Feasibility Layer Aided ML for SCUC
This set of codes implements our TPWRS paper “Feasibility Layer Aided Machine Learning Approach for Day-Ahead Operations”.
Test Power Systems
There are five test power systems used in this work:
- IEEE 24-bus system: one area of the IEEE 73-bus system.
- IEEE 73-bus system: the original data of this test system are described in this reference: “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.
- IEEE 118-bus system: the original data of this test case are from the link below (in IEEE Common Data Format (ieee118cdf.txt)): https://labs.ece.uw.edu/pstca/pf118/ieee118cdf.txt
- South-Carolina (SC) synthetic 500-bus system: the original data of this test system are from https://electricgrids.engr.tamu.edu/electric-grid-test-cases/activsg500/
- The 2383-bus Polish system: the original data of this test system are from matpower (https://matpower.org/). The data were provided by Roman Korab (roman.korab@polsl.pl).
Citation:
If you use any of our codes/data for your work, please cite the following papers as your reference:
Arun Venkatesh Ramesh and Xingpeng Li, “Feasibility Layer Aided Machine Learning Approach for Day-Ahead Operations”, IEEE Transactions on Power Systems, Apr. 2023.
(DOI: 10.1109/TPWRS.2023.3266192)
Paper website: https://rpglab.github.io/papers/ArunR_FL-ML-R-SCUC/
Contributions:
Arun Venkatesh Ramesh developed this set of programs/data. 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.