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Comparative Analysis in DG Installation Scheme for Resilience Enhancement

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dc.citedby0
dc.contributor.authorZakaria F.B.en_US
dc.contributor.authorMusirin I.B.en_US
dc.contributor.authorAminudin N.B.en_US
dc.contributor.authorJohari D.B.en_US
dc.contributor.authorShaaya S.A.en_US
dc.contributor.authorIbrahim N.F.B.en_US
dc.contributor.authorid55646310800en_US
dc.contributor.authorid8620004100en_US
dc.contributor.authorid24733969500en_US
dc.contributor.authorid24733632200en_US
dc.contributor.authorid16022846200en_US
dc.contributor.authorid55140240400en_US
dc.date.accessioned2025-03-03T07:48:04Z
dc.date.available2025-03-03T07:48:04Z
dc.date.issued2024
dc.description.abstractThis paper presents a comparative analysis of the Distributed Generation (DG) scheme for resilience enhancement. This study models categories of hurricanes as disruptive events, considering data on the fragility of transmission towers concerning wind speeds. The simulation involves generating sustained winds corresponding to different categories of hurricanes, following the Saffir-Simpson Hurricane scale. The transmission power system will encounter power outages when the transmission tower collapses. The installation of DG is one of the suitable efforts to alleviate this phenomenon where it is used as a compensating device to improve power grid resilience. In this study, the Evolutionary Programming (EP) and Artificial Immune System (AIS) optimization techniques are used to determine sizing and strategic locations for the placement of multiple DG units for loss control in the power system. The resilience status of the system is also observed. The proposed optimization techniques are validated on the IEEE 30-Bus Reliability Test System (RTS) under varying loads. Verification was conducted through a comparison of optimization outcomes obtained from EP and AIS techniques. The findings illustrate the effectiveness of these algorithms in significantly reducing total loss and improving the resilience of the tested system. ? 2024 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1109/ICPEA60617.2024.10498681
dc.identifier.epage316
dc.identifier.scopus2-s2.0-85191752247
dc.identifier.spage311
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85191752247&doi=10.1109%2fICPEA60617.2024.10498681&partnerID=40&md5=421e9c288565960e6a04b85ac82315c1
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/37156
dc.pagecount5
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitle2024 IEEE 4th International Conference in Power Engineering Applications: Powering the Future: Innovations for Sustainable Development, ICPEA 2024
dc.subjectComputer programming
dc.subjectDuctile fracture
dc.subjectElectric power transmission
dc.subjectHurricanes
dc.subjectOutages
dc.subjectRisk management
dc.subjectUncertainty analysis
dc.subjectArtificial Immune System
dc.subjectComparative analyzes
dc.subjectDisruptive event
dc.subjectGrid hardening
dc.subjectOptimization techniques
dc.subjectResilience
dc.subjectSimpson
dc.subjectTransmission power systems
dc.subjectTransmission tower
dc.subjectWind speed
dc.subjectDistributed power generation
dc.titleComparative Analysis in DG Installation Scheme for Resilience Enhancementen_US
dc.typeConference paperen_US
dspace.entity.typePublication
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