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Integrated Optimization Algorithm in Solving Economic Dispatch Problems

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dc.citedby0
dc.contributor.authorIsmail N.L.en_US
dc.contributor.authorMusirin I.en_US
dc.contributor.authorDahlan N.Y.en_US
dc.contributor.authorMansor M.H.en_US
dc.contributor.authorSentilkumar A.V.en_US
dc.contributor.authorid57190935802en_US
dc.contributor.authorid8620004100en_US
dc.contributor.authorid24483200900en_US
dc.contributor.authorid56372667100en_US
dc.contributor.authorid58746048100en_US
dc.date.accessioned2024-10-14T03:20:25Z
dc.date.available2024-10-14T03:20:25Z
dc.date.issued2023
dc.description.abstractThe utilization of conservative fossil fuels in power generation has played a significant role in driving economic growth, but it has also resulted in adverse consequences towards environmental impacts. This study proposed Multi-objective Hybrid Evolutionary Programming-Barnacles Mating Optimization as a solution to address the Combined Economic Environmental Dispatch problem by weighted-sum method implementation. The bi-objective function are the minimizing of the total generation cost and total emission have been optimized simultaneously. The performance of the algorithm is evaluated on Reliability Test System IEEE 57-Bus consisting of 7 generating units that consider ramp rate limits generator constraint. The proposed algorithm has been compared with the existing techniques, Multi-objective Barnacles Mating Optimizer and Multi-objective Evolutionary Programming. The results reveal that MOHEBMO generates superior and consistent solutions. � 2023 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1109/IICAIET59451.2023.10291341
dc.identifier.epage134
dc.identifier.scopus2-s2.0-85178556739
dc.identifier.spage129
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85178556739&doi=10.1109%2fIICAIET59451.2023.10291341&partnerID=40&md5=75b967b0939046acede13e635cffd0b0
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/34529
dc.pagecount5
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitle5th IEEE International Conference on Artificial Intelligence in Engineering and Technology, IICAIET 2023
dc.subjectbarnacles mating optimizer
dc.subjecteconomic dispatch
dc.subjectevolutionary programming
dc.subjecthybrid algorithm
dc.subjectmulti-objective optimization
dc.subjectweighted-sum
dc.subjectComputer programming
dc.subjectElectric load dispatching
dc.subjectEnvironmental impact
dc.subjectFossil fuels
dc.subjectMultiobjective optimization
dc.subjectBarnacle mating optimizer
dc.subjectEconomic Dispatch
dc.subjectHybrid algorithms
dc.subjectIntegrated optimization
dc.subjectMatings
dc.subjectMulti objective
dc.subjectMulti-objectives optimization
dc.subjectOptimization algorithms
dc.subjectOptimizers
dc.subjectWeighted Sum
dc.subjectEvolutionary algorithms
dc.titleIntegrated Optimization Algorithm in Solving Economic Dispatch Problemsen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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