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Sample IEEE123 Bus system for OEDI SI

Time series load and PV data from an IEEE123 bus system. An example electrical system, named the OEDI SI feeder, is used to test the workflow in a co-simulation. The system used is the IEEE123 test system, which is a well studied test system (see link below to IEEE PES Test Feeder...

Elgindy, T. and Balasubramaniam, K. National Renewable Energy Laboratory

Sep 01, 2022
4 Resources
0 Stars
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Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI)

Super-Resolution for Renewable Resource Data and Urban Heat Islands (Sup3rUHI) introduces machine learning methods to incorporate high-resolution Urban Heat Island (UHI) effects into low-resolution historical reanalysis and future climate model datasets. The dataset includes model...

Buster, G. et al National Renewable Energy Lab (NREL)

Oct 16, 2024
2 Resources
0 Stars
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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

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

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
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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

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

Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts (Sup3rCC)

The Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts (Sup3rCC) data is a collection of 4km hourly wind, solar, temperature, humidity, and pressure fields for the contiguous United States under various climate change scenarios. Sup3rCC is downscaled ...

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

Apr 19, 2023
7 Resources
2 Stars
Publicly accessible

2024 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 (land-based) wind, offshore wind, and concentrating solar power (CSP) are included. Hourly profiles are provid...

Sergi, B. et al National Renewable Energy Laboratory (NREL)

Mar 25, 2025
9 Resources
0 Stars
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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
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