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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
Publicly accessible
Energy Innovation Portal
About the Energy Innovation Portal. The Energy Innovation Portal is a one-stop resource for Department of Energy (DOE) Energy Efficiency and Renewable Energy (EERE) technologies. This application enables users to locate technologies developed with DOE funding and available for lic...
Webmaster, . and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
1 Resources
0 Stars
In curation
1 Resources
0 Stars
In curation
Sedimentary Geothermal Feasibility in Eastern Nevada and Millard County, Utah Well Databases
In order to gather data to assess sedimentary geothermal feasibility in Nevada and Utah, state oil and gas and geothermal databases were serached for well files and well logs. Well data from the Nevada Bureau of Mines and Geology oil and gas and geothermal databases was mined for ...
Taverna, N. National Renewable Energy Laboratory
Nov 30, 2019
12 Resources
0 Stars
Publicly accessible
12 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
Curated
9 Resources
1 Stars
Curated
MOIS LabVIEW Software
Software developed in LabVIEW for the Modular Ocean Instrumentation System (MOIS) is provided. Two documents: MOIS User's Guide and MOIS Software Developer's Guide are included in the submission.
Nelson, E. National Renewable Energy Laboratory
Dec 03, 2015
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
Building Component Library
The Building Component Library (BCL) is the U.S. Department of Energy’s comprehensive online searchable library of energy modeling building blocks and descriptive metadata. Novice users and seasoned practitioners can use the freely available and uniquely identifiable components ...
Long, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
1 Resources
0 Stars
In curation
1 Resources
0 Stars
In curation
U.S. Electric Utility Companies and Rates: Look-up by Zipcode (Feb 2011)
This dataset, compiled by NREL using data from [ABB, the Velocity Suite](http://energymarketintel.com/) and the [U.S. Energy Information Administration dataset 861](http://www.eia.gov/electricity/data/eia861/), provides average residential, commercial and industrial electricity ra...
Huggins, J. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
5 Resources
0 Stars
Curated
5 Resources
0 Stars
Curated
Minnesota High Resolution Wind Resource
Annual average wind resource potential for Minnesota at a 50 meter height.
This data set has been validated by NREL and wind energy meteorological consultants. *Note:* This data is not suitable for micro-siting potential development projects.
###Original data
Data from [...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
3 Resources
0 Stars
In curation
3 Resources
0 Stars
In curation
The Open PV Project
Open PV Project is a collaborative effort between government, industry, and public that is compiling a comprehensive database of photovoltaic (PV) installation data for the U.S. Data for the project are voluntarily contributed from a variety of sources including utilities, install...
Support, O. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
2 Resources
0 Stars
In curation
2 Resources
0 Stars
In curation
U.S. Electric Utility Companies and Rates: Look-up by Zipcode (2018)
This dataset, compiled by NREL using data from [ABB, the Velocity Suite](http://energymarketintel.com/) and the [U.S. Energy Information Administration dataset 861](http://www.eia.gov/electricity/data/eia861/), provides average residential, commercial and industrial electricity ra...
Huggins, J. and Laboratory, N. National Renewable Energy Laboratory
Oct 25, 2019
4 Resources
0 Stars
Curated
4 Resources
0 Stars
Curated
U.S. Electric Utility Companies and Rates: Look-up by Zipcode (2017)
This dataset, compiled by NREL using data from [ABB, the Velocity Suite](http://energymarketintel.com/) and the [U.S. Energy Information Administration dataset 861](http://www.eia.gov/electricity/data/eia861/), provides average residential, commercial and industrial electricity ra...
Huggins, J. and Laboratory, N. National Renewable Energy Laboratory
Oct 24, 2018
4 Resources
0 Stars
Curated
4 Resources
0 Stars
Curated
U.S. Electric Utility Companies and Rates: Look-up by Zipcode (2016)
This dataset, compiled by NREL using data from [ABB, the Velocity Suite](http://energymarketintel.com/) and the [U.S. Energy Information Administration dataset 861](http://www.eia.gov/electricity/data/eia861/), provides average residential, commercial and industrial electricity ra...
Huggins, J. and Laboratory, N. National Renewable Energy Laboratory
Nov 13, 2017
4 Resources
0 Stars
Curated
4 Resources
0 Stars
Curated
U.S. Electric Utility Companies and Rates: Look-up by Zipcode (2015)
This dataset, compiled by NREL using data from [ABB, the Velocity Suite](http://energymarketintel.com/) and the [U.S. Energy Information Administration dataset 861](http://www.eia.gov/electricity/data/eia861/), provides average residential, commercial and industrial electricity ra...
Huggins, J. and Laboratory, N. National Renewable Energy Laboratory
Oct 19, 2016
4 Resources
0 Stars
Curated
4 Resources
0 Stars
Curated
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
1 Resources
0 Stars
Publicly accessible
U.S. Electric Utility Companies and Rates: Look-up by Zipcode (2013)
This dataset, compiled by NREL using data from [ABB, the Velocity Suite](http://energymarketintel.com/) and the [U.S. Energy Information Administration dataset 861](http://www.eia.gov/electricity/data/eia861/), provides average residential, commercial and industrial electricity ra...
Huggins, J. and Laboratory, N. National Renewable Energy Laboratory
Jul 13, 2015
5 Resources
0 Stars
Curated
5 Resources
0 Stars
Curated
U.S. Electric Utility Companies and Rates: Look-up by Zipcode (2014)
This dataset, compiled by NREL using data from [ABB, the Velocity Suite](http://energymarketintel.com/) and the [U.S. Energy Information Administration dataset 861](http://www.eia.gov/electricity/data/eia861/), provides average residential, commercial and industrial electricity ra...
Huggins, J. and Laboratory, N. National Renewable Energy Laboratory
Dec 01, 2015
7 Resources
0 Stars
Curated
7 Resources
0 Stars
Curated
Sedimentary Geothermal Feasibility in Nevada, Western Utah, Colorado, and the Gulf Coast Region of Texas Final Report
The objectives of this project were to (1) perform a literature review of sedimentary geothermal resources, (2) identify data sources and develop data-collection methodologies that characterize selected resources, (3) screen sedimentary basins and formations for sedimentary geothe...
Johnston, H. et al National Renewable Energy Laboratory
Jul 01, 2020
1 Resources
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible