Generalization of transient stability solution using neural network theory

Katsumi Ikenono, Shinichi Iwamoto

    Research output: Contribution to journalArticle

    1 Citation (Scopus)

    Abstract

    This paper presents a generalized online transient stability solution technique using the backpropagation method of the neural network theory. The proposed solution technique can be used for general generator models, including controllers such as AVRs and governors, that have been difficult for the energy function method to handle. The proposed method also considers alterations of network configurations and changes of the number of operating generators. Further, the relationship between input data and effects on the results of the neural network is considered.

    Original languageEnglish
    Pages (from-to)72-79
    Number of pages8
    JournalElectrical Engineering in Japan (English translation of Denki Gakkai Ronbunshi)
    Volume112
    Issue number3
    DOIs
    Publication statusPublished - 1992

    Fingerprint

    Circuit theory
    Neural networks
    Governors
    Backpropagation
    Controllers

    ASJC Scopus subject areas

    • Energy Engineering and Power Technology
    • Electrical and Electronic Engineering

    Cite this

    Generalization of transient stability solution using neural network theory. / Ikenono, Katsumi; Iwamoto, Shinichi.

    In: Electrical Engineering in Japan (English translation of Denki Gakkai Ronbunshi), Vol. 112, No. 3, 1992, p. 72-79.

    Research output: Contribution to journalArticle

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