Wavelet Feature Based Fault Detection and Classification Technique for Transmission line Protection
Manish Kurre, PG scholar ,DIMAT raipur,CG,India; Shailesh M. Deshmukh ,Asst.Prof & Head of Department DIMAT raipur,CG,India
Transmission line, fault detection and classification, wavelet feature, multi-resolution analysis.
In the present scenario, the efficiency of a power system depends on how a fault is accurately detected and classified, so that quick restoration and maintenance of power is accomplished. Fault detection, fault classification, needs to be performed using a fast and responsive algorithm at different levels of a power system. Effect of factors such as fault impedance, fault inception angle (FIA), and fault distance, which cause disturbances in power line can be analyzed by Wavelet based multi resolution analysis (MRA). This paper proposed, a fault detection and classification technique using MRA based on wavelet transform. The present paper also deals with the exploration of advantages and problems related with the proposed fault detection and classification technique. The method of fault detection and classification proposed in this work is based on the three-phase current and voltage waveforms measured during the occurrence of fault in the power transmission-line. The technique proposed in this paper, is verified using MATLAB/Simulink software and the obtained results shows that the wavelet based MRA is a good tool for detection and classification of faults. However it is also shown that the most critical problem related to this technique is the selection of appropriate threshold values for all the three phases. It has been also shown that this technique requires expert hands and knowledge of the system for the selection of proper threshold value.
-
[1] M. Jayabharata Reddy, and D.K. Mohanta, “A wavelet-fuzzy combined approach for classification and location of transmission line faults “,International journal of Electrical Power and Energy system, Volume 29, Issue 9, pp 669-678, November 2007.
[2] Omar AS,” Combined fuzzy-logic wavelet-based fault classification technique for power system relaying”, IEEE Trans. On Power Delivery, Vol.19, No. 2, pp.582-589, July 2004.
[3] Biswarup Das and J.Vittal Reddy, “Fuzzy-Logic-Based Fault classification “, IEEE Trans. On power Delivery, Vol.20, No.2, pp 609-616, April, 2005.
[4] M. M. Tawfik and M. M. Morcos, “ANN-Based Techniques for Estimating Fault Location on Transmission Lines using Prony Method”, IEEE Trans. On Power Delivery, Vol. 16, No. 2, pp. 219-224, April 2001.
[5] Gopalakrishnan, M. Kezunovic, S. M. Mckenna, D. M. Hamai,”Fault Location using the Distributed Parameter Transmission Line Model”, IEEE Trans. On Power Delivery, Vol. 15, pp. 1169-1174, October, 2000.
[6] D. Chanda, N. K. Kishore, A. K. Sinha, “A Wavelet Multi resolution Analysis for Location of Faults on Transmission Lines”, Electrical Power & Energy Systems, Vol. 25, pp.59-69, October, 2003.
[7] H. Osman and O. P. Malik, “Protection of Parallel Transmission Lines using Wavelet Transform”, IEEE Transactions On Power Delivery, Vol. 19, No. 1, pp. 49-55, October, 2004.
[8] Ferrero A, Sangiovanni S, Zappitelli E, “ A fuzzy-set approach to fault type identification in digital relaying”, IEEE Trans. On Power Delivery, Vol. 10, No.1, pp. 169-175, July, 2003.
[9] M. Jaya Bharata Reddy, D. K. Mohanta and B. M. Karan, “Power System Disturbance Recognition using Wavelet and S-Transform Techniques”, International Journal of Emerging Electric Power Systems, Vol. 1, Issue. 2, pp. 1-16, October, 2004.
[10] “Wavelet Toolbox Users Guide” by the Math Works, http//:www.mathworks.com, 2006.
[11] Z. Y. He, X. Q. Chen and G. M. Luo, “Wavelet entropy measure definition and its application for transmission line fault detection and identification (part I: Definition and methodology),” in Proc. IEEE Int. Conf. Power System Technology, Oct. 2006, pp. 1–6.
[12] Zhengyou He, Ling Fu, Sheng Lin, and Zhiqian Bo, “Fault Detection and Classification in EHV Transmission Line Based on Wavelet Singular Entropy”, IEEE Transactions on Power Delivery, Vol.25, No.4, October 2010.
[13] O. A. S. Youssef, “Combined fuzzy-logic wavelet-based fault classification technique for power system relaying,” IEEE Trans. Power Del., vol. 19, no. 2, pp. 582–589, Apr. 2004.
[14] V. C. Klema and A. J. Laub, “The singular value decomposition: Its computation and some applications,” IEEE Trans. Autom. Control, vol. AC- 25, no. 2, pp. 164–176, Apr. 1980.
[15] J. Cadzow, “SVD representation of unitarily invariant matrices,” IEEE Trans. Acoust., Speech Signal Process., vol. 32, no. 3, pp. 512–516, Jun. 1984.
[16] C. E. Shannon, “A mathematical theory of communication,” Bell Syst. Tech. J., vol. 27, pp. 379–423, 623–656, Jul., Oct. 1948.
[17] S. G. Mallat, “A theory for multi-resolution signal decomposition: The wavelet representation,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 11, no. 7, pp. 674–693, Jul. 1989.
[18] Fernando H. Magnago and Ali Abur, “Fault Location Using Wavelets” IEEE Transactions on Power Delivery, Vol. 13, No. 4, October 1998.
[19] K. M. Silva, B. A. Souza, and N. S. D. Brito, ‘‘Fault detection and classification in transmission lines based on wavelet transform and ANN,’’ IEEE Trans. Power Del., vol. 21, no. 4, pp. 2058--2063, Oct. 2006.
Paper ID: GRDJEV01I060091
Published in: Volume : 1, Issue : 6
Publication Date: 2016-06-01
Page(s): 123 - 129
Published in: Volume : 1, Issue : 6
Publication Date: 2016-06-01
Page(s): 123 - 129