CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Application of wavelet Transform in power Quality: A Review

by Suresh K.Gawre, N.P.Patidar, R. K. Nema
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 39 - Number 18
Year of Publication: 2012
Authors: Suresh K.Gawre, N.P.Patidar, R. K. Nema
10.5120/5081-7307

Suresh K.Gawre, N.P.Patidar, R. K. Nema . Application of wavelet Transform in power Quality: A Review. International Journal of Computer Applications. 39, 18 ( February 2012), 30-36. DOI=10.5120/5081-7307

@article{ 10.5120/5081-7307,
author = { Suresh K.Gawre, N.P.Patidar, R. K. Nema },
title = { Application of wavelet Transform in power Quality: A Review },
journal = { International Journal of Computer Applications },
issue_date = { February 2012 },
volume = { 39 },
number = { 18 },
month = { February },
year = { 2012 },
issn = { 0975-8887 },
pages = { 30-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume39/number18/5081-7307/ },
doi = { 10.5120/5081-7307 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:26:48.127463+05:30
%A Suresh K.Gawre
%A N.P.Patidar
%A R. K. Nema
%T Application of wavelet Transform in power Quality: A Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 39
%N 18
%P 30-36
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

From last decades the objective of Power quality (PQ) monitoring and analysis has drastically. Generally the power quality problem covers the time scales range from tens of nanoseconds to steady state to describe different events. Well discussed in various international standards (IEEE, IEC, EN etc) and also give various acceptability curves to quantify and classify different Power Quality phenomenon (CIBMA and ITC) according to amplitude and time frame. It is observed that different tools and methods are always been used to detect and classify the power Quality events. The whole advance tends to process the raw data and extract the information in order to make decision. And further move towards real time monitoring, protection and control. This paper presents a comprehensive review of different techniques based on wavelet transform to detect and classify power quality problems.

