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Intelligent Optimization Systems for MaintenanceScheduling of Power Plant Generators

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dc.citedby1
dc.contributor.authorIsmail F.B.en_US
dc.contributor.authorRandhawa G.S.en_US
dc.contributor.authorAl-Bazi A.en_US
dc.contributor.authorAlkahtani A.A.en_US
dc.contributor.authorid58027086700en_US
dc.contributor.authorid58080315400en_US
dc.contributor.authorid35098298500en_US
dc.contributor.authorid55646765500en_US
dc.date.accessioned2024-10-14T03:21:46Z
dc.date.available2024-10-14T03:21:46Z
dc.date.issued2023
dc.description.abstractThis paper presents a Genetic Algorithm (GA) and Ant-Colony (AC) optimization model for power plant generators� maintenance scheduling. Maintenance scheduling of power plant generators is essential for ensuring the reliability and economic operation of a power system. Proper maintenance scheduling prolongs the shelf life of the generators and prevents unexpected failures. To reduce the cost and duration of generator maintenance, these models are built with various constants, fitness functions, and objective functions. The Analytical Hierarchy Process (AHP), a decision-making tool, is implemented to aid the researcher in prioritizing and re-ranking the maintenance activities from the most important to the least. The intelligent optimization models are developed using MATLAB and the developed intelligent algorithms are tested on a case study in a coal power plant located at minjung, Perak, Malaysia. The power plant is owned and operated by Tenaga Nasional Berhad (TNB), the electric utility company in peninsular Malaysia. The results show that GA outperforms ACO since it reduces maintenance costs by 39.78% and maintenance duration by 60%. The study demonstrates that the proposed optimization method is effective in reducing maintenance time and cost while also optimizing power plant operation. � 2023 NSP Natural Sciences Publishing Cor.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.18576/isl/120322
dc.identifier.epage1332
dc.identifier.issue3
dc.identifier.scopus2-s2.0-85146923869
dc.identifier.spage1319
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85146923869&doi=10.18576%2fisl%2f120322&partnerID=40&md5=f3dc4d6e7fcb415e6e8f1f3976fbda4c
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/34690
dc.identifier.volume12
dc.pagecount13
dc.publisherNatural Sciences Publishingen_US
dc.sourceScopus
dc.sourcetitleInformation Sciences Letters
dc.subjectAnt-Colony Optimization
dc.subjectGenerator
dc.subjectGenetic Algorithm
dc.subjectMaintenance Scheduling
dc.subjectOptimization modeling
dc.titleIntelligent Optimization Systems for MaintenanceScheduling of Power Plant Generatorsen_US
dc.typeArticleen_US
dspace.entity.typePublication
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