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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
2 Stars
Publicly accessible
8 Resources
2 Stars
Publicly accessible
Topology-Based Machine-Learning for Modeling Power-System Responses to Contingencies
This is the companion dataset to the presentation NREL/PR-6A20-77485, which was presented at the 2020 Joint Statistical Meeting on August 3, 2020. Developed for the machine-learning predictive modeling of power-system responses to disruptions, it contains results of power-system c...
BushNational Renewable Energy Laboratory
Aug 01, 2020
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
PNNL Distribution System State Estimator Docker Image
This is the docker image for Pacific Northwest National Laboratory's (PNNL) distribution system state estimator (DSSE) used for the demo of OEDI-SI platform. To support the operation of modern distribution systems, operators require real-time visibility into system states. Due to ...
Bhatti, B. et al Pacific Northwest National Laboratory
Jul 10, 2023
6 Resources
2 Stars
Publicly accessible
6 Resources
2 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
Publicly accessible
9 Resources
1 Stars
Publicly accessible
Peregrine HPC Energy Research
Complete power and performance metric data for 10,000 jobs randomly selected from two years of the Peregrine system’s operation (all jobs prior to October, 2015). Complete power and performance metric data for jobs run on the Peregrine system in April, 2015. Related Publica...
PhillipsNational Renewable Energy Laboratory
Apr 10, 2024
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
NREL HPC Eagle Jobs Data
Three months of Eagle jobs data including Slurm metadata and derived power use characterization.
Eash and EganNational Renewable Energy Laboratory
Nov 24, 2020
3 Resources
0 Stars
Publicly accessible
3 Resources
0 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
4 Resources
0 Stars
Publicly accessible