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Power System Controlled Islanding using Modified Discrete Optimization Techniques

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dc.contributor.authorSaharuddin N.Z.en_US
dc.contributor.authorAbidin I.Z.en_US
dc.contributor.authorMokhlis H.en_US
dc.contributor.authorHassan M.Y.en_US
dc.contributor.authorid55613455300en_US
dc.contributor.authorid35606640500en_US
dc.contributor.authorid8136874200en_US
dc.contributor.authorid55322556200en_US
dc.date.accessioned2023-05-29T09:11:19Z
dc.date.available2023-05-29T09:11:19Z
dc.date.issued2021
dc.descriptionComputer programming; Distributed power generation; Electric lines; Electric power system control; Electric power transmission; Light transmission; Particle swarm optimization (PSO); Power control; Controlled islanding; Discrete particle swarm optimization; Evolutionary programming techniques; Minimal power; Minimal power flow disruption; Modified discrete evolutionary programming technique; Modified discrete particle swarm optimization technique; Particle swarm optimization technique; Power flows; Power imbalance; Electric load flowen_US
dc.description.abstractControlled 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. � 2021. All Rights Reserved.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.14569/IJACSA.2021.0120756
dc.identifier.epage492
dc.identifier.issue7
dc.identifier.scopus2-s2.0-85112239696
dc.identifier.spage487
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85112239696&doi=10.14569%2fIJACSA.2021.0120756&partnerID=40&md5=72d29dc4077b953aa8d97536feda9d2b
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/26508
dc.identifier.volume12
dc.publisherScience and Information Organizationen_US
dc.relation.ispartofAll Open Access, Gold
dc.sourceScopus
dc.sourcetitleInternational Journal of Advanced Computer Science and Applications
dc.titlePower System Controlled Islanding using Modified Discrete Optimization Techniquesen_US
dc.typeArticleen_US
dspace.entity.typePublication
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