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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
County-Level Hourly Renewable Capacity Factor Dataset for the ReEDS Model
This dataset contains hourly capacity factors for each renewable resource class and region (in this case, county). Technologies like large-scale utility PV (UPV), onshore wind, offshore wind, and concentrating solar power (CSP) are included. The dataset contains 7 years of hourly ...
Cole, W. et al National Renewable Energy Laboratory (NREL)
Aug 01, 2023
5 Resources
2 Stars
Publicly accessible
5 Resources
2 Stars
Publicly accessible
Flow Redirection and Induction in Steady State (FLORIS) Wind Plant Power Production Data Sets
This dataset contains turbine and plant-level power outputs for 252,500 cases of diverse wind plant layouts operating under a wide range of yawing and atmospheric conditions. The power outputs were computed using the Gaussian wake model in NREL's FLOw Redirection and Induction in ...
Ramos, D. et al National Renewable Energy Laboratory
Feb 12, 2021
5 Resources
0 Stars
Publicly accessible
5 Resources
0 Stars
Publicly accessible
Photovoltaic Data Acquisition (PVDAQ) Public Datasets
The NREL PVDAQ is a large-scale time-series database containing system metadata and performance data from a variety of experimental PV sites and commercial public PV sites. The datasets are used to perform on-going performance and degradation analysis. Some of the sets can exhibit...
Deline, C. et al NREL
Dec 21, 2021
8 Resources
1 Stars
Publicly accessible
8 Resources
1 Stars
Publicly accessible
ARPA-E Grid Optimization (GO) Competition Challenge 2
The ARPA-E Grid Optimization (GO) Competition Challenge 2, from 2020 to 2021, expanded upon the problem posed in Challenge 1 by adding adjustable transformer tap ratios, phase shifting transformers, switchable shunts, price-responsive demand, ramp rate constrained generators and l...
Elbert, S. et al Pacific Northwest National Laboratory
Sep 20, 2024
29 Resources
0 Stars
Publicly accessible
29 Resources
0 Stars
Publicly accessible
ARPA-E Grid Optimization (GO) Competition Challenge 1
The ARPA-E Grid Optimization (GO) Competition Challenge 1, from 2018 to 2019, focused on the basic Security Constrained AC Optimal Power Flow problem (SCOPF) for a single time period. The Challenge utilized sets of unique datasets generated by the ARPA-E GRID DATA program. Each da...
Elbert, S. et al Pacific Northwest National Laboratory
Aug 05, 2024
29 Resources
0 Stars
Publicly accessible
29 Resources
0 Stars
Publicly accessible
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
39 Resources
1 Stars
Publicly accessible