Reactive power tracing in pool-based power system utilising the hybrid genetic algorithm and least squares support vector machine

M. W. Mustafa, M. H. Sulaiman, H. Shareef, S. N Abd Khalid

    Research output: Contribution to journalArticle

    20 Citations (Scopus)

    Abstract

    This study presents a new method for reactive power tracing in a pool-based power system by introducing the hybrid genetic algorithm and least squares support vector machine (GA-LSSVM). The idea is to use GA to obtain the optimal values of regularisation parameter, γ, and kernel radial basis function (RBF) parameter, σ2, and adopt a supervised learning approach to train the LSSVM model. The technique that uses proportional sharing method (PSM) is used as a teacher. To obtain a lossless system, the concept of virtual load is proposed. Prior to that, the equivalent transmission line model is introduced. It integrates the nodal reactive power with the power produced by shunt admittances. Based on power-flow solution and reactive power tracing procedure by PSM, the description of inputs and outputs for training and testing data is created. The generators' shares to reactive loads in the test system are expected can be determined accurately by proposed GA-LSSVM model. In this study, five-bus system is used to illustrate the concept of virtual load and equivalent transmission line model whereas the 25-bus equivalent system of southern Malaysia is used to illustrate the effectiveness of the proposed GA-LSSVM model compared to PSM and artificial neural network.

    Original languageEnglish
    Pages (from-to)133-141
    Number of pages9
    JournalIET Generation, Transmission and Distribution
    Volume6
    Issue number2
    DOIs
    Publication statusPublished - Feb 2012

    Fingerprint

    Reactive power
    Support vector machines
    Genetic algorithms
    Electric lines
    Supervised learning
    Neural networks
    Testing

    ASJC Scopus subject areas

    • Electrical and Electronic Engineering
    • Energy Engineering and Power Technology
    • Control and Systems Engineering

    Cite this

    Reactive power tracing in pool-based power system utilising the hybrid genetic algorithm and least squares support vector machine. / Mustafa, M. W.; Sulaiman, M. H.; Shareef, H.; Khalid, S. N Abd.

    In: IET Generation, Transmission and Distribution, Vol. 6, No. 2, 02.2012, p. 133-141.

    Research output: Contribution to journalArticle

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