New ANN-Based Algorithms for Detecting HIFs in Multigrounded MV Networks

Application of two new ANN-based algorithms for arcing high impedance fault (HIF) detection in multigrounded medium-voltage (MV) distribution networks is presented in this paper. The paper provides an evaluation of two new structures of artificial neural networks (ANNs) that may be used for reliable HIF detection in multigrounded as well as isolated, compensated, and grounded via small resistance distribution grids. The results obtained by use of both neural nets are presented. The performance was tested using data obtained from staged HIFs in real MV network as well as from electromagnetic transients program-alternative transients program simulations. A small number of necessary neurons in developed ANNs, short measuring sliding data window, and easy interpretation of obtained output signals are the main advantages of the proposed approach. Satisfactory results of ANN performance were observed for all examined HIF cases in which the ground fault current was greater than 16 A. The selected ANNs of best performance show high reliability and immunity to transients resulting from switching operations in protected feeders and from capacitor bank switching.

[1]  John A. Orr,et al.  High impedance fault arcing on sandy soil in 15 kV distribution feeders: contributions to the evaluation of the low frequency spectrum , 1990 .

[2]  G. Swift,et al.  Detection of high impedance arcing faults using a multi-layer perceptron , 1992 .

[3]  Shyh-Jier Huang,et al.  High-impedance fault detection utilizing a Morlet wavelet transform approach , 1999 .

[4]  Mohamed A. Deriche,et al.  A high impedance fault detector using a neural network and subband decomposition , 2001, Proceedings of the Sixth International Symposium on Signal Processing and its Applications (Cat.No.01EX467).

[5]  Sang-Hee Kang,et al.  High-impedance fault detection in distribution networks with use of wavelet-based algorithm , 2006, IEEE Transactions on Power Delivery.

[6]  D. Sutanto,et al.  High-impedance fault detection using discrete wavelet transform and frequency range and RMS conversion , 2005, IEEE Transactions on Power Delivery.

[7]  Soon-Ryul Nam,et al.  A modeling method of a high impedance fault in a distribution system using two series time-varying resistances in EMTP , 2001, 2001 Power Engineering Society Summer Meeting. Conference Proceedings (Cat. No.01CH37262).

[8]  M. Kizilcay,et al.  Digital simulation of fault arcs in power systems , 2007 .

[9]  B. Don Russell,et al.  Distribution High Impedance Fault Detection Utilizing High Frequency Current Components , 1982, IEEE Power Engineering Review.

[10]  James A. Momoh,et al.  An implementation of a hybrid intelligent tool for distribution system fault diagnosis , 1996 .

[11]  David C. Yu,et al.  An adaptive high and low impedance fault detection method , 1994 .

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

[13]  Ming-Ta Yang,et al.  Detection of high impedance fault in distribution feeder using wavelet transform and artificial neural networks , 2004, 2004 International Conference on Power System Technology, 2004. PowerCon 2004..

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

[15]  Mark W. White,et al.  A neural network approach to the detection of incipient faults on power distribution feeders , 1990 .