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Pareto optimal approach in Multi-Objective Chaotic Mutation Immune Evolutionary Programming (MOCMIEP) for optimal Distributed Generation Photovoltaic (DGPV) integration in power system

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dc.citedby20
dc.contributor.authorSyed Mustaffa S.A.en_US
dc.contributor.authorMusirin I.en_US
dc.contributor.authorMohamad Zamani M.K.en_US
dc.contributor.authorOthman M.M.en_US
dc.contributor.authorid57189288788en_US
dc.contributor.authorid8620004100en_US
dc.contributor.authorid57193428895en_US
dc.contributor.authorid35944613200en_US
dc.date.accessioned2023-05-29T07:22:33Z
dc.date.available2023-05-29T07:22:33Z
dc.date.issued2019
dc.descriptionComputer programming; Distributed power generation; Evolutionary algorithms; Integration; Pareto principle; Renewable energy resources; Voltage control; Fast voltage stability indices; Multi objective; Optimal; Pareto-optimal; Photovoltaic; Distributed computer systemsen_US
dc.description.abstractThe latest advancement in the technology, including the integration of the renewable energy resources, has become a recent trend in the power system infrastructure. Although, this can bring many benefits, excessive integration without proper planning may lead to unwanted circumstances such as voltage instability and higher power losses. This paper proposes a new Pareto optimality based technique namely: Multi-objective Chaotic Mutation Immune Evolutionary Programming. The technique was developed to determines the optimal location and sizing of Distributed Generated Photovoltaic (DGPV) and minimizing the multiple objective functions, namely, the active power losses and Fast Voltage Stability Index (FVSI), simultaneously. The method was tested on the IEEE test system. The results revealed that the proposed technique had the ability to acquire a set of Pareto solutions. Furthermore, this paper also confirmed that Multi-objective Chaotic Mutation Immune Evolutionary Programming (MOCMIEP) outperformed the Multi-objective Evolutionary Programming and Multi-objective Artificial Immune System in most cases. � 2019 THE AUTHORSen_US
dc.description.natureFinalen_US
dc.identifier.doi10.1016/j.asej.2019.04.006
dc.identifier.epage754
dc.identifier.issue4
dc.identifier.scopus2-s2.0-85066078323
dc.identifier.spage745
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85066078323&doi=10.1016%2fj.asej.2019.04.006&partnerID=40&md5=0d31c1fa7eea8b9ac2b913213bdc911f
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24278
dc.identifier.volume10
dc.publisherAin Shams Universityen_US
dc.relation.ispartofAll Open Access, Gold
dc.sourceScopus
dc.sourcetitleAin Shams Engineering Journal
dc.titlePareto optimal approach in Multi-Objective Chaotic Mutation Immune Evolutionary Programming (MOCMIEP) for optimal Distributed Generation Photovoltaic (DGPV) integration in power systemen_US
dc.typeArticleen_US
dspace.entity.typePublication
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