Article: Ordinal-based genetic algorithm with cascaded encoding for reactive power optimization of electricity market

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TitleOrdinal-based genetic algorithm with cascaded encoding for reactive power optimization of electricity market
AuthorsZhao, D2
He, G2
Zhong, J1
Ni, Y1
KeywordsGenetic algorithm
Mixed integer optimization
Opportunity cost
Ordinal optimization
Reactive power optimization
Issue Date2008
CitationDianli Zidonghua Shebei / Electric Power Automation Equipment, 2008, v. 28 n. 2, p. 1-5 [How to Cite?]
AbstractGenerators and capacitors are main reactive power sources for reactive load demands and system voltage stability. The cost of reactive power resource should be considered in dispatch optimization, based on which the reactive power market is built. A reactive power optimization model based on reactive power cost is proposed, which regards the on-off of capacitor as O-1 variable. The reactive power optimization becomes the non-linear programming of mixed integers, to which genetic algorithm with cascaded encoding is applied. The ordinal optimization theory is introduced to direct the individual selection and generation times of genetic algorithm. Its reliability is evaluated quantitatively. Simulation results of IEEE 30-bus system show its effectiveness. The operating conditions and relevant benefits are analyzed based on 5 cases.
ISSN1006-6047
2011 SCImago Journal Rankings: 0.037
ReferencesReferences in Scopus
DC Field
Value
dc.contributor.authorZhao, D
dc.contributor.authorHe, G
dc.contributor.authorZhong, J
dc.contributor.authorNi, Y
dc.date.accessioned2012-08-08T08:33:30Z
dc.date.available2012-08-08T08:33:30Z
dc.date.issued2008
dc.description.abstractGenerators and capacitors are main reactive power sources for reactive load demands and system voltage stability. The cost of reactive power resource should be considered in dispatch optimization, based on which the reactive power market is built. A reactive power optimization model based on reactive power cost is proposed, which regards the on-off of capacitor as O-1 variable. The reactive power optimization becomes the non-linear programming of mixed integers, to which genetic algorithm with cascaded encoding is applied. The ordinal optimization theory is introduced to direct the individual selection and generation times of genetic algorithm. Its reliability is evaluated quantitatively. Simulation results of IEEE 30-bus system show its effectiveness. The operating conditions and relevant benefits are analyzed based on 5 cases.
dc.description.natureLink_to_subscribed_fulltext
dc.identifier.citationDianli Zidonghua Shebei / Electric Power Automation Equipment, 2008, v. 28 n. 2, p. 1-5 [How to Cite?]
dc.identifier.epage5
dc.identifier.issn1006-6047
2011 SCImago Journal Rankings: 0.037
dc.identifier.issue2
dc.identifier.scopuseid_2-s2.0-40449141651
dc.identifier.spage1
dc.identifier.urihttp://hdl.handle.net/10722/155440
dc.identifier.volume28
dc.languageeng
dc.relation.ispartofDianli Zidonghua Shebei / Electric Power Automation Equipment
dc.relation.referencesReferences in Scopus
dc.subjectGenetic algorithm
dc.subjectMixed integer optimization
dc.subjectOpportunity cost
dc.subjectOrdinal optimization
dc.subjectReactive power optimization
dc.titleOrdinal-based genetic algorithm with cascaded encoding for reactive power optimization of electricity market
dc.typeArticle
Author Affiliations
  1. The University of Hong Kong
  2. Tsinghua University