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Conference Paper: A multi-agent based negotiation support system for cost allocation of cross-border transmission

TitleA multi-agent based negotiation support system for cost allocation of cross-border transmission
Authors
Keywordspower market
cross-border trade plan
decentralized optimization
multi-agent technology
Issue Date2001
PublisherIEEE, Computer Society. The Journal's web site is located at https://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000730
Citation
The 34th Annual Hawaii International Conference on System Sciences Proceedings, Maui, HI, 3-6 Jaunary 2001 How to Cite?
AbstractRegulation and protection have been the major issues to prevent the consumers from enjoying good quality of service (QoS) at reasonable prices, for example, electricity and long distance call service. Deregulation in such industries started in early 1970s and have achieved significant results in, for example, telecommunication industry. The deregulation in telecommunication was mainly focused on reducing the market power to add more competition to reduce the price and to improve QoS. Similarly, the power industry in several countries also underwent regulation. The power industry used to be protected and regulated. Consumers were forced to buy electricity from particular suppliers and suffered high prices and low QoS. After deregulation, the original boundary lines have been removed and consumers have more alternatives. How to support optimal planning of cross-border electricity trade has become an important issue since then. Decentralization, or participants have the rights to participate in decision making, is one of the directions of deregulation. In this paper a decentralized structure is suggested to solve the problem by using multi-agent technology to create autonomy for each participant. In such structure the centralization of information transmission or decision making is prevented. Each participant behaves rationally to search for best benefit or payoff through the information she or he owns or through information exchange with other participants. Although all the market participants make decisions to protect their own benefits, the optimal solution (total costs) of the whole system can be achieved finally. This structure is based on the method proposed in [5] and implementation, which a multiagent system called Multi-Agent System for Cross-Border Trade (MASCBT), was done by using Java programming language. A demonstration on a 5-area test system shows that the suggested new approach is effective and promising.
Persistent Identifierhttp://hdl.handle.net/10722/46265
ISSN

 

DC FieldValueLanguage
dc.contributor.authorWei, Pen_HK
dc.contributor.authorYan, Yen_HK
dc.contributor.authorNi, Yen_HK
dc.contributor.authorYen, Jen_HK
dc.contributor.authorWu, FFen_HK
dc.date.accessioned2007-10-30T06:46:06Z-
dc.date.available2007-10-30T06:46:06Z-
dc.date.issued2001en_HK
dc.identifier.citationThe 34th Annual Hawaii International Conference on System Sciences Proceedings, Maui, HI, 3-6 Jaunary 2001en_HK
dc.identifier.issn1060-3425en_HK
dc.identifier.urihttp://hdl.handle.net/10722/46265-
dc.description.abstractRegulation and protection have been the major issues to prevent the consumers from enjoying good quality of service (QoS) at reasonable prices, for example, electricity and long distance call service. Deregulation in such industries started in early 1970s and have achieved significant results in, for example, telecommunication industry. The deregulation in telecommunication was mainly focused on reducing the market power to add more competition to reduce the price and to improve QoS. Similarly, the power industry in several countries also underwent regulation. The power industry used to be protected and regulated. Consumers were forced to buy electricity from particular suppliers and suffered high prices and low QoS. After deregulation, the original boundary lines have been removed and consumers have more alternatives. How to support optimal planning of cross-border electricity trade has become an important issue since then. Decentralization, or participants have the rights to participate in decision making, is one of the directions of deregulation. In this paper a decentralized structure is suggested to solve the problem by using multi-agent technology to create autonomy for each participant. In such structure the centralization of information transmission or decision making is prevented. Each participant behaves rationally to search for best benefit or payoff through the information she or he owns or through information exchange with other participants. Although all the market participants make decisions to protect their own benefits, the optimal solution (total costs) of the whole system can be achieved finally. This structure is based on the method proposed in [5] and implementation, which a multiagent system called Multi-Agent System for Cross-Border Trade (MASCBT), was done by using Java programming language. A demonstration on a 5-area test system shows that the suggested new approach is effective and promising.en_HK
dc.format.extent154975 bytes-
dc.format.extent12538 bytes-
dc.format.extent11910 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE, Computer Society. The Journal's web site is located at https://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000730en_HK
dc.rights©2001 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.subjectpower marketen_HK
dc.subjectcross-border trade planen_HK
dc.subjectdecentralized optimizationen_HK
dc.subjectmulti-agent technologyen_HK
dc.titleA multi-agent based negotiation support system for cost allocation of cross-border transmissionen_HK
dc.typeConference_Paperen_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/HICSS.2001.926224-
dc.identifier.hkuros60932-
dc.identifier.issnl1060-3425-

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