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http://dx.doi.org/10.5370/JEET.2015.10.3.729

Algorithm for Fault Detection and Classification Using Wavelet Singular Value Decomposition for Wide-Area Protection  

Lee, Jae-Won (College of Information and Communication Engineering, Sungkyunkwan University)
Kim, Won-Ki (College of Information and Communication Engineering, Sungkyunkwan University)
Oh, Yun-Sik (College of Information and Communication Engineering, Sungkyunkwan University)
Seo, Hun-Chul (School of IT Engineering, Yonam Institue of Digital Technolgy)
Jang, Won-Hyeok (Dept. of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign)
Kim, Yoon Sang (School of Computer and Science Engineering, Korea University of Technology and Education)
Park, Chul-Won (Dept. of Electrical Engineering, Gangneung-Wonju National University)
Kim, Chul-Hwan (College of Information and Communication Engineering, Sungkyunkwan University)
Publication Information
Journal of Electrical Engineering and Technology / v.10, no.3, 2015 , pp. 729-739 More about this Journal
Abstract
An algorithm for fault detection and classification method for wide-area protection in Korean transmission systems is proposed. The modeling of 345-kV and 765-kV Korean power system transmission networks using the Electro Magnetic Transient Program - Restructured Version (EMTP-RV) is presented and the algorithm for fault detection and classification in transmission lines is developed. The proposed algorithm uses the Wavelet Transform (WT) and Singular Value Decomposition (SVD). The Singular value of Approximation coefficient (SA) and part Sum of Detail coefficient (SD) are introduced. The characteristics of the SA and SD at the fault conditions are analyzed and used in the algorithm for fault detection and classification. The validation of the proposed algorithm is verified by various simulation results.
Keywords
EMTP-RV; Fault detection and classification; Transmission system; Wavelet singular value decomposition; Wide-area protection;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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