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    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/46370

    题名: Neuro-fuzzy approach to real-time transient stability prediction based on synchronized phasor measurements
    作者: Liu, Chih-wen;Tsay, Shuenn-shing;Wang, Yi-jen;蘇木春;Su, Mu-chun
    贡献者: 淡江大學電機工程學系
    关键词: Phasor measurement unit (PMU);Real-time transient stability prediction;Fuzzy hyperrectangular composite neural network (FHRCNN)
    日期: 1999-03-01
    上传时间: 2010-03-26 22:10:43 (UTC+8)
    出版者: Elsevier
    摘要: 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.
    關聯: Electric power systems research 49(2), pp.123-127
    DOI: 10.1016/S0378-7796(98)00104-7
    显示于类别:[電機工程學系暨研究所] 期刊論文


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