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dc.contributor.authorNabavi, S.
dc.contributor.authorKazemi, A.
dc.contributor.authorMasoum, Mohammad Sherkat
dc.date.accessioned2017-01-30T12:11:49Z
dc.date.available2017-01-30T12:11:49Z
dc.date.created2015-03-03T20:17:22Z
dc.date.issued2011
dc.identifier.citationNabavi, S. and Kazemi, A. and Masoum, M. 2011. Congestion Management using Genetic Algorithm in Deregulated Power Environments. International Journal of Computer Applications. 18 (2): pp. 19-23.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/19082
dc.description.abstract

Congestion cost allocation is an important issue in congestion management. This paper presents a genetic algorithm (GA) to determine the optimal generation levels in a deregulated market. The main issue is congestion in lines, which limits transfer capability of a system with available generation capacity. Nodal pricing method is used to determine locational marginal price (LMP) of each generator at each bus. Simulation results based on the proposed GA and the Power World Simulator software is presented and compared for the IEEE 30-bus test system.

dc.publisherFoundation of Computer Science
dc.relation.urihttp://www.ijcaonline.org/volume18/number2/pxc3872894.pdf
dc.titleCongestion Management using Genetic Algorithm in Deregulated Power Environments
dc.typeJournal Article
dcterms.source.volume18
dcterms.source.number2
dcterms.source.startPage19
dcterms.source.endPage23
dcterms.source.issn09758887
dcterms.source.titleInternational Journal of Computer Applications
curtin.departmentDepartment of Electrical and Computer Engineering
curtin.accessStatusFulltext not available


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