References
  1. I. Daubechies, Ten Lectures on Wavelets. SIAM, Philadelphia, Pennsylvania, 1992
  2. C. Sidney Burrus Ramesh A. Gopinath and Haitao guo ‘Introduction to wavelet and wavelet transform’ Prentice Hall publication.
  3. Surya Santoso, Power quality assessment via wavelet transform analysis” IEEE transictions on power delevery,Vol 11, no.2, april 1996
  4. Surya Santoso, power quality disturbance data compression using wavelet, IEEE transictions on power delevery,Vol 12, no.3, July 1997
  5. Elmitwally, S. Farghal, M. Kandil, S. Abdelkader, and M. Elkateb, Proposed wavelet- neurofuzzy combined system for power quality violations detection and diagnosis, Proc. Inst. Elect. Eng., Gen., Transm.Distrib., vol. 148, no. 1, pp. 15–20, Jan. 2001
  6. A. M. Gouda, S. H. Kanoun, M. M. A. Salama, and Chikhani, Wavelet-based signal processing for disturbance classification and measurement, Proc. Inst. Elect. Eng.,Gen., Transm. Distrib., vol.149, no. 3, pp. 310–318, May 2002.
  7. T. K. Abdel-Galil, M. Kamel, A. M. Youssef, E. F. El-Saadany, and M. M. A. Salama, Power quality disturbance classification using the inductive inference approach, IEEE Trans. Power Del., vol. 19, no. 4, pp. 1812–1818, Oct. 2004.
  8. M. H. J. Bollen and I. Y. H. Gu, Signal Processing of Power Quality Disturbances. Piscataway, NJ: IEEE Press, 2006.
  9. U. D. Dwivedi and S. N. Singh, A robust energy features estimation for detection and classification of power quality disturbances, in Proc. IEEE Power Eng. Soc. Power India Conf., 2006, pp. 384–390.
  10. El sayed mohamed Tag eldin, Characterization of power quality disturbances based on wavelet transforms, int J. energy technology and policy, vol.4, nos1/ 2,.2006
  11. U. D. Dwivedi, S. N. Singh, and S. C. Srivastava, Analysis of transient disturbances in distribution systems: A hybrid approach, in Proc. IEEE Power Eng. Soc. General Meeting, 2007, pp. 1–8.
  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. IEEE power quality event characterization 1159.2, Feb. 2001.
  14. J. Barros and E. Perez, Automatic detection and analysis of voltage events in power systems, IEEE Transactions on Instrumentation and Measurement, vol. 55, no. 5, pp.1487-1493, Oct. 2006.
  15. Wen Ren Yang, Modeling of wavelet based voltage sag monitoring system and design for the mixed signal integrated circuit implementation, IEEE international conference industrial Tecc., ICIT 21-24 April 2008.
  16. Wei Liao, Hua Wang, Pu han, Neural network based detection and recognition method for power quality disturbance, Control and Decision Conference (CCDC), 2010 Chinese.
  17. A.M. Gaouda, Monitoring Nonstationary Signals, IEEE Recommended Prac for monitoring Elrctrical power Quality,1995
  18. U. D. Dwivedi, S. N. Singh, Denoising Techniques With Change-Point Approach for Wavelet-Based Power-Quality Monitoring, IEEE Trans. Power Del., vol -24, no. 3, July 2009.
  19. Algira, ”Power Quality Following Deregulation” proceedings of the IEEE, vol. 88, no. 2, february 2000
  20. Yang Hong-Tzer, and Liao Chiung-Chou, 2001. A de-noising scheme for enhancing wavelet-based power quality monitoring system, IEEE Trans on Power Delivery, vol. 16, no. 3, pp. 353 - 360.
  21. Kajihara H.H., 1968. “Quality power for electronics” Electro-Technology, vol.82, no.5.
  22. G. Strang and T. Nguyen” Wavelets and Filter Banks” Wellesley, MA: Wellesley Cambridge Press, 1996.
  23. C. K. Chui, An Introduction to Wavelets. New York: Academic, 1992.
  24. M. Misiti, Y. Misiti, G. Oppenheim, and J.-M. Poggi, “Wavelet toolbox for use with Matlab—User’s guide,” The MathWorks, Natick,MA,1997.
  25. M. P. Collins, W. G. Hurley, and E. Jones, The application of wavelet theory to power quality diagnostics,in Proc. 29th Univ. Power Eng.Conf., 1994, pp. 129–132.
  26. Y. Xu, X. Xiao,Y.Yang, and X. Chen, Application of wavelet transform in power quality analysis, Dianli Xitong Zidonghue/Automat. Electric Power Syst., vol. 23, no. 23, pp. 55–58, 1999.
  27. A. M. Gouda, M. M. A. Salama, M. R. Sultan, and A. Y. Chikhani, Application of multiresolution signal decomposition for monitoring short-duration variations in distribution systems, IEEE Trans. Power Delivery, vol. 15, pp. 478–485, Apr. 2000.
