Please use this identifier to cite or link to this item: http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/2020
Full metadata record
DC FieldValueLanguage
dc.contributor.authorAsokan, K.
dc.contributor.authorAshokkumar, R.
dc.date.accessioned2021-03-17T08:02:22Z
dc.date.accessioned2022-07-07T05:15:07Z-
dc.date.available2021-03-17T08:02:22Z
dc.date.available2022-07-07T05:15:07Z-
dc.date.issued2014
dc.identifier.urihttp://repo.lib.jfn.ac.lk/ujrr/handle/123456789/2020-
dc.description.abstractIn the competitive electricity market, Power Generation companies (GENCOs) and large consumers are participating in bidding methodologies for their own benefits. In oligopoly market structure, GENCOs tries to maximize their profit and minimize the risk factor. So it is very essential and important for the GENCOs to formulate optimal bidding strategies before entering into the electricity market to achieve a maximum profit , since the market clearing price (MRP) are variable in nature.In this paper an innovative approach for defining optimal bidding strategy is presented as a stochastic optimization problem and solved by Firefly algorithm.(FA). The Firefly Algorithm is a Meta heuristic, nature inspired, optimization algorithm which is based on the social flashing behavior of fireflies and has been introduced for the bidding problem to obtain the global optimal solution. The proposed Firefly algorithm effectively maximizes the GENCOs profit. The proposed Firefly algorithm effectively maximizes the GENCOs profit. A numerical example with six suppliers is considered to illustrate the essential features of the proposed method and test results are tabulated. The simulation result shows that these approaches effectively maximize the Profit of GENCOs, converge much faster and more reliable when compared with existing methods.en_US
dc.language.isoenen_US
dc.publisheruniversity of Jaffnaen_US
dc.subjectElectricity marketen_US
dc.subjectOptimal biddingen_US
dc.subjectProfit maximizationen_US
dc.subjectFirefly algorithmen_US
dc.titleProfit maximization of power generation companies in competitive electricity marketen_US
dc.typeArticleen_US
Appears in Collections:ICCM 2014

Files in This Item:
File Description SizeFormat 
Regional Development-5.pdf79.5 kBAdobe PDFThumbnail
View/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.