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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
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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
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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
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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
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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
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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
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Training dataset and results for geothermal exploration artificial intelligence, applied to Brady Hot Springs and Desert Peak

The submission includes the labeled datasets, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model: brady_som_output.gri, brady_som_output.grd, brady_som_output.* desert_som_output.gri, desert_som_output.grd, desert_som_outpu...

Moraga, J. et al Colorado School of Mines

Sep 01, 2020
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Artificial Intelligence for Robust Integration of AMI and Synchrophasor Data to Significantly Boost Solar Adoption

The overarching goal of the project is to create a highly efficient framework of machine learning (ML) methods that provide consistent and accurate real-time knowledge of system states from diverse advanced metering infrastructure (AMI) devices and phasor measurement units (PMUs) ...

Ayyanar, R. et al Arizona State University

Feb 01, 2025
12 Resources
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Airfoil Computational Fluid Dynamics 9k shapes, 2 AoA's

This dataset contains aerodynamic quantities including flow field values (momentum, energy, and vorticity) and summary values (coefficients of lift, drag, and momentum) for 8,996 airfoil shapes, computed using the HAM2D CFD (computational fluid dynamics) model. The airfoil shapes ...

Ramos, D. et al National Renewable Energy Laboratory (NREL)

Feb 10, 2023
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Airfoil Computational Fluid Dynamics 2k shapes, 25 AoA's, 3 Re numbers

This dataset contains aerodynamic quantities including flow field values (momentum, energy, and vorticity) and summary values (coefficients of lift, drag, and momentum) for 1,830 airfoil shapes computed using the HAM2D CFD (computational fluid dynamics) model. The airfoil shapes w...

Ramos, D. et al National Renewable Energy Laboratory (NREL)

Feb 10, 2023
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DEEPEN Data Catalog for Magmatic Geothermal Systems in the United States

This data catalog contains information related to the Training Site Analysis for the Geothermica project "DE-risking Exploration of geothermal Plays in magmatic ENvironments (DEEPEN)." The DEEPEN project aims to reduce exploration risk for geothermal fluids in magmatic systems by ...

Kolker, A. et al National Renewable Energy Laboratory

Sep 30, 2021
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Dataset for Evaluation of Extreme Weather Impacts on Utility-Scale Photovoltaic Plant Performance in the United States

This dataset is a fusion of three data types (operations and maintenance tickets, weather data, and production data) that was used to support machine learning analysis and evaluation of drivers for low performance at photovoltaic (PV) sites during compound, extreme weather events....

Gunda, T. and Jackson, N. Sandia National Laboratories

Apr 01, 2021
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Flow Redirection and Induction in Steady State (FLORIS) Wind Plant Power Production Data Sets

This dataset contains turbine and plant-level power outputs for 252,500 cases of diverse wind plant layouts operating under a wide range of yawing and atmospheric conditions. The power outputs were computed using the Gaussian wake model in NREL's FLOw Redirection and Induction in ...

Ramos, D. et al National Renewable Energy Laboratory

Feb 12, 2021
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Processed Lab Data for Neural Network-Based Shear Stress Level Prediction

Machine learning can be used to predict fault properties such as shear stress, friction, and time to failure using continuous records of fault zone acoustic emissions. The files are extracted features and labels from lab data (experiment p4679). The features are extracted with a n...

Marone, C. et al Pennsylvania State University

May 14, 2021
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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
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EGS Collab Experiment 1: DNA tracer data on transport through porous media

This submission contains DNA tracer data that supports the analysis and conclusions of the publication, "DNA tracer transport through porous media The effect of DNA length and adsorption." https://doi.org/10.1029/2020WR028382. This experiment used DNA as an artificial reservoir t...

Zhang, Y. et al Stanford University

Nov 21, 2020
3 Resources
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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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Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk

In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity producti...

Siler, D. et al United States Geological Survey

Oct 01, 2021
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Acoustic Camera Debris Imaging Tanana River Test Site 2025

This data is raw acoustic camera recordings from two different acoustic cameras deployed in the Tanana River at the University of Alaska Fairbanks's (UAF's) Tanana River Test Site near Nenana, Alaska. The purpose of this data collection is to develop and train algorithms to identi...

Loeffler, B. et al University of Alaska Fairbanks

Jun 19, 2025
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DEPRECATED. SEE UPDATE LINK BELOW. Distribution System Upgrade Unit Cost Database

REVISED 1/2/2019. SEE UPDATE LINK BELOW. This database contains unit cost information for different components that may be used to integrate distributed photovotaic D-PV systems onto distribution systems. Some of these upgrades and costs may also apply to integration of other dis...

HorowitzNational Renewable Energy Laboratory

Nov 20, 2017
3 Resources
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Industrial Assessment Centers Database

The Industrial Assessment Centers (IAC) Database is a collection of all the publicly available data from energy efficiency assessments conducted by IACs at small and medium-sized industrial facilities. The data includes information beginning in 1981 on the type of facility assesse...

Smegal, J. and Muller, M. Office of Energy Efficiency & Renewable Energy

Nov 25, 2014
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2019 Distribution System Upgrade Unit Cost Database Current Version

IMPORTANT NOTE: This is the current version of NREL's Distribution System Unit cost Database and should be considered the most up-to-date. Compared to the previous version (https//data.nrel.gov/submissions/77) this database has additional data points and has been modified for impr...

HorowitzNational Renewable Energy Laboratory

Jan 02, 2019
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SOLTHERM Thermodynamic Database for Geochemical Modeling

This data submission is a link to a thermodynamic database maintained by the University of Oregon. The data at this link are not 'data results' from sampling. The data at this link comprise a thermodynamic database for aqueous species, minerals, and gases, including data for stoic...

Palandri, J. University of Oregon

Oct 07, 2015
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LLMs for EV Infrastructure Permitting

The Electric Vehicle (EV) charging permitting processes' database is a novel, multi-jurisdictional resource designed to contain the required codes and compliances in a structured database. Within this database are three tables, each structured with 287 columns, designed to capture...

Renganathan, U. et al National Renewable Energy Lab (NREL)

Sep 24, 2025
12 Resources
1 Stars
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Argonne Geothermal Geochemical Database v2.0

A database of geochemical data from potential geothermal sources aggregated from multiple sources as of March 2010. The database contains fields for the location, depth, temperature, pH, total dissolved solids concentration, chemical composition, and date of sampling. A separate...

Harto, C. Argonne National Laboratory

May 22, 2013
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