Classification of Single Line to Ground Faults on Double Circuit Transmission Line using ANN

Abstract— This paper discusses the potential application of ANN techniques for detection of single line to ground faults and fault type classification on double circuit transmission lines with remote end infeed. Distance protection of double circuit transmission lines has been a very challenging task. The problems arise principally as a result of the mutual coupling between the two circuits under different fault conditions. An accurate algorithm for fault detection and classification of single line-to-ground faults (A1N, A2N, B1N, B2N, C1N & C2N) in double circuit transmission line considering the effects of mutual coupling, high fault resistance, varying fault location, fault inception angle and remote source infeed is presented using feed forward neural network (FFNN) algorithm. The algorithm employs the fundamental components of voltage and current signals. This technique neither requires communication link to retrieve the remote end data nor zero sequence current compensation for healthy phases are required. This is a major advantage of the proposed algorithm for protection of double circuit line fed from both the ends. Results of study on a 220 kV transmission line are presented as an illustration. Simulation results indicate that algorithm is immune to the effect of mutual coupling, fault type, fault inception angle, fault resistance, fault location and remote end infeed. Index Terms— Artificial neural network, Double circuit transmission line, Fault detection & classification, High impedance fault, Single line-to-ground fault.

[1]  I. Pavic,et al.  Double-circuit line adaptive protection based on Kohonen neural network considering different operation and switching modes , 2002, LESCOPE'02. 2002 Large Engineering Systems Conference on Power Engineering. Conference Proceedings.

[2]  Tahar Bouthiba,et al.  Fault location in EHV transmission lines using artificial neural networks , 2004 .

[3]  H. Khorashadi-Zadeh,et al.  Transmission Line Fault Detection & Phase Selection using ANN , 2003 .

[4]  L. van der Sluis,et al.  Adaptive Distance Protection of Double-Circuit Lines using Artificial Neural Networks , 1997, IEEE Power Engineering Review.

[5]  Zhang Zhaoning,et al.  Application of wavelet fuzzy neural network in locating single line to ground fault (SLG) in distribution lines , 2007 .

[6]  Denis V. Coury,et al.  Artificial neural network approach to distance protection of transmission lines , 1998 .

[7]  R. N. Patel,et al.  Fault Classification of Double Circuit Transmission Line Using Artificial Neural Network , 2008 .

[8]  M. R. Aghaebrahimi,et al.  A Novel Approach to Fault Classification and Fault Location for Medium Voltage Cables Based on Artificial Neural Network , 2006 .

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

[10]  V. Fernao Pires,et al.  A neural space vector fault location for parallel double-circuit distribution lines , 2005 .

[11]  S. A. Khaparde,et al.  An adaptive approach in distance protection using an artificial neural network , 1996 .

[12]  Inmaculada Zamora,et al.  A new approach to fault location in two-terminal transmission lines using artificial neural networks , 2000 .

[13]  D. Thukaram,et al.  ANN applications in fault locators , 2001 .

[14]  R. Patel,et al.  MATLAB-Based Modelling of Power System Components in Transient Stability Analysis , 2005 .