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  • Research Article
  • Open Access

Wavelet Transform for Processing Power Quality Disturbances

EURASIP Journal on Advances in Signal Processing20072007:047695

  • Received: 29 April 2006
  • Accepted: 17 February 2007
  • Published:


The emergence of power quality as a topical issue in power systems in the 1990s largely coincides with the huge advancements achieved in the computing technology and information theory. This unsurprisingly has spurred the development of more sophisticated instruments for measuring power quality disturbances and the use of new methods in processing and analyzing the measurements. Fourier theory was the core of many traditional techniques and it is still widely used today. However, it is increasingly being replaced by newer approaches notably wavelet transform and especially in the post-event processing of the time-varying phenomena. This paper reviews the use of wavelet transform approach in processing power quality data. The strengths, limitations, and challenges in employing the methods are discussed with consideration of the needs and expectations when analyzing power quality disturbances. Several examples are given and discussions are made on the various design issues and considerations, which would be useful to those contemplating adopting wavelet transform in power quality applications. A new approach of combining wavelet transform and rank correlation is introduced as an alternative method for identifying capacitor-switching transients.


  • Information Technology
  • Power System
  • Quality Data
  • Quantum Information
  • Wavelet Transform

Authors’ Affiliations

School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore


  1. IEC 61000-2-1 : Electromagnetic compatibility (EMC)—part 2: environment - section 1: description of the environment - electromagnetic environment for low-frequency conducted disturbances and signalling in public power supply systems. 1st edition, 1990Google Scholar
  2. IEEE Std. 1159–1995 : IEEE Recommended Practice for Monitoring Electric Power Quality. 1995.Google Scholar
  3. IEC 61000-2-2 : Electromagnetic compatibility (EMC)—part 2-2: environment - compatibility levels for low-frequency conducted disturbances and signalling in public low-voltage power supply systems. 2nd edition, 2002Google Scholar
  4. Gu IY-H, Styvaktakis E: Bridge the gap: signal processing for power quality applications. Electric Power Systems Research 2003,66(1):83-96. 10.1016/S0378-7796(03)00074-9View ArticleGoogle Scholar
  5. Gu IY-H, Bollen MHJ: Time-frequency and time-scale domain analysis of voltage disturbances. IEEE Transactions on Power Delivery 2000,15(4):1279-1284. 10.1109/61.891515View ArticleGoogle Scholar
  6. Bruce A, Donoho D, Gao H-Y: Wavelet analysis [for signal processing]. IEEE Spectrum 1996,33(10):26-35. 10.1109/6.540087View ArticleGoogle Scholar
  7. Graps A: An introduction to wavelets. IEEE Computational Science & Engineering 1995,2(2):50-61. 10.1109/99.388960View ArticleGoogle Scholar
  8. Fernández RMC, Rojas HND: An overview of wavelet transforms in power system. Proceedings of the 14th Power System Computational Conference (PSCC '02), June 2002, Sevilla, SpainGoogle Scholar
  9. Mallat S: A Wavelet Tour of Signal Processing. 2nd edition. Academic Press, San Diego, Calif, USA; 1999.MATHGoogle Scholar
  10. Robertson DC, Camps OI, Mayer JS, Gish Sr WB: Wavelets and electromagnetic power system transients. IEEE Transactions on Power Delivery 1996,11(2):1050-1056. 10.1109/61.489367View ArticleGoogle Scholar
  11. Karimi M, Mokhtari H, Iravani MR: Wavelet based on-line disturbance detection for power quality applications. IEEE Transactions on Power Delivery 2000,15(4):1212-1220. 10.1109/61.891505View ArticleGoogle Scholar
