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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 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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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
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
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1 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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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
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
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1 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
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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
0 Stars
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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
2 Resources
0 Stars
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2 Resources
0 Stars
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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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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
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2 Resources
0 Stars
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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
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4 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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EDX
###What is the Energy Data eXchange?
The Energy Data eXchange (EDX) was developed and is maintained by NETL-ORD
as an online system to support internal coordination and collaboration
as well as timely tech transfer of data-driven products across NETL's
research portfolios...
Rowan, C. and (NETL), N. National Renewable Energy Laboratory
Nov 25, 2014
1 Resources
0 Stars
In curation
1 Resources
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In curation
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
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
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
2 Resources
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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
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1 Resources
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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
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
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
2 Resources
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In curation
DOE User Facilities and RD Equipment
This dataset contains information about hundreds of designated user-facilities and R&D equipment funded by the U.S. Department of Energy and accessible to the private sector. These facilities reside at DOE's
Honey, K. and (DOE), U. National Renewable Energy Laboratory
Nov 25, 2014
1 Resources
0 Stars
In curation
1 Resources
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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
2 Resources
0 Stars
In curation