  28. Zhou Wenhui Li Qing Zhou Zhaojing, Power quality detection using wavelet-multiresolution signal decomposition, IEEE Trans. Power Delivery, vol. 14, pp. 1469–1476, Apr. 1999.
  29. A. M. Gaouda, M. M. A. Salama, A. Y. Chikhani, and M. R. Sultan, Application of wavelet analysis for monitoring dynamic performance in industrial plants, in Proc. North Amer. Power Symp., Laramie, WY,1997, pp. 325–331.
  30. P. Pillay and A. Bhattacharjee, Application of wavelets to model short term power system disturbances, IEEE Trans. Power Syst., vol. 11, pp.2031–2037, July 1996.
  31. J. Liu and P. Pillay, Application of wavelet analysis in power system disturbance modeling, in Proc. 5th IEEE AFRICON Conf., Cape Town,South Africa, 1999, pp. 639–642.
  32. U.D. Dwivedi, Deepti Shakya and SN Singh, Power Quality Monitoring and Analysis: An Overview and Key Issues, , International Journal of Systems Signal Control and Engineering Application, Vol., 1, No.1, 2008, pp. 74-88 ,
  33. G. T. Heydt and A. W. Galli, Transient power quality problems analyzed using wavelets, IEEE Trans. Power Delivery, vol. 12, pp.908–915, Apr. 1997.
  34. A. W. Galli, G. T. Heydt, and P. F. Ribeiro, Exploring the power of wavelet analysis, IEEE Comput. Appl. Power, vol. 9, pp. 37–41, Apr.1996.
  35. A.W. Galli and O. M. Nielsen, Wavelet analysis for power system transients, IEEE Comput. Appl. Power, vol. 12, pp. 16–25, Jan. 1999.
  36. O. Poisson, P. Rioual, and M. Meunier, New signal processing tools applied to power quality analysis, IEEE Trans. Power Delivery, vol.14, pp. 561–566, Apr. 1999.
  37. L. Agrisani, P. Daponte, M. D. Apuzzo, and A. Testa, “A measurement method based on the wavelet transform for power quality analysis,” IEEE Trans. Power Delivery, vol. 13, pp. 990–998, Aug. 1998.
  38. T. B. Littler and D. J. Morrow, Wavelets for the analysis and compression of power system disturbances, IEEE Trans. Power Delivery, vol.14, pp. 358–364, Apr. 1999.
  39. J. Chung, E. J. Powers, W. M. Grady, and S. C. Bhatt, Variable rate power disturbance signal compression using embedded zero tree wavelet transform coding, in Proc. IEEE Power Eng. Soc. Winter Meet., vol. 2,New York, NY, 1999, pp. 1305–1309.
  40. S. Santoso, E. J. Powers, and W. M. Grady, Power quality disturbance data compression using wavelet transform methods, IEEE Trans. Power Delivery, Vol. 12, pp. 1250–1257, June 1997.
  41. K. Mehta and B. D. Russell, Data compression for digital data from power systems disturbances: Requirements and technique evaluation,, IEEE Trans. Power Delivery, vol. 4, pp. 1683–1688, June 1989.
  42. R. P. Bingham, D. G. Kreiss, and S. Santoso, Advances in data reduction techniques for power quality instrumentation, in Proc. Third Eur. Power Quality Conf 1995.
  43. Information Technology Industry Council. ITIC Curve Application Note. [Online] http://www.itic.org/iss_pol/techdocs/curve.Pdf.
  44. Zwe-Lee Gaing “Wavelet-Based Neural Network for Power Disturbance Recognition and Classification” IEEE Transactions On Power Delivery, Vol. 19, No. 4, October 2004
  45. A.M. Gaouda, S.H. Kanoun, M.M.A. Salama and A.Y. Chikhani, Wavelet-based signal processing for disturbance classification and measurement, IEE Proc-Gener. Tr~instn. Distrib. Vol. 149, No. 3, May 2002
  46. Boris Bizjak, Peter Planinsic , Classification of Power Disturbances using Fuzzy Logic, Power Electronics and Motion Control Conference, EPE-PEMC,. 12th International 2006
  47. Wael R. Anis Ibrahim and Medhat M. Morcos, Artificial Intelligence and Advanced Mathematical Tools for Power Quality Applications: A Survey, IEEE Transactions On Power Delivery, Vol. 17, No. 2, April 2002
  48. Enrique Pérez, Voltage Event Detection and Characterization Methods: A Comparative Study, Transmission & Distribution Conference and Exposition: Latin America, 2006. TDC '06. IEEE/PES
  49. T.Lachman, A.P.Memon, T.R.Mohamad and Z.A.Memon ,Detection of Power Quality Disturbances Using Wavelet Transform Technique, International Journal For The Advancement Of Science & Arts, Vol. 1, No. 1, 2010
