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National Renewable Energy Laboratory×

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

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

Residential Energy Expenditures for Water Heating (2005)

Provides total and average household expenditures on energy for water heating in the United States in 2005. The data was collected as part of the Residential Energy Consumption Survey (RECS). RECS is a national survey that collects residential energy-related data. The survey col...
Hallett, K. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
3 Resources
0 Stars
In curation

Residential Energy Consumption Survey Results: Total Energy Consumption, Expenditures, and Intensities (2005)

The Residential Energy Consumption Survey (RECS) is a national survey that collects residential energy-related data. The 2005 survey collected data from 4,381 households in housing units statistically selected to represent the 111.1 million housing units in the U.S. Data were obta...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
3 Resources
0 Stars
In curation

Form EIA-860 Annual Electric Generator Report

The Form EIA-860 is a generator-level survey that collects specific information about existing and planned generators and associated environmental equipment at electric power plants with 1 megawatt or greater of combined nameplate capacity. The survey data is summarized in...
Aabakken, J. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation

Solar Resources by Class and Country

These estimates are derived from the best available solar resource data available to NREL. Resources are organized by class and country. Resolution varies spatially from 1 km to 1 degree (approximately 100 km) depending on the data source. High spatial resolution datasets (1 km...
Heimiller, D. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
4 Resources
1 Stars
In curation

Afghanistan Wind Power Density at 50-m Above Ground Level GIS Data

This dataset was developed by the National Renewable Energy Laboratory (NREL) for the [U.S. Agency for International Development'](http://www.usaid.gov/)s (USAID) [South Asia Regional Initiative for Energy Cooperation](http://www.sari-energy.org/) (SARI/E). The dataset contains Wi...
Langle, N. National Renewable Energy Laboratory
Nov 25, 2014
3 Resources
0 Stars
Publicly accessible

NREL GIS Data: Hawaii Low Resolution Concentrating Solar Power Resource

_Abstract:_ Monthly and annual average solar resource potential for Hawaii. _Purpose:_ Provide information on the solar resource potential for Hawaii. The insolation values represent the average solar energy available to a flat plate collector, such as a photovoltaic panel, o...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation

NREL GIS Data: Alaska Low Resolution Photovoltaic Solar Resource

_Abstract:_ Monthly and annual average solar resource potential for Alaska. _Purpose:_ Provide information on the solar resource potential for Alaska. The insolation values represent the average solar energy available to a flat plate collector, such as a photovoltaic panel, o...
Wood, J. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation

NREL GIS Data: Continental United States Photovoltaic Low Resolution

_Abstract:_ Monthly and annual average solar resource potential for the lower 48 states of the United States of America. _Purpose:_ Provide information on the solar resource potential for the United States of America lower 48 states. The insolation values represent the averag...
Wood, J. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation

NREL GIS Data: Hawaii Low Resolution Photovoltaic Solar Resource

_Abstract:_ Monthly and annual average solar resource potential for Hawaii. _Purpose:_ Provide information on the solar resource potential for Hawaii. The insolation values represent the average solar energy available to a flat plate collector, such as a photovoltaic panel, o...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation

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

NREL GIS Data: Seasonal and diurnal data from Afghanistan surface weather stations

This dataset was developed by the National Renewable Energy Laboratory (NREL) for the [U.S. Agency for International Development'](http://www.usaid.gov/)s (USAID) [South Asia Regional Initiative for Energy Cooperation](http://www.sari-energy.org) (SARI/E). The dataset contains gra...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation

NREL GIS Data: Alaska Low Resolution Concentrating Solar Power Resource

_Abstract:_ Monthly and annual average solar resource potential for Alaska. _Purpose:_ Provide information on the solar resource potential for Alaska. The insolation values represent the average solar energy available to a flat plate collector, such as a photovoltaic panel, o...
Wood, J. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation

Form EIA-906, EIA-920, and EIA-923 Databases

The EIA-906, EIA-920, EIA-923 and predecessor forms provide monthly and annual data on generation and fuel consumption at the power plant and prime mover level. A subset of plants, steam-electric plants 10 MW and above, also provides boiler level and ge...

Aabakken, J. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
5 Resources
0 Stars
In curation

NREL GIS Data: Continental United States High Resolution Concentrating Solar Power

_Abstract:_ Monthly and annual average solar resource potential for the lower 48 states of the United States of America. _Purpose:_ Provide information on the solar resource potential for the for the lower 48 states of the United States of America. _Supplemental Informatio...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation

NREL Wave Energy Assessment for the United States and Puerto Rico

This dataset estimates the naturally available and technically recoverable U.S. wave energy resources, using a 51-month Wavewatch III hindcast database developed especially for this study by National Oceanographic and Atmospheric Administration's (NOAA's) National Centers for Envi...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
9 Resources
0 Stars
In curation

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