Broken Conductor Detection on Power Distribution Feeder

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An irregular activity on electric power distribution feeder, which does not draw adequate fault current to be detected by general protective devices, is called as High impedance fault (HIF). This paper presents the algorithm for HIF detection based on the amplitude of third and fifth harmonics of current, voltage and power. It proposes an intelligent algorithm using the Fuzzy Subtractive Clustering Model (FSCM) to detect the high impedance fault. The Fast Fourier Transformation (FFT) is used to extract the feature of the faulted signals and other power system events. The effect of capacitor bank switching, non-linear load current, no-load line switching and other normal event on distribution feeder harmonics is discussed. The HIF and other operation event data were obtained by simulation of a 13.8 kV distribution feeder using PSCAD. It is evident from the outcomes that the proposed algorithm can effectively differentiate the HIFs from other events in power distribution feeder
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FFT; High Impedance Faults; Subtractive Clustering; TSK Fuzzy Modeling

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M. Sedighizadeh, a. Rezazadeh, and N. I. Elkalashy, “Approaches in High Impedance Fault Detection - A Chronological Review,” Advances in Electrical and Computer Engineering, vol. 10, no. 3, pp. 114–128, 2010.

B. Aucoin and B. Russell, “Distribution high impedance fault detection utilizing high frequency current components,” IEEE Trans. Power Apparatus and Systems, vol. PAS-101, no. 6, pp. 1596–1606, 1982.

E. M. Emanuel, A.E., Cyganski, D., Orr, J.A., Shiller, S., Gulachenski, “High impedance fault arcing on sandy soil in 15 kV distribution feeders: contributions to the evaluation of the low frequency spectrum,” IEEE Trans. Power Delivery, …, vol. 5, no. 2, pp. 676–686, 1990.

W. Kwon and G. Lee, “High impedance fault detection utilizing incremental variance of normalized even order harmonic power,” IEEE Trans. Power Deliv, vol. 6, no. 2, pp. 557–564, 1991.

R. P. Russell, B.D., Mehta, K., Cinchali, “An arcing fault detection technique using low frequency current components performance evaluation using recorded field data,” IEEE Trans. Power Deliv, vol. 3, no. 4, pp. 1493–1500, 1988.

S. Lien, K.Y., Chen, S.L., Tzong, C.J.L., Guo, Y., Lin, T.M., Shen, “Energy variance criterion and threshold tuning scheme for high impedance fault detection,” IEEE Trans. Power Deliv, vol. 14, no. 3, pp. 810–817, Jul. 1999.

J. A. Lazkano, A., Ruiz, J., Aramendi, E., Gonzalez, “Study of high impedance fault detection in levante area in Spain,” Proc. Int. Conf. Harmonics and Quality of power, pp. 1011–1016, 2000.

A. G. Lai, L.L., Styvaktakis, E., Sichanie, “Application of discrete wavelet transform to high impedance fault identification,” Proc. Int. Conf. Energy Management and Power Deliveivery, pp. 689–693, 1998.

T. M. Lai, L. a. Snider, E. Lo, and D. Sutanto, “High-Impedance Fault Detection Using Discrete Wavelet Transform and Frequency Range and RMS Conversion,” IEEE Trans. Power Deliv, vol. 20, no. 1, pp. 397–407, Jan. 2005.

M. . Sedighi, A.R., Haghifam, M.R., Malik, O.P., Ghassemian, “High impedance fault detection based on wavelet transform and statistical pattern recognition,” IEEE Trans. Power Deliv, vol. 20, no. 4, pp. 2414–2421, 2005.

Sulaiman, M., Adnan H. Tawafan, High impedance fault detection on power distribution feeder, (2012) International Review on Modelling and Simulations (IREMOS), 5 (5), pp. 2197–2204.

A. Etemadi and M. Sanaye-Pasand, “High-impedance fault detection using multi-resolution signal decomposition and adaptive neural fuzzy inference system,” Generation, Transmission & …, vol. 2, no. 1, pp. 110–118, 2008.

S. H. Michalik, M., Lukowicz, M., Rabizant, W., Lee, S.J., Kang, “New ANN-based algorithms for detecting HIFs in multigrounded MV networks,” IEEE Trans. Power Deliv, vol. 23, no. 1, pp. 58–66, 2008.

P. K. Samantaray, S.R., Panigrahi, B.K., Dash, “High impedance fault detection in power distribution networks using time-frequency transform and probabilistic neural network,” IET Generation, Transmission & Distribution, vol. 2, no. 2, pp. 261–270, 2008.

N. Ghaffarzadeh and B. Vahidi, “A New Protection Scheme for High Impedance Fault Detection using Wavelet Packet Transform,” Advances in Electrical and Computer Engineering, vol. 10, no. 3, pp. 17–20, 2010.

O. P. Haghifam, M.-R.; Sedighi, A.-R.; Malik, “Development of a fuzzy inference system based on genetic algorithm for high-impedance fault detection,” Generation, Transmission & …, vol. 153, no. 3, pp. 359–367, 2006.

S. Saleem and A. Sharaf, “A fuzzy ARTMAP based high impedance arc fault detection scheme,” in Electrical and Computer Engineering,2008. CCECE 2008. Canadian Conference on, 2008, pp. 871–876.

M. Tagaki, T., Sugeno, “Fuzzy identification of systems and its application to modeling and control.pdf,” IEEE Transactions on systems, Menand Cybemetics 15, pp. 116–132, 1985.

M. Sugeno and G. T. Kang, “Structure identification of fuzzy model,” Fuzzy Sets and Systems, vol. 28, no. 1, pp. 15–33, 1988.

Chiu SL, “fuzzy model identification based on cluster estimation.pdf,” journal of intelligent and fuzzy systems, vol. 2, pp. 267–278, 1994.

T. Lai, L. Snider, and E. Lo, “Wavelet transform based relay algorithm for the detection of stochastic high impedance faults,” International Conference on Power Systems Transients, vol. 1, no. 1, pp. 1–6, 2003.


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