  50. Bousaleh G., Hassoun F., Ibrahim T. ,Application of Wavelet Transform in the Field of Electromagnetic Compatibility and power quality of Industrial Systems, International Conference on Advances in Computational Tools for Engineering Applications, 2009. ACTEA '09.
  51. M. Gaouda, S. H. Kanoun, M. M. A. Salama, and A. Y. Chikhani, Pattern Recognition Applications for Power System Disturbance Classification, IEEE Transactions On Power Delivery, Vol. 17, No. 3, July 2002
  52. Bahisham Yunus, Haiyu Li , Analysis of Power Quality Waveform for Data Transmission Efficiency over IEC 61850 Communication Standard, First International Power and Energy Conference PEC on November 28-29, 2006
  53. G. Panda, P. K. Dash, A. K. Pradhan, and S. K. Meher Data Compression of Power Quality Events Using the Slantlet Transform IEEE Transactions On Power Delivery, Vol. 17, No. 2, April 2002
  54. D. Saxena et al. Power quality event classification: an overview and key issues, International Journal of Engineering, Science and Technology Vol. 2, No. 3, 2010, pp. 186-199
  55. Enrique Pérez and Julio Barros. A Proposal for On-Line Detection and Classification of Voltage Events in Power System IEEE Transactions On Power Delivery, Vol. 23, No. 4, October 2008
  56. Julio Barros and Enrique Pérez, A Combined Wavelet – Kalman Filtering Scheme for Automatic Detection and Analysis of Voltage Dips in Power Systems, Power Tech IEEE Russia 27-30 June 2005
  57. A. M. Gaouda, A. H. El-Hag. And S. H. Jayaram Detection of Discharge Activities During Food Processing by Pulsed Electric Field , IEEE Transactions on Industry Applications 2008
  58. Surya Santoso and Edward J. Powers, Power Quality Disturbance Waveform Recognition Using Wavelet-Based Neural Classifier—Part 1: Theoretical Foundation, IEEE Transactions On Power Delivery, Vol. 15, No. 1, January 2000
  59. Surya Santoso, and Edward J. Powers Power Quality Disturbance Waveform Recognition Using Wavelet-Based Neural Classifier—Part 2: Application IEEE Transactions On Power Delivery, Vol. 15, No. 1, January 2000
  60. Surya Santoso, Characterization of Distribution Power Quality Events with Fourier and Wavelet Transforms, IEEE Transactions On Power Delivery, Vol. 15, No. 1, January 2000
  61. Surya Santoso, Electric Power Quality Disturbance Detection Using Wavelet Transform Analysis, International Symposium on Time-Frequency and Time-Scale Analysis, 1994., Proceedings of the IEEE-SP 1994
  62. A.M. Gaouda, S.H. Kanoun, M.M.A. Salama and A.Y. Chikhani ,Wavelet-based signal processing for disturbance classification and measurement, IEE Proc.-Gener. Trunsm. Distrib., Vol. 149. No. 3, May 2002
  63. Hong-Tzer Yang, and Chiung-Chou Liao, A De-Noising Scheme for Enhancing Wavelet-Based Power Quality Monitoring, System IEEE Transactions On Power Delivery, Vol. 16, No. 3, July 2001
  64. Valdomiro VEGA ,Automatic Power Quality Disturbance Classification Using Wavelet, Support Vector Machine And Artificial Neural Network, CIRED 20th International Conference on Electricity Distribution Praga, 8-11 June 2009
  65. F. B. Costa, , B. A. Souza, , and N. S. D. Brito, A Wavelet-Based Algorithm to Analyze Oscillographic Data with Single and Multiple Disturbances, Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, 2008 IEEE 2008
  66. N. Hamzah, Z. Zakaria A. Mohamed & A. Hussain, A Novel Software Tool For Power Quality Diagnosis, IEEE 8th International Conference on Computer and Information Technology Workshops. 8-11 July 2008
  67. B.K. Panigrahi V.R. Pandi, Optimal feature selection for classification of power quality disturbances using wavelet packet-based fuzzy k-nearest neighbour algorithm, IET Gener. Transm. Distrib., 2009, Vol. 3, Iss. 3, pp. 296–306
  68. Suriya Kaewarsa1et al. Wavelet-Based Intelligent System for Recognition of Power Quality Disturbance Signals, Lecture Notes in Computer Science, 2006, Volume 3972/2006, 1378-1385
Index Terms

Computer Science
Information Sciences

Keywords

Power quality wavelet transform De-noising multi-resolution adaptive filter A I Techniques

Powered by PhDFocusTM