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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/46370


    Title: Neuro-fuzzy approach to real-time transient stability prediction based on synchronized phasor measurements
    Authors: Liu, Chih-wen;Tsay, Shuenn-shing;Wang, Yi-jen;蘇木春;Su, Mu-chun
    Contributors: 淡江大學電機工程學系
    Keywords: Phasor measurement unit (PMU);Real-time transient stability prediction;Fuzzy hyperrectangular composite neural network (FHRCNN)
    Date: 1999-03-01
    Issue Date: 2010-03-26 22:10:43 (UTC+8)
    Publisher: Elsevier
    Abstract: With new systems capable of making synchronized phasor measurements there are possibilities for real-time assessment of the stability of a transient swing in power systems. In the future, on-line control will be necessary as operating points are pushed closer toward the margin and fast reaction time becomes critical to the survival of the system. In this paper we develop a novel class of fuzzy hyperrectangular composite neural networks which utilize real-time phasor angle measurements to provide fast transient stability prediction for use with high-speed control. From simulation tests on a sample power system, it reveals that the proposed tool can yield a highly successful prediction rate in real-time.
    Relation: Electric power systems research 49(2), pp.123-127
    DOI: 10.1016/S0378-7796(98)00104-7
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Journal Article

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