Fault Detection and Classification Logic for Transmission Lines Using Multi-resolution Wavelet Analysis

Abstract This article presents a fast, hardware efficient logic for fault detection and classification in transmission lines. The proposed logic employs only one-terminal current samples and is based on multi-resolution wavelet analysis. First-level high-frequency details of the modal currents in the range of 5 to 10 kHz are extracted. Depending on the amount of high-frequency components in the transformed current signals after processing, the faults are classified into ten types. An adaptive threshold value is chosen, rather than a fixed threshold in the case of faults involving the ground, to make the classification reliable and accurate. The validity of the proposed logic was exhaustively tested by simulating various types of faults on a system modeled in Alternative Transient Program (ATP)/Electromagnetic Transient Program (EMTP).The proposed logic was found to be acceptably reliable and accurate even in the presence of fault resistance and current transformer (CT) saturation.

[1]  O.A.S. Youssef,et al.  Combined fuzzy-logic wavelet-based fault classification technique for power system relaying , 2004, IEEE Transactions on Power Delivery.

[2]  Yuan Liao,et al.  Fault Noise Based Approach to Phase Selection Using Wavelets Based Feature Extraction , 1999 .

[3]  R.K. Aggarwal,et al.  A New Approach to Phase Selection Using Fault Generated High Frequency Noise and Neural Networks , 1997, IEEE Power Engineering Review.

[4]  James S. Thorp,et al.  Computer Relaying for Power Systems , 2009 .

[5]  J. M. Drake,et al.  Realtime fault detection and classification in power systems using microprocessors , 1994 .

[6]  B. Das,et al.  Fuzzy-logic-based fault classification scheme for digital distance protection , 2005, IEEE Transactions on Power Delivery.

[7]  A. T. Johns,et al.  Digital Protection for Power Systems , 1995 .

[8]  Zhiqian Bo,et al.  Positional protection of transmission line using fault generated high frequency transient signals , 2000 .

[9]  M. D. Cox,et al.  Discrete wavelet analysis of power system transients , 1996 .

[10]  O. P. Malik,et al.  Study of Wavelet-Based Ultra-High-Speed Directional Transmission Line Protection , 2002, IEEE Power Engineering Review.

[11]  W. L. Chan,et al.  Study of protection scheme for transmission line based on wavelet transient energy , 2006 .

[12]  P. R. Drum,et al.  C37.110 guide for the application of current transformers used for protective relaying purposes , 1999 .

[13]  O.A.S. Youssef.  Fault classification based on wavelet transforms , 2001, 2001 IEEE/PES Transmission and Distribution Conference and Exposition. Developing New Perspectives (Cat. No.01CH37294).

[14]  Ingrid Daubechies,et al.  The wavelet transform, time-frequency localization and signal analysis , 1990, IEEE Trans. Inf. Theory.

[15]  B. Kulicke,et al.  Neural network approach to fault classification for high speed protective relaying , 1995 .

[16]  U. Jayachandra Shenoy,et al.  Classification of power system faults using wavelet transforms and probabilistic neural networks , 2003, Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS '03..

[17]  R. N. Mahanty,et al.  Comparison of Fault Classification Methods Based on Wavelet Analysis and ANN , 2006 .

[18]  C. J. Kim,et al.  Classification of Faults and Switching Events by Inductive Reasoning and Expert System Methodology , 1989, IEEE Power Engineering Review.

[19]  M. M. Mansour,et al.  A Multi-Microprocessor Based Travelling Wave Relay - Theory and Realization , 1986, IEEE Transactions on Power Delivery.

[20]  Huisheng Wang,et al.  Fuzzy-neuro approach to fault classification for transmission line protection , 1998 .

[21]  H.H. Zurn,et al.  An approach using wavelet transform for fault type identification in digital relaying , 1999, 1999 IEEE Power Engineering Society Summer Meeting. Conference Proceedings (Cat. No.99CH36364).