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Multi-objective evolutionary programming for solving economic dispatch problem

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dc.citedby2
dc.contributor.authorAdnan N.A.en_US
dc.contributor.authorMansor M.H.en_US
dc.contributor.authorRoslan N.en_US
dc.contributor.authorMusirin I.en_US
dc.contributor.authorKhader P.S.A.en_US
dc.contributor.authorKamil K.en_US
dc.contributor.authorJelani S.en_US
dc.contributor.authorZuhdi A.W.M.en_US
dc.contributor.authorid57212722015en_US
dc.contributor.authorid56372667100en_US
dc.contributor.authorid57205233093en_US
dc.contributor.authorid8620004100en_US
dc.contributor.authorid36926269300en_US
dc.contributor.authorid57195622807en_US
dc.contributor.authorid57193388570en_US
dc.contributor.authorid56589966300en_US
dc.date.accessioned2023-05-29T07:28:10Z
dc.date.available2023-05-29T07:28:10Z
dc.date.issued2019
dc.description.abstractEconomic dispatch (ED) is an optimisation strategy to ensure power systems operate in an economic manner. This paper proposes a multi-objective optimisation method to minimise the total generation cost and total system loss simultaneously and find the best adjustment for this economic dispatch problem. This study focused on solving the multi-objective economic dispatch problem using a Heuristic Optimisation (HO) method, namely Multi-Objective Evolutionary Programming (MOEP). The Weighted Sum Method (WSM) is integrated with EP to find a trade-off solution between two objectives: total generation cost minimisation and total system loss minimisation. The practicable proposed method was tested on the IEEE 30-Bus Reliability Test System (RTS) for three different scenarios. MATLAB programming language was used to run the designated algorithm of MOEP. The performance of MOEP to solve the multi-objective ED problem was then compared with another method; the Multi-Objective Artificial Immune System (MOAIS). The experimental results show that MOEP dominates in all cases that have been tested, proving that MOEP is superior than MOAIS in providing high-quality solution to economic dispatch problem with multiple objectives in terms of cheap total generation cost and low total system loss. � 2019, World Academy of Research in Science and Engineering. All rights reserved.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo44
dc.identifier.doi10.30534/ijatcse/2019/4481.62019
dc.identifier.epage302
dc.identifier.issue1.6 Special Issue
dc.identifier.scopus2-s2.0-85078254747
dc.identifier.spage296
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85078254747&doi=10.30534%2fijatcse%2f2019%2f4481.62019&partnerID=40&md5=bc32e959b370163dd44275f7ea685d0e
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24873
dc.identifier.volume8
dc.publisherWorld Academy of Research in Science and Engineeringen_US
dc.relation.ispartofAll Open Access, Bronze
dc.sourceScopus
dc.sourcetitleInternational Journal of Advanced Trends in Computer Science and Engineering
dc.titleMulti-objective evolutionary programming for solving economic dispatch problemen_US
dc.typeArticleen_US
dspace.entity.typePublication
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