  12. Wilkinson WA, Cox MD: Discrete wavelet analysis of power system transients. IEEE Transactions on Power Systems 1996,11(4):2038-2044. 10.1109/59.544682View ArticleGoogle Scholar
  13. Butler-Purry KL, Bagriyanik M: Characterization of transients in transformers using discrete wavelet transforms. IEEE Transactions on Power Systems 2003,18(2):648-656. 10.1109/TPWRS.2003.810979View ArticleGoogle Scholar
  14. Poisson O, Rioual P, Meunier M: Detection and measurement of power quality disturbances using wavelet transform. IEEE Transactions on Power Delivery 2000,15(3):1039-1044. 10.1109/61.871372View ArticleGoogle Scholar
  15. Santoso S, Grady WM, Powers EJ, Lamoree J, Bhatt SC: Characterization of distribution power quality events with Fourier and wavelet transforms. IEEE Transactions on Power Delivery 2000,15(1):247-254. 10.1109/61.847259View ArticleGoogle Scholar
  16. Hong Y-Y, Wang C-W: Switching detection/classification using discrete wavelet transform and self-organizing mapping network. IEEE Transactions on Power Delivery 2005,20(2, part 2):1662-1668. 10.1109/TPWRD.2004.833921View ArticleGoogle Scholar
  17. Zhu TX, Tso SK, Lo KL: Wavelet-based fuzzy reasoning approach to power-quality disturbance recognition. IEEE Transactions on Power Delivery 2004,19(4):1928-1935. 10.1109/TPWRD.2004.832382View ArticleGoogle Scholar
  18. Gaing Z-L: Wavelet-based neural network for power disturbance recognition and classification. IEEE Transactions on Power Delivery 2004,19(4):1560-1568. 10.1109/TPWRD.2004.835281View ArticleGoogle Scholar
  19. Lin C-H, Tsao M-C: Power quality detection with classification enhancible wavelet-probabilistic network in a power system. IEE Proceedings: Generation, Transmission and Distribution 2005,152(6):969-976. 10.1049/ip-gtd:20045177View ArticleGoogle Scholar
  20. IEC 61000-4-7 : Electromagnetic compatibility (EMC)—part 4-7: testing and measurement techniques - general guide on harmonics and interharmonics measurement and instrumentation, for power supply systems and equipment connected thereto. International Electrotechnical Commission, 2002Google Scholar
  21. Barros J, Diego RI: Application of the wavelet-packet transform to the estimation of harmonic groups in current and voltage waveforms. IEEE Transactions on Power Delivery 2006,21(1):533-535. 10.1109/TPWRD.2005.848437View ArticleGoogle Scholar
  22. Saied MM: Capacitor switching transients: analysis and proposed technique for identifying capacitor size and location. IEEE Transactions on Power Delivery 2004,19(2):759-765. 10.1109/TPWRD.2003.822953View ArticleGoogle Scholar
  23. William HP, Brian PF, Saul AT, William TV: Numerical Recipes in C: The Art of Scientific Computing. 2nd edition. Cambridge University Press, Cambridge, UK; 1992.MATHGoogle Scholar
  24. Durbak DW: Modeling guidelines for switching transients, modeling and analysis of system transients. IEEE PES special publication, 1998Google Scholar
  25. Hwang W-L, Mallat S: Singularities and noise discrimination with wavelets. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '92), March 1992, San Francisco, Calif, USA 4: 377–380.Google Scholar
  26. Mallat S, Hwang W-L: Singularity detection and processing with wavelets. IEEE Transactions on Information Theory 1992,38(2, part 2):617-643. 10.1109/18.119727MathSciNetView ArticleGoogle Scholar
  27. Daubechies I: Ten Lectures on Wavelets. SIAM, Philadelphia, Pa, USA; 1992.View ArticleGoogle Scholar
  28. Huang S-J, Hsieh C-T, Huang C-L: Application of Morlet wavelets to supervise power system disturbances. IEEE Transactions on Power Delivery 1999,14(1):235-243. 10.1109/61.736728View ArticleGoogle Scholar
  29. User's Guide of Wavelet Toolbox MathWorks, 2004,


© S. Chen and H. Y. Zhu. 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.