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Article: Application of generalized ant colony optimizaiton algorithm integrated with particle swarm optimization algorithm in economic dispatch of power system

TitleApplication of generalized ant colony optimizaiton algorithm integrated with particle swarm optimization algorithm in economic dispatch of power system
Authors
KeywordsEconomic Dispatch
Generalized Ant Colony Optimization Algorithm
Particle Swarm Optimization Algorithm
Power System
Issue Date2004
PublisherPower System Technology Press. The Journal's web site is located at http://www.dwjs.com.cn/
Citation
Power System Technology, 2004, v. 28 n. 21, p. 34-38 How to Cite?
AbstractAn optimized algorithm in which the general ant colony optimization (GACO) is integrated with particle swarm optimization (PSO) is proposed and is applied to economic dispatch of a complicated, non-concex and nonlinear power system. This integrated algorithm possesses large scale search capability of generalized ant colony algorithm and better local search capability of particle swarm algorithm at the same time. Under the condition of ensuring global convergence, high quality optimization solution can be searched by the proposed algorithm. The simulation results of several calculation examples show that the proposed algorithm is effective and feasible.
Persistent Identifierhttp://hdl.handle.net/10722/155775
ISSN
2015 SCImago Journal Rankings: 0.684
References

 

DC FieldValueLanguage
dc.contributor.authorHou, YHen_US
dc.contributor.authorLu, LJen_US
dc.contributor.authorXiong, XYen_US
dc.contributor.authorWu, YWen_US
dc.date.accessioned2012-08-08T08:35:17Z-
dc.date.available2012-08-08T08:35:17Z-
dc.date.issued2004en_US
dc.identifier.citationPower System Technology, 2004, v. 28 n. 21, p. 34-38en_US
dc.identifier.issn1000-3673en_US
dc.identifier.urihttp://hdl.handle.net/10722/155775-
dc.description.abstractAn optimized algorithm in which the general ant colony optimization (GACO) is integrated with particle swarm optimization (PSO) is proposed and is applied to economic dispatch of a complicated, non-concex and nonlinear power system. This integrated algorithm possesses large scale search capability of generalized ant colony algorithm and better local search capability of particle swarm algorithm at the same time. Under the condition of ensuring global convergence, high quality optimization solution can be searched by the proposed algorithm. The simulation results of several calculation examples show that the proposed algorithm is effective and feasible.en_US
dc.languageengen_US
dc.publisherPower System Technology Press. The Journal's web site is located at http://www.dwjs.com.cn/en_US
dc.relation.ispartofPower System Technologyen_US
dc.subjectEconomic Dispatchen_US
dc.subjectGeneralized Ant Colony Optimization Algorithmen_US
dc.subjectParticle Swarm Optimization Algorithmen_US
dc.subjectPower Systemen_US
dc.titleApplication of generalized ant colony optimizaiton algorithm integrated with particle swarm optimization algorithm in economic dispatch of power systemen_US
dc.typeArticleen_US
dc.identifier.emailHou, YH:yhhou@eee.hku.hken_US
dc.identifier.authorityHou, YH=rp00069en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-9744246861en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-9744246861&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume28en_US
dc.identifier.issue21en_US
dc.identifier.spage34en_US
dc.identifier.epage38en_US
dc.publisher.placeChinaen_US
dc.identifier.scopusauthoridHou, YH=7402198555en_US
dc.identifier.scopusauthoridLu, LJ=7403962870en_US
dc.identifier.scopusauthoridXiong, XY=7201634426en_US
dc.identifier.scopusauthoridWu, YW=7406898040en_US

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