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...
保存先:
主要な著者: | , , , |
---|---|
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 |
タグ: |
タグ追加
タグなし, このレコードへの初めてのタグを付けませんか!
|
id |
my.utem.eprints.25802 |
---|---|
record_format |
eprints |
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 |
_version_ |
1728055221531181056 |
score |
13.251813 |