Time-Domain Simulation Samples for Frequency-Constrained Look-Ahead Energy Scheduling

Dataset, by Mingjian Tuo, Jul 24, 2023.
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This is the raw dataset (12.74 GB) for over 8,000 samples from power system time-domain simulation on the IEEE 24-bus test system. This dataset was used for our frequency-constrained SCUC studies that led to multiple papers. This dataset can also be used for frequency-constrained OPF studies.

The download time could be a few hours long due to the size of this dataset. So, you may need to have stable internet to successfully download it.

Test System Description:

  • The IEEE 24-bus power system used here is one area out of the three-area system modified IEEE RTS-96 reliability test system (73-bus). The original reference is: “The IEEE Reliability Test System-1996. A report prepared by the Reliability Test System Task Force of the Application of Probability Methods Subcommittee” and link is here.

Citation:

If you use any module/data here for your work, please cite the following papers as your references:

  1. Mingjian Tuo and Xingpeng Li, “Deep Learning based Security-Constrained Unit Commitment Considering Locational Frequency Stability in Low-Inertia Power Systems”, 54th North American Power Symposium, Salt Lake City, UT, USA, Oct. 2022.
  2. Mingjian Tuo and Xingpeng Li, “Active Linearized Sparse Neural Network-based Frequency-Constrained Unit Commitment”, arXiv:2307.04880, Jul. 2023.

Paper1 website: https://rpglab.github.io/papers/MJ-Tuo_DL_SCUC_LFS-NAPS/

Paper2 website: https://rpglab.github.io/papers/MJ-Tuo-ALSNN-RCUC/

Contributions:

Mingjian Tuo created this dataset. Xingpeng Li supervised this work.

Contact:

Dr. Xingpeng Li

University of Houston

Email: xli83@central.uh.edu

Website: https://rpglab.github.io/

License:

This work is licensed under the terms of the Creative Commons Attribution 4.0 (CC BY 4.0) license.

Disclaimer:

The author doesn’t make any warranty for the accuracy, completeness, or usefulness of any information disclosed; and the author assumes no liability or responsibility for any errors or omissions for the information (data/code/results etc) disclosed.