A Fault Detection and Classification Technique Based on Sequential Components

This paper presents a fault classification technique for transmission lines based on the fault sequence components, for fast and reliable operation of protective relays. First, symmetrical components of fault current and voltage signals are extracted. Next, the fault type is classified using the zero and negative sequences. To realize the faulted phases in ground faults, a criterion index based on the zero and negative sequences is defined. The imaginary part of the defined criterion index is used. This index is maximum in the faulted phase in single-phase-to-ground faults, and it is minimum in one of the faulted phases in phase-to-phase-to-ground faults. In addition, to identify ungrounded faults, a different criterion index using the positive and negative sequences is defined. The results show that the scheme provides a fast fault classification, without the need for a threshold to operate.

[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]  N.S.D. Brito,et al.  Haar Wavelet-Based Method for Fast Fault Classification in Transmission Lines , 2006, 2006 IEEE/PES Transmission & Distribution Conference and Exposition: Latin America.

[3]  Adly A. Girgis,et al.  Analysis of high-impedance fault generated signals using a Kalman filtering approach , 1990 .

[4]  S.M. Rovnyak,et al.  Decision tree-based methodology for high impedance fault detection , 2004, IEEE Transactions on Power Delivery.

[5]  Alessandro Ferrero,et al.  A fuzzy-set approach to fault-type identification in digital relaying , 1994 .

[6]  B. Jeyasurya,et al.  Transmission line distance protection using wavelet transform algorithm , 2004, IEEE Transactions on Power Delivery.

[7]  Alexander Mamishev,et al.  Analysis of high impedance faults using fractal techniques , 1995 .

[8]  Xiang-Ning Lin,et al.  Novel design of a fast phase selector using correlation analysis , 2005, IEEE Transactions on Power Delivery.

[9]  N.S.D. Brito,et al.  Fault detection and classification in transmission lines based on wavelet transform and ANN , 2006, IEEE Transactions on Power Delivery.

[10]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  M.M. Mansour,et al.  High-phase order power transmission lines relaying approach based on the wavelet analysis of the fault generated traveling waves , 2004, 39th International Universities Power Engineering Conference, 2004. UPEC 2004..

[12]  Michel Meunier,et al.  Classification of power distribution system fault currents using wavelets associated to artificial neural networks , 1996, Proceedings of Third International Symposium on Time-Frequency and Time-Scale Analysis (TFTS-96).

[13]  David Chan Tat Wai,et al.  A novel technique for high impedance fault identification , 1998 .

[14]  B. D. Russell,et al.  A digital signal processing algorithm for detecting arcing faults on power distribution feeders , 1989 .

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

[16]  O.P. Malik,et al.  Transmission line distance protection based on wavelet transform , 2004, IEEE Transactions on Power Delivery.

[17]  G. Panda,et al.  Fault Classification and Section Identification of an Advanced Series-Compensated Transmission Line Using Support Vector Machine , 2007, IEEE Transactions on Power Delivery.

[18]  O.P. Malik,et al.  High impedance fault detection based on wavelet transform and statistical pattern recognition , 2005, IEEE Transactions on Power Delivery.