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Multi-Objective Environmental/Economic Dispatch Solution Using ABC_PSO Hybrid Algorithm

dc.contributor.authorManteaw, Emmanuel Dartey
dc.contributor.authorOdero, Nicodemus Abungu
dc.date.accessioned2018-12-03T10:54:50Z
dc.date.available2018-12-03T10:54:50Z
dc.date.issued2012
dc.description.abstractThe problem of power system optimization has become a deciding factor in current power system engineering practice with emphasis on cost and emission reduction. The economic and emission dispatch problem has been addressed in this paper using two efficient optimization methods, Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO). A hybrid produced from these two algorithms is used on the 30-bus 6 generator IEEE test system. The results are compared with ABC, Fuzzy Controlled Genetic Algorithm (FCGA) and Non Sorting Genetic Algorithm (NSGA-II) and found to be effective on the combined economic and emission dispatch problem.en_US
dc.identifier.issn2250-3153
dc.identifier.urihttp://ir.mksu.ac.ke/bitstream/handle/123456780/2079/c797eb3c762fd94b7ced4a7f92e30be14d8c.pdf?sequence=1&isAllowed=y
dc.language.isoen_USen_US
dc.publisherInternational Journal of Scientific and Research Publicationsen_US
dc.subjectEconomic and Emission Dispatchen_US
dc.subjectArtificial Bee Colonyen_US
dc.subjectParticle Swarm Optimizationen_US
dc.subject6-Generator test systemen_US
dc.titleMulti-Objective Environmental/Economic Dispatch Solution Using ABC_PSO Hybrid Algorithmen_US
dc.typeArticleen_US

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