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National Renewable Energy Laboratory×

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

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

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

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

Geothermal Drilling and Completions: Petroleum Practices Technology Transfer

NREL and the Colorado School of Mines (SURGE) conducted research in FY14 to identify petroleum drilling and completion practices (methods and technologies) that can be transferred to geothermal drilling and completion, to provide the geothermal industry with more effective, lower ...
Visser, C. et al National Renewable Energy Laboratory
Sep 30, 2014
1 Resources
0 Stars
Publicly accessible

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
Publicly accessible

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

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

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
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
Publicly accessible

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

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
Publicly accessible

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

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
Publicly accessible

NREL GIS Data: Alaska High Resolution Wind Resource

Annual average wind resource potential for the main section of the state of Alaska. Note: we do not have a complete 50m coverage for the entire state. The wind power resource estimates were produced by AWS TrueWind using their MesoMap system and historical weather data under co...
Wood, J. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation

NREL GIS Data: Arkansas High Resolution Wind Resource

_Abstract:_ Annual average wind resource potential for the state of Arkansas at a 50 meter height. _Purpose:_ Provide information on the wind resource development potential within the state of Arkansas. _Supplemental Information:_ This data set has been validated by NREL ...
Wood, J. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation

NREL GIS Data: Arizona High Resolution Wind Resource

_Abstract:_ Annual average wind resource potential for the state of Arizona at a 50 meter height. This dataset will be replaced when the southwest region has been completed, and the data may change when this region has been completed. _Purpose:_ Provide information on the win...
Wood, J. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation

Wave Tank Characterization Data

This data set was collected from a 16k gallon single paddle type wave tank after adjustments were made to the transfer function in the control software. The file names describe the commanded wave height and period which can then be compared with the actual measured height and peri...
Candon, C. et al National Renewable Energy Laboratory
Jul 14, 2023
1 Resources
0 Stars
Publicly accessible

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
Publicly accessible

NREL GIS Data: Alaska Low Resolution Wind Resource

Annual average wind resource potential for the United States (low resolution) ### License Info DISCLAIMER NOTICE This GIS data was developed by the National Renewable Energy Laboratory (?NREL?), which is operated by the Alliance for Sustainable Energy, LLC for the U.S. Depa...
Twong, . and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation

NREL GIS Data: Continental United States Low Resolution Wind Resource

Annual average wind resource potential for the United States (low resolution) ### License Info DISCLAIMER NOTICE This GIS data was developed by the National Renewable Energy Laboratory (?NREL?), which is operated by the Alliance for Sustainable Energy, LLC for the U.S. Depa...
Twong, . and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation

NREL GIS Data: Hawaii Low Resolution Wind Resource

Annual average wind resource potential of Hawaii (low resolution) ### License Info DISCLAIMER NOTICE This GIS data was developed by the National Renewable Energy Laboratory (NREL), which is operated by the Alliance for Sustainable Energy, LLC for the U.S. Department of Ener...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation

NREL GIS Data: U.S. Atlantic Coast Offshore Windspeed 90m Height High Resolution

This dataset is a geographic shapefile generated from the original raster data. The original raster data resolution is a 200-meter cell size. The data provide an estimate of annual average wind speed at 90 meter height above surface for specific offshore regions of the United Stat...
Wood, J. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation

NREL GIS Data: Afghanistan and Pakistan High Resolution Wind

Shapefile for NREL's high-resolution Afghanistan and Pakistan wind resource data. ### License Info DISCLAIMER NOTICE This GIS data was developed by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC for the U.S. De...
Wood, J. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation

NREL GIS Data: Texas High Resolution Wind Resource

Annual average wind resource development potential for the state of Texas. This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile is in a UTM zone 19,...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation
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