Cover
Vol. 12 No. 1 (2012)

Published: July 31, 2012

Pages: 134-142

Original Article

Wavelet Packet Transform Based Power Quality Analysis

Adel A. OBED 1
1 Electrical Department, College of Engineering, Basrah University.
History
  • Received: April 30, 2012
  • Available Online: July 31, 2012
DOI

https://doi.org/10.33971/bjes.12.1.11

Abstract

This paper presents a diagnostic technique for power quality analysis against different disturbances in electrical power source. The presented technique utilizes a wavelet packet transform (WPT)-based a proposed algorithm for monitoring and detection various disturbances occurring in supply voltage signal and in supply frequency. The values and the time locations for low and high frequency coefficients are determined up to level six and compared with a threshold determined from the operation of healthy source. The proposed technique is tested on certain cases and the simulated results indicate that this technique is effective for detecting and monitoring different mentioned disturbances.

Keywords

References

  1. L. Lin, N. Huang, and W. Huang, “Review of Power Quality Signal Compression Based on Wavelet Theory” IEEE Conference on Test and Measurement, PP 235-238, 2009.
  2. M. A. S. K. Khan, T. S. Radwan and M. A. Rahman, “Real Time Implementation of Wavelet Packet Transform Based Diagnosis and Protection of Three-Phase Induction Motors” IEEE Trans. Energy Conversion, Vol. 22, No. 3, Sep., 2007.
  3. P. K. Dash, B. K. Panigrahi and G. Panda, “Power Quality Analysis Using S-Transform” IEEE Trans. Power Delivery, Vol. 18, No. 2, PP. 406-411, 2003.
  4. L. Shangwel and S. Yaming, “Study on the Classification Method of Power Disturbances Based on the Combination of S Transform and SVM Multi-Class Classifier with Binary Tree”, 3rd International Conference on Electric Utility Deregulation and Restructuring and Power Technologies, PP. 2275-2280, 2008.
  5. Y. Jia, Z. Y. He and T. L. Zang, “S-Transform Based Power Quality Indices for Transient Disturbances”, IEEE conference on Power and Energy Engineering, Asia-Pacific, PP. 1-4, 2010.
  6. N. Huang, W. Huang, L. Lin and J. Qi, “Review of Power-Quality Disturbance Recognition Using S-transform” IEEE IITA International Conference on Control, Automation and Systems Engineering, PP. 438-441, 2009.
  7. Z. Wen-yuan, “The Detection of Power Quality Hybrid Disturbance Based on S Transform” IEEE Conference on Power and Energy Engineering, Asia-Pacific, PP. 1-4, 2010.
  8. W. Wen-jun, F. Jian-hua and L. Wan-shan, “The Application of WPT in Compress Power Quality Disturbance” IEEE Conference on Control and Decision, Chinese, PP. 384-387, 2010.
  9. L. L. Lai, W. L. Chan, C. T. Tse and A. T. P So, “Real-time Frequency and Harmonic Evaluation Using Artificial Neural Network”, IEEE Trans. On Power Delivery, Vol. 14, No. 1, PP. 52-59, 1999.
  10. W. L. Chan, A. T. P. So and L. L. Lai, “Harmonics Load Signature Recognition by Wavelet Transform”, International Conference on Electric Utility Deregulation Restructuring and Power Technologies DRPT2000, IEEE, PP. 666-671, 2000.
  11. A. Elmitwaly, 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. Trans. Dist., Vol. 148, No. 1, PP. 15-20, 2001.
  12. N. C. F. Tse., “Practical Application of Wavelet to Power Quality Analysis”, IEEE Power Engineering Society General Meeting, 2006.
  13. G. Strang and T. Nguyen, “Wavelet and Filter Banks” Wellesley, MA: Wellesley-Cambridge, 1996.
  14. MathWorks, Matlab, “Wavelet Toolbox, Ver. 2.0.”