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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
Curated

Powder River Basin (WY, MT) Coal and Coalbed Methane: Evaluating and Revising 100 Years of Studies

The USGS published a USGS Professional Paper in 2010 entitled *After a century: Revised paleogene coal stratigraphy, correlation, and deposition, Powder River Basin, Wyoming and Montana*, (available: http://pubs.usgs.gov/pp/1777/). Information about the coal resources in this Powd...

Hallett, K. and USGS, . National Renewable Energy Laboratory

Sep 28, 2010
2 Resources
0 Stars
In curation

2014 Wind Turbine Gearbox Damage Distribution based on the NREL Gearbox Reliability Database

Despite the improvements in wind turbine gearbox design and manufacturing practices, the wind industry is still challenged by premature wind turbine gearbox failures. To help address this industry-wide challenge, a consortium called the Gearbox Reliability Collaborative (GRC) was ...

Sheng, S. National Renewable Energy Laboratory

Feb 09, 2015
1 Resources
0 Stars
In curation

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

Most Likely Extreme Response Analysis of an Ellipsoid Float Wave Energy Converter

Input data and heave results (unsteady RANS-VOF overset simulations performed in Star-CCM+) for a float with an ellipsoid geometry. Five extreme sea states were considered, as detailed in the conference paper "Application of the Most Likely Extreme Response Method for Wave Energy ...

Quon, E. National Renewable Energy Laboratory

Jun 17, 2016
7 Resources
0 Stars
Publicly accessible

Form EIA-861, "Annual Electric Power Industry Report."

This is an electric utility data file that includes such information as peak load, generation, electric purchases, sales, revenues, customer counts and demand-side management programs, green pricing and net metering programs, and distributed generation capacity. The data sou...

Aabakken, J. and Laboratory, N. National Renewable Energy Laboratory

Nov 25, 2014
4 Resources
0 Stars
In curation

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
0 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