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    Congestion Management using Genetic Algorithm in Deregulated Power Environments

    Access Status
    Fulltext not available
    Authors
    Nabavi, S.
    Kazemi, A.
    Masoum, Mohammad Sherkat
    Date
    2011
    Type
    Journal Article
    
    Metadata
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    Citation
    Nabavi, 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.
    Source Title
    International Journal of Computer Applications
    Additional URLs
    http://www.ijcaonline.org/volume18/number2/pxc3872894.pdf
    ISSN
    09758887
    School
    Department of Electrical and Computer Engineering
    URI
    http://hdl.handle.net/20.500.11937/19082
    Collection
    • Curtin Research Publications
    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.

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