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Article: Enhanced particle swarm optimization algorithm and its application on economic dispatch of power systems

TitleEnhanced particle swarm optimization algorithm and its application on economic dispatch of power systems
Authors
KeywordsEconomic Dispatch
Electric Power Engineering
Enhanced Particle Swarm Optimization Algorithm
Power System
Stochastic Analysis
Issue Date2004
PublisherZhongguo Dianji Gongcheng Xuehui. The Journal's web site is located at http://www.dwjs.com.cn
Citation
Zhongguo Dianji Gongcheng Xuebao/Proceedings Of The Chinese Society Of Electrical Engineering, 2004, v. 24 n. 7, p. 95-100 How to Cite?
AbstractA versatile optimization called enhanced particle swarm optimization algorithm (EPSO) is presented. The algorithm can be used to solve the discontinuous, nonconvex, nonlinear constrained optimization problems. The economic dispatch (ED) problem of power system is solved by this algorithm. The convergence property of the EPSO is discussed based on the stochastic analysis theory, and the results prove that the enhanced particle swarm optimization algorithm has global convergence property and the convergence property is independent of the initialization distribution. Moreover, a sufficient condition for convergence is presented. The algorithm is tested and validated in two cases. The results show that the EPSO for ED problem is versatile and efficient.
Persistent Identifierhttp://hdl.handle.net/10722/155465
ISSN
2015 SCImago Journal Rankings: 0.881
References

 

DC FieldValueLanguage
dc.contributor.authorHou, YHen_US
dc.contributor.authorLu, LJen_US
dc.contributor.authorXiong, XYen_US
dc.contributor.authorCheng, SJen_US
dc.contributor.authorWu, YWen_US
dc.date.accessioned2012-08-08T08:33:38Z-
dc.date.available2012-08-08T08:33:38Z-
dc.date.issued2004en_US
dc.identifier.citationZhongguo Dianji Gongcheng Xuebao/Proceedings Of The Chinese Society Of Electrical Engineering, 2004, v. 24 n. 7, p. 95-100en_US
dc.identifier.issn0258-8013en_US
dc.identifier.urihttp://hdl.handle.net/10722/155465-
dc.description.abstractA versatile optimization called enhanced particle swarm optimization algorithm (EPSO) is presented. The algorithm can be used to solve the discontinuous, nonconvex, nonlinear constrained optimization problems. The economic dispatch (ED) problem of power system is solved by this algorithm. The convergence property of the EPSO is discussed based on the stochastic analysis theory, and the results prove that the enhanced particle swarm optimization algorithm has global convergence property and the convergence property is independent of the initialization distribution. Moreover, a sufficient condition for convergence is presented. The algorithm is tested and validated in two cases. The results show that the EPSO for ED problem is versatile and efficient.en_US
dc.languageengen_US
dc.publisherZhongguo Dianji Gongcheng Xuehui. The Journal's web site is located at http://www.dwjs.com.cnen_US
dc.relation.ispartofZhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineeringen_US
dc.subjectEconomic Dispatchen_US
dc.subjectElectric Power Engineeringen_US
dc.subjectEnhanced Particle Swarm Optimization Algorithmen_US
dc.subjectPower Systemen_US
dc.subjectStochastic Analysisen_US
dc.titleEnhanced particle swarm optimization algorithm and its application on economic dispatch of power systemsen_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-s2.0-4344670670en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-4344670670&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume24en_US
dc.identifier.issue7en_US
dc.identifier.spage95en_US
dc.identifier.epage100en_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.scopusauthoridCheng, SJ=7404685116en_US
dc.identifier.scopusauthoridWu, YW=7406898040en_US

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