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Chaotic mutation immune evolutionary programming for voltage security with the presence of DGPV

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dc.citedby7
dc.contributor.authorMustaffa S.A.S.en_US
dc.contributor.authorMusirin I.en_US
dc.contributor.authorOthman M.M.en_US
dc.contributor.authorMansor M.H.en_US
dc.contributor.authorid57189288788en_US
dc.contributor.authorid8620004100en_US
dc.contributor.authorid35944613200en_US
dc.contributor.authorid56372667100en_US
dc.date.accessioned2023-05-29T06:38:27Z
dc.date.available2023-05-29T06:38:27Z
dc.date.issued2017
dc.description.abstractDue to environmental concern and certain constraint on building a new power plant, renewable energy particularly distributed generation photovoltaic (DGPV) has becomes one of the promising sources to cater the increasing energy demand of the power system. Furthermore, with appropriate location and sizing, the integration of DGPV to the grid will enhance the voltage stability and reduce the system losses. Hence, this paper proposed a new algorithm for DGPV optimal location and sizing of a transmission system based on minimization of Fast Voltage Stability Index (FVSI) with considering the system constraints. Chaotic Mutation Immune Evolutionary Programming (CMIEP) is developed by integrating the piecewise linear chaotic map (PWLCM) in the mutation process in order to increase the convergence rate of the algorithm. The simulation was applied on the IEEE 30 bus system with a variation of loads on Bus 30. The simulation results are also compared with Evolutionary Programming (EP) and Chaotic Evolutionary Programming (CEP) and it is found that CMIEP performed better in most of the cases. � 2017 Institute of Advanced Engineering and Science. All rights reserved.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.11591/ijeecs.v6.i3.pp721-729
dc.identifier.epage729
dc.identifier.issue3
dc.identifier.scopus2-s2.0-85020822585
dc.identifier.spage721
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85020822585&doi=10.11591%2fijeecs.v6.i3.pp721-729&partnerID=40&md5=398a3f68ec9dea30f10e6e05f002d400
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/23209
dc.identifier.volume6
dc.publisherInstitute of Advanced Engineering and Scienceen_US
dc.sourceScopus
dc.sourcetitleIndonesian Journal of Electrical Engineering and Computer Science
dc.titleChaotic mutation immune evolutionary programming for voltage security with the presence of DGPVen_US
dc.typeArticleen_US
dspace.entity.typePublication
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