教師資料查詢 | 類別: 期刊論文 | 教師: 蘇木春 SU MU-CHUN (瀏覽個人網頁)

標題:Neuro-fuzzy approach to real-time transient stability prediction based on synchronized phasor measurements
學年87
學期2
出版(發表)日期1999/03/01
作品名稱Neuro-fuzzy approach to real-time transient stability prediction based on synchronized phasor measurements
作品名稱(其他語言)
著者Liu, Chih-wen; Tsay, Shuenn-shing; Wang, Yi-jen; 蘇木春; Su, Mu-chun
單位淡江大學電機工程學系
出版者Elsevier
著錄名稱、卷期、頁數Electric power systems research 49(2), pp.123-127
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.
關鍵字Phasor measurement unit (PMU);Real-time transient stability prediction;Fuzzy hyperrectangular composite neural network (FHRCNN)
語言英文
ISSN0378-7796
期刊性質國外
收錄於
產學合作
通訊作者
審稿制度
國別荷蘭
公開徵稿
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