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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主要な著者: Saharuddin, Nur Zawani, Zainal Abidin, Izham, Mokhlis, Hazlie, Hassan, Mohammad Yusri
フォーマット: 論文
言語:English
出版事項: Science and Information Organization 2021
オンライン・アクセス: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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spelling my.utem.eprints.258022022-03-21T09:53:50Z http://eprints.utem.edu.my/id/eprint/25802/ Power System Controlled Islanding Using Modified Discrete Optimization Techniques Saharuddin, Nur Zawani Zainal Abidin, Izham Mokhlis, Hazlie Hassan, Mohammad Yusri 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. Science and Information Organization 2021 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/25802/2/PAPER%20JURNAL%202021%20INTERNATIONAL%20JOURNAL.PDF Saharuddin, Nur Zawani and Zainal Abidin, Izham and Mokhlis, Hazlie and Hassan, Mohammad Yusri (2021) Power System Controlled Islanding Using Modified Discrete Optimization Techniques. International Journal of Advanced Computer Science and Applications, 12 (7). pp. 487-492. ISSN 2158-107X https://thesai.org/Downloads/Volume12No7/Paper_56-Power_System_Controlled_Islanding.pdf 10.14569/IJACSA.2021.0120756
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
description 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.
format Article
author Saharuddin, Nur Zawani
Zainal Abidin, Izham
Mokhlis, Hazlie
Hassan, Mohammad Yusri
spellingShingle Saharuddin, Nur Zawani
Zainal Abidin, Izham
Mokhlis, Hazlie
Hassan, Mohammad Yusri
Power System Controlled Islanding Using Modified Discrete Optimization Techniques
author_facet Saharuddin, Nur Zawani
Zainal Abidin, Izham
Mokhlis, Hazlie
Hassan, Mohammad Yusri
author_sort Saharuddin, Nur Zawani
title Power System Controlled Islanding Using Modified Discrete Optimization Techniques
title_short Power System Controlled Islanding Using Modified Discrete Optimization Techniques
title_full Power System Controlled Islanding Using Modified Discrete Optimization Techniques
title_fullStr Power System Controlled Islanding Using Modified Discrete Optimization Techniques
title_full_unstemmed Power System Controlled Islanding Using Modified Discrete Optimization Techniques
title_sort power system controlled islanding using modified discrete optimization techniques
publisher Science and Information Organization
publishDate 2021
url 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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score 13.251813