow, . et al National Renewable Energy Laboratory
Dec 23, 2024
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
Battery Inverter Experimental Data
The increase in power electronic based generation sources require accurate modeling of inverters. Accurate modeling requires experimental data over wider operation range. We used 30 kW off-the-shelf grid following battery inverter in the experiments. We used controllable AC supply...
Prabakar, . et al National Renewable Energy Laboratory
Jan 06, 2023
2 Resources
0 Stars
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2 Resources
0 Stars
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Fuel Cell Inverter Dataset
This data set contains the three phase AC voltage, three phase AC current, DC voltage and DC current. These data sets were captured during fuel cell inverter operation in grid-connected dispatch, islanded load changes, transition from grid-connected mode to islanded mode and vice-...
Prabakar, . et al National Renewable Energy Laboratory
Oct 21, 2024
1 Resources
0 Stars
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1 Resources
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Publicly accessible
PV Inverter Experimental Data
The increase in power electronic based generation sources require accurate modeling of inverters. Accurate modeling requires experimental data over wider operation range. We used 20 kW off-the-shelf grid following PV inverter in the experiments. We used controllable AC supply and ...
Prabakar, . et al National Renewable Energy Laboratory
Jan 06, 2023
2 Resources
0 Stars
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2 Resources
0 Stars
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Split Phase Inverter Data
The increase in power electronic based generation sources require accurate modeling of inverters. Accurate modeling requires experimental data over wider operation range. We used 8.35 kW off-the-shelf grid following split phase PV inverter in the experiments. We used controllable ...
Prabakar, . et al National Renewable Energy Laboratory
Mar 23, 2023
2 Resources
0 Stars
Publicly accessible
2 Resources
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PV Inverter Experimental Dataset Version 2 with 100 Percent Power
The increase in power electronic based generation sources require accurate modeling of inverters. Accurate modeling requires experimental data over wider operation range. We used 20 kW off-the-shelf grid following PV inverter in the experiments. We used controllable AC supply and ...
Prabakar, . et al National Renewable Energy Laboratory
Nov 10, 2023
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
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OPFLearnData: Dataset for Learning AC Optimal Power Flow
The datasets are resulting from OPFLearn.jl, a Julia package for creating AC OPF datasets. The package was developed to provide researchers with a standardized way to efficiently create AC OPF datasets that are representative of more of the AC OPF feasible load space compared to t...
Joswig-Jones, . et al National Renewable Energy Laboratory
Oct 26, 2021
12 Resources
0 Stars
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12 Resources
0 Stars
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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
0 Stars
Publicly accessible
4 Resources
0 Stars
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National Forest System Lands in geothermal potential area
A GIS layer from the BLM nationwide PEIS of lands within the U.S. National Forest system that contain geothermal potential. The GIS layer contains .SBX, .XML, .SHX, .DBF (.XLS), .PRJ, .SBN, and .SHP data.
### License Info
Made open by BLM. http://www.doi.gov/privacy.cfm
Hill, G. and (BLM), U. National Renewable Energy Laboratory
Jul 29, 2014
2 Resources
0 Stars
In curation
2 Resources
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In curation
BuildingsBench: A Large-Scale Dataset of 900K Buildings and Benchmark for Short-Term Load Forecasting
The BuildingsBench datasets consist of:
Buildings-900K: A large-scale dataset of 900K buildings for pretraining models on the task of short-term load forecasting (STLF). Buildings-900K is statistically representative of the entire U.S. building stock.
7 real residential and com...
Emami, P. and Graf, P. National Renewable Energy Laboratory
Dec 31, 2018
6 Resources
1 Stars
Publicly accessible
6 Resources
1 Stars
Publicly accessible
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
Publicly accessible
9 Resources
1 Stars
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Gulf of Mexico Outer Continental Shelf Mapping Data
The US Department of Interior's (DOI) Bureau of Ocean Energy Management, Regulation and Enforcement (BOEMRE) published geographic data of offshore activities in the Gulf of Mexico Outer Continental Shelf (OCS) area. The data were built from the Technical Information Management Sys...
Hallett, K. and (BOEMRE), U. National Renewable Energy Laboratory
May 30, 2007
14 Resources
0 Stars
In curation
14 Resources
0 Stars
In curation
Renewable Energy Potential Model: Priority Geothermal Leasing Areas ReEDs Results
This dataset contains the results of a study conducted by the National Renewable Energy Laboratory (NREL) to identify potential future priority geothermal leasing areas on Bureau of Land Management (BLM) and United States Forest Service (USFS) lands. The analysis uses the Regional...
Smith, F. et al National Renewable Energy Laboratory
May 20, 2024
4 Resources
0 Stars
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4 Resources
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DEEPEN Global Standardized Categorical Exploration Datasets for Magmatic Plays
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
4 Resources
0 Stars
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4 Resources
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Residential Loads May 2, 2016
Power measurements for various residential appliances in the System Performance Lab (SPL) in the Energy System Integration Facility (ESIF). This data set was collected as part of a project evaluating a new type of power meter that can reduce the cost of submetering many circuits i...
SparnNational Renewable Energy Laboratory
Jun 14, 2016
1 Resources
0 Stars
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1 Resources
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GDR Data Management and Best Practices for Submitters and Curators
Resources for GDR data submitters and curators, including training videos, step-by-step guides on data submission, and detailed documentation of the GDR. The Data Management and Submission Best Practices document also contains API access and metadata schema information for develo...
Weers, J. et al National Renewable Energy Laboratory
Mar 31, 2021
3 Resources
0 Stars
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3 Resources
0 Stars
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MHKDR Data Management and Best Practices for Submitters and Curators
Resources for MHKDR data submitters and curators, including training videos, step-by-step guides on data submission, and detailed documentation of the MHKDR. The Data Management and Submission Best Practices document also contains API access and metadata schema information for dev...
Weers, J. et al National Renewable Energy Laboratory
Dec 15, 2021
3 Resources
0 Stars
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3 Resources
0 Stars
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Water DAMS Data Management and Best Practices for Submitters and Curators
Resources for Water DAMS data submitters and curators, including training videos, step-by-step guides on data submission, and detailed documentation of Water DAMS. The Data Management and Submission Best Practices document also contains API access and metadata schema information ...
Weers, J. et al National Renewable Energy Laboratory
Aug 01, 2020
3 Resources
0 Stars
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3 Resources
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OEDI Data Management and Best Practices for Submitters and Curators
Resources for OEDI data submitters and curators, including training videos, step-by-step guides on data submission, and detailed documentation of OEDI. The Data Management and Submission Best Practices document also contains API access and metadata schema information for developer...
Weers, J. et al National Renewable Energy Laboratory
Sep 01, 2022
3 Resources
1 Stars
Publicly accessible
3 Resources
1 Stars
Publicly accessible
Bureau of Land Management (BLM) Public Lands in geothermal potential area
The dataset is a GIS layer displaying BLM public lands that lie within an area that has geothermal potential. The GIS layer contains .SBX, .XML, .SHX, .DBF (.XLS), .PRJ, .SBN, and .SHP data.
### License Info
Open information http://www.doi.gov/privacy.cfm
Hill, G. and (BLM), U. National Renewable Energy Laboratory
Jul 29, 2014
2 Resources
0 Stars
In curation
2 Resources
0 Stars
In curation
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
1 Resources
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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
2 Resources
0 Stars
In curation