Publication:
Optimal economic load dispatch using multiobjective cuckoo search algorithm

Simple item page
dc.citedby11
dc.contributor.authorYasin Z.M.en_US
dc.contributor.authorAziz N.F.A.en_US
dc.contributor.authorSalim N.A.en_US
dc.contributor.authorWahab N.A.en_US
dc.contributor.authorRahmat N.A.en_US
dc.contributor.authorid57211410254en_US
dc.contributor.authorid57221906825en_US
dc.contributor.authorid36806685300en_US
dc.contributor.authorid35790572400en_US
dc.contributor.authorid55647163881en_US
dc.date.accessioned2023-05-29T06:51:00Z
dc.date.available2023-05-29T06:51:00Z
dc.date.issued2018
dc.description.abstractIn this paper, Multiobjective Cuckoo Search Algorithm (MOCSA) is developed to solve Economic Load Dispatch (ELD) problem. The main goal of the ELD is to meet the load demand at minimum operating cost by determining the output of the committed generating unit while satisfying system equality and inequality constraints. The problem formulation is based on a multiobjective model in which the multiobjective are defined as fuel cost minimization and carbon emission minimization. MOCSA is based on the inspiration from the brooding parasitism of cuckoo species in nature. Three cases are considered to test the effectiveness of the proposed technique which are fuel cost minimization, carbon emission minimization and multiobjective function with fixed weighted sum. The effectiveness of the MOCSA�s performances are illustrated through comparative study with other techniques such as Multiobjective Genetic Algorithm (MOGA) and Multiobjective Particle Swarm Optimization (MOPSO) in terms of fitness functions. The proposed study was conducted on three generating unit system at various loading condition. The result proved that MOCSA provide better solution in minimizing fuel cost and carbon emission usage as compared to other techniques. � 2018 Institute of Advanced Engineering and Science All rights reserved.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.11591/ijeecs.v12.i1.pp168-174
dc.identifier.epage174
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85051242715
dc.identifier.spage168
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85051242715&doi=10.11591%2fijeecs.v12.i1.pp168-174&partnerID=40&md5=9095ce60f5e3e2ad249c6fb9ee27d777
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/23681
dc.identifier.volume12
dc.publisherInstitute of Advanced Engineering and Scienceen_US
dc.relation.ispartofAll Open Access, Green
dc.sourceScopus
dc.sourcetitleIndonesian Journal of Electrical Engineering and Computer Science
dc.titleOptimal economic load dispatch using multiobjective cuckoo search algorithmen_US
dc.typeArticleen_US
dspace.entity.typePublication
Files
Collections
SCOPUS