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Article: Economic dispatch of power systems based on generalized ant colony optimization method

TitleEconomic dispatch of power systems based on generalized ant colony optimization method
Authors
KeywordsEconomic Dispatch
Fixed Point Theorem
Generalized Ant Colony Optimization (Gaco)
Issue Date2003
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, 2003, v. 23 n. 3, p. 59-64 How to Cite?
AbstractA new versatile optimization algorithm called generalized ant colony optimization (GACO) is presented. The economic dispatch (ED) problem of power systems be solved by the algorithm. The GACO is based on the concepts of ant colony optimization for combinatorial optimization problems. The positive feedback, distributed computation, and the constructive greedy heuristic are used in the algorithm to solve the discontinuous, nonconvex, nonlinear constrained optimization problems. The convergence property of the GACO is discussed based on the fixed-point theory on a complete metric space. Several sufficient conditions for convergence are presented. The algorithm is tested and validated in several cases. In these cases, the GACO can provide accurate dispatch solutions in reasonable time. The results show that the GACO for the ED problem is versatile, robust and efficient.
Persistent Identifierhttp://hdl.handle.net/10722/155197
ISSN
2015 SCImago Journal Rankings: 0.881
References

 

DC FieldValueLanguage
dc.contributor.authorHou, YHen_US
dc.contributor.authorXiong, XYen_US
dc.contributor.authorWu, YWen_US
dc.contributor.authorLu, LJen_US
dc.date.accessioned2012-08-08T08:32:18Z-
dc.date.available2012-08-08T08:32:18Z-
dc.date.issued2003en_US
dc.identifier.citationZhongguo Dianji Gongcheng Xuebao/Proceedings Of The Chinese Society Of Electrical Engineering, 2003, v. 23 n. 3, p. 59-64en_US
dc.identifier.issn0258-8013en_US
dc.identifier.urihttp://hdl.handle.net/10722/155197-
dc.description.abstractA new versatile optimization algorithm called generalized ant colony optimization (GACO) is presented. The economic dispatch (ED) problem of power systems be solved by the algorithm. The GACO is based on the concepts of ant colony optimization for combinatorial optimization problems. The positive feedback, distributed computation, and the constructive greedy heuristic are used in the algorithm to solve the discontinuous, nonconvex, nonlinear constrained optimization problems. The convergence property of the GACO is discussed based on the fixed-point theory on a complete metric space. Several sufficient conditions for convergence are presented. The algorithm is tested and validated in several cases. In these cases, the GACO can provide accurate dispatch solutions in reasonable time. The results show that the GACO for the ED problem is versatile, robust 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.subjectFixed Point Theoremen_US
dc.subjectGeneralized Ant Colony Optimization (Gaco)en_US
dc.titleEconomic dispatch of power systems based on generalized ant colony optimization methoden_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-s2.0-0038107797en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0038107797&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume23en_US
dc.identifier.issue3en_US
dc.identifier.spage59en_US
dc.identifier.epage64en_US
dc.publisher.placeChinaen_US
dc.identifier.scopusauthoridHou, YH=7402198555en_US
dc.identifier.scopusauthoridXiong, XY=7201634426en_US
dc.identifier.scopusauthoridWu, YW=7406898040en_US
dc.identifier.scopusauthoridLu, LJ=7403962870en_US

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