Detection of Power Quality Disturbances using Wavelet Transform
Commenced in January 2007
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Edition: International
Paper Count: 32799
Detection of Power Quality Disturbances using Wavelet Transform

Authors: Sudipta Nath, Arindam Dey, Abhijit Chakrabarti

Abstract:

This paper presents features that characterize power quality disturbances from recorded voltage waveforms using wavelet transform. The discrete wavelet transform has been used to detect and analyze power quality disturbances. The disturbances of interest include sag, swell, outage and transient. A power system network has been simulated by Electromagnetic Transients Program. Voltage waveforms at strategic points have been obtained for analysis, which includes different power quality disturbances. Then wavelet has been chosen to perform feature extraction. The outputs of the feature extraction are the wavelet coefficients representing the power quality disturbance signal. Wavelet coefficients at different levels reveal the time localizing information about the variation of the signal.

Keywords: Power quality, detection of disturbance, wavelet transform, multiresolution signal decomposition.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1331533

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References:


[1] S. Santoso, E. J. Powers, W. M. Grady and P. Hofmann, "Power quality assessment via wavelet transform analysis", IEEE Trans. Power Delivery, vol. 11, no. 2, pp. 924-930, Apr. 1996.
[2] G.T. Heydt and A.W. Galli, "Transient power quality problems analyzed using wavelets", IEEE Trans. Power Delivery, vol. 12, no. 2, pp. 908- 915, Apr. 1997.
[3] T. Hiyama, W. Hubbi and T.H. Ortmeyer, "Fuzzy logic control scheme with variable gain for static VAR compensator to enhance power system stability", IEEE Trans. on Power Systems, vol. 14, no. 1, pp. 186-191, February 1999.
[4] S. Santoso, W. M. Grady, E. J. Powers, J. Lamoree and S. C. Bhatt, "Characterization of distribution power quality events with fourier and wavelet transforms", IEEE Trans. Power Delivery, vol. 15, no. 1, pp. 247-254, Jan. 2000.
[5] P.K. dash, S. Mishra, M.M. A. Salama and A.C. Liew, "Classification of power system disturbances using a fuzzy expert system and a fourier linear combiner" IEEE Trans. Power Delivery, vol. 15, no. 2, pp. 472- 477, Apr. 2000.
[6] O. Poisson, P. Rioual and M. Meunier, "Detection and measurement of power quality disturbances using wavelet transform" IEEE Trans. Power Delivery, vol. 15, no. 3, pp. 1039-1044, July 2000.
[7] L. Angrisani, P. Daponte and Massimo D. Apuzzo, "Wavelet network based detection and classification of transients" IEEE Trans. Power Delivery, vol. 50, no. 5, pp. 1425-1435, Oct. 2001.
[8] E. Styvaktakis, M. H. J. Bollen and I.Y.H. Gu, "Expert system for classification and analysis of power system events", IEEE Trans. Power Delivery, vol. 17, no. 2, pp. 423-428, Apr. 2002.
[9] J. Huang, M. Negnevitsky and D. T. Nguyen, "A neural-fuzzy classifier for recognition of power quality disturbances", IEEE Trans. Power Delivery, vol. 17, no. 2, pp. 609-616, April 2002.
[10] J.L.J. Driesen and R. J.M. Belmans, "Wavelet based power quantification approaches", IEEE Trans. Power Delivery, vol. 52, no. 4, pp. 1232-1238, August 2003.
[11] H. He and J. A. Starzyk, "A self-organizing learning array system for power quality classification based on wavelet transform", IEEE Trans. Power Delivery, vol. 21, no. 1, pp. 286-295, Jan. 2006.
[12] C.H. Lin and C.H. Wang, "Adaptive wavelet networks for power quality detection and discrimination in a power system", IEEE Trans. Power Delivery, vol. 21, no. 3, pp. 1106-1113, July 2006.
[13] A. I. Megahed, A.M. Moussa and A.E. Bayoumy, "Usage of wavelet transform in the protection of series-compensated transmission lines", IEEE Trans. Power Delivery, vol. 21, no. 3, pp. 1213-1221, July 2006.
[14] M. Michalik, W. Rebizant, M. Lukowicz, S. J. Lee and S. H. Kang, "High-impedance fault detection in distribution networks with use of wavelet-based algorithm", IEEE Trans. Power Delivery, vol. 21, no. 4, pp. 1793-1802, October 2006.
[15] W.R.A. Ibrahim and M.M. Morcos, "An adaptive fuzzy self-learning technique for prediction of abnormal operation of electrical systems" IEEE Trans. Power Delivery, vol. 21, no. 4, pp. 1770-1777, October 2006.
[16] T. Tarasiuk, "Hybrid wavelet-fourier method for harmonics and harmonic subgroups measurement - case study" IEEE Trans. Power Delivery, vol. 22, no. 1, pp. 4-17, Jan. 2007.
[17] Y.Y. Hong and B.Y. Chen, "Locating switched capacitor using wavelet transform and hybrid principal component analysis network" IEEE Trans. Power Delivery, vol. 22, no. 2, pp. 1145-1152, April 2007.
[18] S.P. Valsan and K.S. Swarup, "Computationally efficient wavelettransform -based digital directional protection for busbars", IEEE Trans. Power Delivery, vol. 22, no. 3, pp. 1342-1350, July 2007.
[19] S. M. Brahma, "Distance relay with out-of-step blocking function using wavelet transform", IEEE Trans. Power Delivery, vol. 22, no. 3, pp. 1360-1366, July 2007.
[20] M.B. I. Reaz, F. Choong, M. S. Sulaiman, F. M. Yasin and M. Kamada, "Expert system for power quality disturbance classifier", IEEE Trans. Power Delivery, vol. 22, no. 3, pp. 1979-1988, July 2007.
[21] A.M. Gargoom, N. Ertugrul and W.L. Soong, "Investigation of effective automatic recognition systems of power quality events", IEEE Trans. Power Delivery, vol. 22, no. 4, pp. 2319-2326, October 2007.
[22] N.I. Elkalashy, M. Lehtonen, H.A. Darwish, A.M.I. Taalab and M.A. Izzularab, "DWT based detection and transient power direction based location of high impedance faults due to leaning trees in unearthed MV networks", IEEE Trans. Power Delivery, vol. 23, no. 1, pp. 94-101, January 2008.
[23] S. Mishra, C.N. Bhende and B.K. Panigrahi, "Detection and classification of power quality disturbances using S transform and probabilistic neural network", IEEE Trans. Power Delivery, vol. 23, no. 1, pp. 280-287, January 2008.