A Quick Classification Method of the Power Quality Disturbances

DOI: 10.4236/eng.2014.67040   PDF   HTML   XML   3,961 Downloads   5,398 Views  


This paper introduces a quick classification method of the power quality disturbances. Based on analyzing the characteristics of different electrical disturbance signals in time domain, four distinctive features are extracted from electrical signals for classifying different power quality disturbances and then an automatic classifier is proposed. Using the proposed classification method,a PQ monitor of the classifying power quality disturbances is developed based on the TMS320F2812DSP micro-processor. Semi-physical simulation, lab experiment and field measurement results have verified that this proposed method can classify single or complex disturbance signals effectively.

Share and Cite:

Yi Tang, Y. and Liu, H. (2014) A Quick Classification Method of the Power Quality Disturbances. Engineering, 6, 374-384. doi: 10.4236/eng.2014.67040.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Heydt, G.T., Fjeld, P.S., Liu, C.C., et al. (1999) Applications of the Window FFT to Electric Power Quality Assessment. IEEE Transactions on Power Delivery, 14, 1411-1416.
[2] Gaing, Z.-L. (2004) Wavelet-Based Neural Network for Power Disturbance Recognition and Classification. IEEE Transactions on Power Delivery, 19, 1560-1568.
[3] Ece, D.G. and Gerek, O.N. (2004) Power Quality Event Detection Using Joint 2-D-Wavelet Subspaces. IEEE Transactions on Instrumentation and Measurements, 53, 1040-1046.
[4] Chilukuri, M.V. and Dash, P.K. (2004) Multiresolution S-Transform-Based Fuzzy Recognition System for Power Quality Events. IEEE Transactions on Power Delivery, 19, 323-330.
[5] Gaouda, A.M., Salama, M.M.A., Sultan, M.K. and Chikhani, A.Y. (1999) Power Quality Detection and Classification Using Wavelet-Multiresolution Signal Decomposition. IEEE Transactions on Power Delivery, 14, 1469-1476. http://dx.doi.org/10.1109/61.796242
[6] Santoso, S., Powers, E.J., Grady, W.M. and Hofmann, P. (1996) Power Quality Assessment via Wavelet Transform Analysis. IEEE Transactions on Power Delivery, 11, 924-930.
[7] Dash, P.K., Panigrahi, B.K. and Panda, G. (2003) Power Quality Analysis Using S-Transform. IEEE Transactions on Power Delivery, 18, 406-411. http://dx.doi.org/10.1109/TPWRD.2003.809616
[8] Stockwell, R.G., Mansinha, L. and Lowe, R.P. (1996) Localization of the Complex Spectrum the S Transform. IEEE Transactions on Signal Processing, 44, 998-1001.
[9] Axelberg, P.G.V., Gu, I.Y.-H. and Bollen, M.H.J. (2007) Support Vector Machine for Classification of Voltage Disturbances. IEEE Transactions on Power Delivery, 22, 1297-1303.
[10] Mishra, S., Bhende, C.N. and Panigrahi, B.K. (2008) Detection and Classification of Power Quality Disturbances Using S-Transform and Probabilistic Neural Network. IEEE Transactions on Power Delivery, 23, 280-287. http://dx.doi.org/10.1109/TPWRD.2007.911125
[11] Zhao, F.Z. and Yang, R.G. (2007) Power-Quality Disturbance Recognition Using S-Transform. IEEE Transactions on Power Delivery, 22, 944-950. http://dx.doi.org/10.1109/TPWRD.2006.881575
[12] IEEE Std 1159-1995 (1995) IEEE Recommended Practice for Monitoring Electric Power Quality.

comments powered by Disqus

Copyright © 2020 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.