File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Research on identification of operation state in electricity market

TitleResearch on identification of operation state in electricity market
Authors
KeywordsDecision Tree
Electricity Market
Operation State
State Identification
Issue Date2007
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, 2007, v. 27 n. 22, p. 63-68 How to Cite?
AbstractIdentification of power market operation state is of importance to hedging market risk. Based on Dr. Dyliacco's research, the paper presents a new series of key index to identify the operation state of power market by a brief survey of the determining method of power market state. The decision tree method is applied in order to deal with the large quantity and complexity of index. Furthermore, the algorithm based on the information entropy is used to learn from a set of typical examples and thus to form the decision tree to identify the unknown state. The numeric analysis is carried out based on the data of California electricity market of 2000. The results show that the proposed methods can provide with the reasonable results in accord with reality and prove the effectiveness of the methods in market state identification and pre-warning.
Persistent Identifierhttp://hdl.handle.net/10722/155388
ISSN
2015 SCImago Journal Rankings: 0.881
References

 

DC FieldValueLanguage
dc.contributor.authorJian, HYen_US
dc.contributor.authorKang, CQen_US
dc.contributor.authorZhong, Jen_US
dc.contributor.authorXia, Qen_US
dc.date.accessioned2012-08-08T08:33:15Z-
dc.date.available2012-08-08T08:33:15Z-
dc.date.issued2007en_US
dc.identifier.citationZhongguo Dianji Gongcheng Xuebao/Proceedings Of The Chinese Society Of Electrical Engineering, 2007, v. 27 n. 22, p. 63-68en_US
dc.identifier.issn0258-8013en_US
dc.identifier.urihttp://hdl.handle.net/10722/155388-
dc.description.abstractIdentification of power market operation state is of importance to hedging market risk. Based on Dr. Dyliacco's research, the paper presents a new series of key index to identify the operation state of power market by a brief survey of the determining method of power market state. The decision tree method is applied in order to deal with the large quantity and complexity of index. Furthermore, the algorithm based on the information entropy is used to learn from a set of typical examples and thus to form the decision tree to identify the unknown state. The numeric analysis is carried out based on the data of California electricity market of 2000. The results show that the proposed methods can provide with the reasonable results in accord with reality and prove the effectiveness of the methods in market state identification and pre-warning.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.subjectDecision Treeen_US
dc.subjectElectricity Marketen_US
dc.subjectOperation Stateen_US
dc.subjectState Identificationen_US
dc.titleResearch on identification of operation state in electricity marketen_US
dc.typeArticleen_US
dc.identifier.emailZhong, J:jinzhong@hkucc.hku.hken_US
dc.identifier.authorityZhong, J=rp00212en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-34548317261en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-34548317261&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume27en_US
dc.identifier.issue22en_US
dc.identifier.spage63en_US
dc.identifier.epage68en_US
dc.publisher.placeChinaen_US
dc.identifier.scopusauthoridJian, HY=7005705170en_US
dc.identifier.scopusauthoridKang, CQ=7402312938en_US
dc.identifier.scopusauthoridZhong, J=13905948700en_US
dc.identifier.scopusauthoridXia, Q=7202871531en_US

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats