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Reactive power planning for maximum load margin improvement using Fast Artificial Immune Support Vector Machine (FAISVM)

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dc.citedby9
dc.contributor.authorAziz N.F.A.en_US
dc.contributor.authorAbdul Rahman T.K.en_US
dc.contributor.authorZakaria Z.en_US
dc.contributor.authorid57221906825en_US
dc.contributor.authorid8922419700en_US
dc.contributor.authorid56276791800en_US
dc.date.accessioned2023-05-16T02:46:47Z
dc.date.available2023-05-16T02:46:47Z
dc.date.issued2014
dc.description.abstractLoad margin improvement is an important issue in power system planning and operation. This paper, first, presents a newly voltage stability index called Voltage Stability Condition Indicator (VSCI) to evaluate the voltage stability state of load buses in a system. It also proposes a fast optimization algorithm for reactive power planning problem (RPP) through Fast Artificial Immune Support Vector Machine (FAISVM). FAISVM is a hybrid algorithm that incorporates the application of Artificial Immune System (AIS) and Support Vector Machine (SVM) in solving RPP problems. The newly proposed algorithm can determine the optimal tap settings of tap changing transformers, the value of reactive power injection at the reactive power sources and the injection at the reactive power generator buses. The performances of the techniques proposed were verified using the IEEE 30-bus test system and compared with another newly developed hybrid Evolutionary Support Vector Machine (ESVM). The simulation results have shown that FASIVM outperformed ESVM in terms of maximum load margin improvement and computation time significantly and also reduce active power losses. © 2014 Praise Worthy Prize S.r.l. - All rights reserved.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.15866/ireaco.v7i5.2361
dc.identifier.epage447
dc.identifier.issue5
dc.identifier.scopus2-s2.0-84908345064
dc.identifier.spage436
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84908345064&doi=10.15866%2fireaco.v7i5.2361&partnerID=40&md5=7cc3512445ed729db1d88741108ddfa8
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22029
dc.identifier.volume7
dc.publisherPraise Worthy Prizeen_US
dc.sourceScopus
dc.sourcetitleInternational Review of Automatic Control
dc.titleReactive power planning for maximum load margin improvement using Fast Artificial Immune Support Vector Machine (FAISVM)en_US
dc.typeArticleen_US
dspace.entity.typePublication
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