Power System Controlled Islanding Using Modified Discrete Optimization Techniques
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...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Science and Information Organization
2021
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| Online Access: | http://eprints.utem.edu.my/id/eprint/25802/2/PAPER%20JURNAL%202021%20INTERNATIONAL%20JOURNAL.PDF http://eprints.utem.edu.my/id/eprint/25802/ https://thesai.org/Downloads/Volume12No7/Paper_56-Power_System_Controlled_Islanding.pdf |
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| Summary: | 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. |
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