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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

Global Energy & Mining Data, World Bank (1970 2007)

Alternative and Nuclear Energy: Percentage of Total Energy Use Combustible Renewables and Waste: Metric Tons of Oil Equivalent Combustible Renewable and Waste: Percentage of Total Energy Electric Power Consumption Electric Power Transmission and Distribution Losses Electric Power ...

Brodt-Giles, D. and Bank, W. National Renewable Energy Laboratory

Oct 12, 2013
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
1 Stars
Publicly accessible

Typical Solar Years (TSYs) and Typical Wind Years (TWYs) for the Assessment of PV System and Wind Turbine Performance

This dataset comprises Typical Solar Years (TSYs) and Typical Wind Years (TWYs) for the efficient assessment of PV system and wind turbine performance for over 2,000 locations across the U.S. TSYs and TWYs are single synthetic years generated from the National Aeronautics and Spac...

Zeng, Z. et al Argonne National Laboratory

Jul 14, 2024
7 Resources
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Solar-to-Grid Public Data File for Utility-scale (UPV) and Distributed Photovoltaics (DPV) Generation, Capacity Credit, and Value for 2012-2020

Lawrence Berkeley National Laboratory (Berkeley Lab) estimates hourly project-level generation data for utility-scale solar projects and hourly county-level generation data for residential and non-residential distributed photovoltaic (PV) systems in the seven organized wholesale m...

Seel, J. et al Lawrence Berkeley National Lab

Oct 01, 2021
4 Resources
1 Stars
Publicly accessible

INTEGRATE Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements

The INTEGRATE (Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements) project is developing a new inverse-design capability for the aerodynamic design of wind turbine rotors using invertible neural networks. This AI-based design techno...

Vijayakumar, G. et al National Renewable Energy Laboratory (NREL)

May 04, 2021
8 Resources
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Solar-to-Grid Public Data File for Utility-scale (UPV) and Distributed Photovoltaics (DPV) Generation, Capacity Credit, and Value

Seel, J. et al Lawrence Berkeley National Lab

Sep 30, 2020
5 Resources
0 Stars
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ARPA-E Grid Optimization (GO) Competition Challenge 3

Synthetic Input Data and Team Results for the GO Competition Challenge 3 for Events 1 4 and the Sandbox, along with problem and format descriptions and code to validate data and solutions, are available here. Data for industry scenarios will not be made public. The Grid Optimizat...

Elbert, S. et al Pacific Northwest National Laboratory

May 02, 2024
39 Resources
1 Stars
Publicly accessible

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