Artificial neural network application to voltage stability considering power system configuration

Shinichi Iwamoto, Masahiro Kinoshita, Chen Ching Liu

    Research output: Contribution to journalArticle

    1 Citation (Scopus)

    Abstract

    In the power system area, the artificial neural network theory has been applied to various subjects. However, when applying this theory to practical power system models, the dimensional problem is often encountered. Namely, the required memory and learning time increase dramatically with the size of the power system. In this paper, we propose a neural network model which exploits power system configuration in order to reduce the required memory. The proposed neural network is applied to the calculation of a voltage stability index and estimation of the initial value for computation of the unstable power flow solutions. Numerical simulations based on a 43-bus power system model demonstrate the effectiveness of the proposed method.

    Original languageEnglish
    Pages (from-to)39-45
    Number of pages7
    JournalInternational Journal of Engineering Intelligent Systems for Electrical Engineering and Communications
    Volume2
    Issue number1
    Publication statusPublished - 1994 Mar

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    Voltage control
    Neural networks
    Data storage equipment
    Circuit theory
    Computer simulation

    ASJC Scopus subject areas

    • Engineering(all)

    Cite this

    Artificial neural network application to voltage stability considering power system configuration. / Iwamoto, Shinichi; Kinoshita, Masahiro; Liu, Chen Ching.

    In: International Journal of Engineering Intelligent Systems for Electrical Engineering and Communications, Vol. 2, No. 1, 03.1994, p. 39-45.

    Research output: Contribution to journalArticle

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