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Adaptive particle swarm optimisation for solving non-convex economic dispatch problems

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dc.citedby2
dc.contributor.authorJamain N.en_US
dc.contributor.authorMusirin I.en_US
dc.contributor.authorMansor M.H.en_US
dc.contributor.authorOthman M.M.en_US
dc.contributor.authorSalleh S.A.M.en_US
dc.contributor.authorid57202735757en_US
dc.contributor.authorid8620004100en_US
dc.contributor.authorid56372667100en_US
dc.contributor.authorid35944613200en_US
dc.contributor.authorid57201743907en_US
dc.date.accessioned2023-05-29T06:39:08Z
dc.date.available2023-05-29T06:39:08Z
dc.date.issued2017
dc.description.abstractThis paper presents adaptive particle swarm optimization for solving non-convex economic dispatch problems. In this study, a new technique was developed known as adaptive particle swarm optimization (APSO), to alleviate the problems experienced in the traditional particle swarm optimisation (PSO). The traditional PSO was reported that this technique always stuck at local minima. In APSO, economic dispatch problem are considered with valve point effects. The search efficiency was improved when a new parameter was inserted into the velocity term. This has achieved local minima. In order to show the effectiveness of the proposed technique, this study examined two case studies, with and without contingency. � 2017 Universiti Putra Malaysia Press.en_US
dc.description.natureFinalen_US
dc.identifier.epage286
dc.identifier.issueS3
dc.identifier.scopus2-s2.0-85049130525
dc.identifier.spage275
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85049130525&partnerID=40&md5=d2e945037c877bea157983a950a6ff8b
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/23287
dc.identifier.volume25
dc.publisherUniversiti Putra Malaysia Pressen_US
dc.sourceScopus
dc.sourcetitlePertanika Journal of Science and Technology
dc.titleAdaptive particle swarm optimisation for solving non-convex economic dispatch problemsen_US
dc.typeArticleen_US
dspace.entity.typePublication
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