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Article: Optimal bidding strategies for generation companies with network congestion taken into account

TitleOptimal bidding strategies for generation companies with network congestion taken into account
Authors
KeywordsCongestion management
Electricity bidding
Electricity markets
Genetic algorithm
Market power
Monte Carlo simulation
Issue Date2003
Citation
Dianli Xitong Zidonghua/Automation Of Electric Power Systems, 2003, v. 27 n. 12, p. 12-17 How to Cite?
AbstractIn the electricity market environment, generation dispatch is bid-based rather than cost-based, and hence it has become a major concern for generation companies of how to build optimal bidding strategies. The deficiency of transmission capacity could lead to congestion, and as a result, the whole electricity market can then be actually divided into two or more submarkets. A direct consequence of transmission congestion is the change of competitive positions of generation companies concerned in the electricity market, and the optimal bidding strategies of them should accordingly be changed. In this work, the problem of developing optimal bidding strategies for generation companies in the electricity market environment with transmission network congestion taken into account is investigated, and a stochastic optimization model is first formulated under the presumption that the bidding behaviors of rival generation companies can be modeled as normal probability distributions. An approach is next presented for solving the optimization problem using the well-known Monte Carlo simulation method and the genetic algorithm. Finally, the modified IEEE 14-bus system is employed to illustrate the essential features of the proposed model and method.
Persistent Identifierhttp://hdl.handle.net/10722/74107
ISSN
2015 SCImago Journal Rankings: 0.772
References

 

DC FieldValueLanguage
dc.contributor.authorMa, Len_HK
dc.contributor.authorWen, Fen_HK
dc.contributor.authorNi, Yen_HK
dc.contributor.authorWu, FFen_HK
dc.date.accessioned2010-09-06T06:57:52Z-
dc.date.available2010-09-06T06:57:52Z-
dc.date.issued2003en_HK
dc.identifier.citationDianli Xitong Zidonghua/Automation Of Electric Power Systems, 2003, v. 27 n. 12, p. 12-17en_HK
dc.identifier.issn1000-1026en_HK
dc.identifier.urihttp://hdl.handle.net/10722/74107-
dc.description.abstractIn the electricity market environment, generation dispatch is bid-based rather than cost-based, and hence it has become a major concern for generation companies of how to build optimal bidding strategies. The deficiency of transmission capacity could lead to congestion, and as a result, the whole electricity market can then be actually divided into two or more submarkets. A direct consequence of transmission congestion is the change of competitive positions of generation companies concerned in the electricity market, and the optimal bidding strategies of them should accordingly be changed. In this work, the problem of developing optimal bidding strategies for generation companies in the electricity market environment with transmission network congestion taken into account is investigated, and a stochastic optimization model is first formulated under the presumption that the bidding behaviors of rival generation companies can be modeled as normal probability distributions. An approach is next presented for solving the optimization problem using the well-known Monte Carlo simulation method and the genetic algorithm. Finally, the modified IEEE 14-bus system is employed to illustrate the essential features of the proposed model and method.en_HK
dc.languageengen_HK
dc.relation.ispartofDianli Xitong Zidonghua/Automation of Electric Power Systemsen_HK
dc.subjectCongestion managementen_HK
dc.subjectElectricity biddingen_HK
dc.subjectElectricity marketsen_HK
dc.subjectGenetic algorithmen_HK
dc.subjectMarket poweren_HK
dc.subjectMonte Carlo simulationen_HK
dc.titleOptimal bidding strategies for generation companies with network congestion taken into accounten_HK
dc.typeArticleen_HK
dc.identifier.emailNi, Y: yxni@eee.hku.hken_HK
dc.identifier.emailWu, FF: ffwu@eee.hku.hken_HK
dc.identifier.authorityNi, Y=rp00161en_HK
dc.identifier.authorityWu, FF=rp00194en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-0141596940en_HK
dc.identifier.hkuros83275en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0141596940&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume27en_HK
dc.identifier.issue12en_HK
dc.identifier.spage12en_HK
dc.identifier.epage17en_HK
dc.publisher.placeChinaen_HK
dc.identifier.scopusauthoridMa, L=36072648200en_HK
dc.identifier.scopusauthoridWen, F=7102815249en_HK
dc.identifier.scopusauthoridNi, Y=7402910021en_HK
dc.identifier.scopusauthoridWu, FF=7403465107en_HK

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