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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 7, 2021.
Abstract: Controlled islanding is implemented to save the power system from experiencing blackouts during severe sequence line tripping. The power system is partitioned into several stand-alone islands by removing the optimal transmission line during controlled islanding execution. Since selecting the optimal transmission lines to be removed (cutsets) is important in this action, a good technique is required in order to determine the optimal islanding solution (lines to be removed). Thus, this paper developed two techniques, namely Modified Discrete Evolutionary Programming (MDEP) and Modified Discrete Particle Swarm Optimization (MDPSO) to determine the optimal islanding solution for controlled islanding implementation. The best technique among these two which is based on their capability of producing the optimal islanding solution with minimal objective function (minimal power flow disruption) will be selected to implement the controlled islanding. The performance of these techniques is evaluated through case studies using the IEEE 118-bus test system. The results show that the MDEP technique produces the best optimal islanding solution compared to the MDPSO and other previously published techniques.
N. Z. Saharuddin, I. Z. Abidin, H. Mokhlis and M.Y. Hassan, “Power System Controlled Islanding using Modified Discrete Optimization Techniques” International Journal of Advanced Computer Science and Applications(IJACSA), 12(7), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120756
@article{Saharuddin2021,
title = {Power System Controlled Islanding using Modified Discrete Optimization Techniques},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120756},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120756},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {7},
author = {N. Z. Saharuddin and I. Z. Abidin and H. Mokhlis and M.Y. Hassan}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.