Publication:
Chaotic local search based algorithm for optimal DGPV allocation

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dc.citedby1
dc.contributor.authorMustaffa S.A.S.en_US
dc.contributor.authorMusirin I.en_US
dc.contributor.authorOthman M.M.en_US
dc.contributor.authorZamani M.K.M.en_US
dc.contributor.authorKalam A.en_US
dc.contributor.authorid57189288788en_US
dc.contributor.authorid8620004100en_US
dc.contributor.authorid35944613200en_US
dc.contributor.authorid57193428895en_US
dc.contributor.authorid55543249600en_US
dc.date.accessioned2023-05-29T06:51:49Z
dc.date.available2023-05-29T06:51:49Z
dc.date.issued2018
dc.description.abstractThe advent of advanced technology has led to the increase of electricity demand in most countries in the world. This phenomenon has made the power system network operate close to the stability limit. Therefore, the power utilities are looking forward to the solution to increase the loadability of the existing infrastructure. Integration of renewable energy into the grid such as Distributed Generation Photovoltaic (DGPV) can be one of the possible solutions. In this paper, Chaotic Mutation Immune Evolutionary Programming (CMIEP) algorithm is used as the optimization method while the chaotic mapping was employed in the local search for optimal location and sizing of DGPV. The chaotic local search has the capability of finding the best solution by increasing the possibility of exploring the global minima. The proposed technique was applied to the IEEE 30 Bus RTS with variation of load. The simulation results are compared with Evolutionary Programming (EP) and it is found that CMIEP performed better in most of the cases. � 2018 Institute of Advanced Engineering and Science. All rights reserved.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.11591/ijeecs.v11.i1.pp113-120
dc.identifier.epage120
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85046810666
dc.identifier.spage113
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85046810666&doi=10.11591%2fijeecs.v11.i1.pp113-120&partnerID=40&md5=ebdbd8abe193b93bafdc28163b7437d2
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/23787
dc.identifier.volume11
dc.publisherInstitute of Advanced Engineering and Scienceen_US
dc.relation.ispartofAll Open Access, Green
dc.sourceScopus
dc.sourcetitleIndonesian Journal of Electrical Engineering and Computer Science
dc.titleChaotic local search based algorithm for optimal DGPV allocationen_US
dc.typeArticleen_US
dspace.entity.typePublication
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