Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33122
Detection and Classification of Power Quality Disturbances Using S-Transform and Wavelet Algorithm
Authors: Mohamed E. Salem Abozaed
Abstract:
Detection and classification of power quality (PQ) disturbances is an important consideration to electrical utilities and many industrial customers so that diagnosis and mitigation of such disturbance can be implemented quickly. S-transform algorithm and continuous wavelet transforms (CWT) are time-frequency algorithms, and both of them are powerful in detection and classification of PQ disturbances. This paper presents detection and classification of PQ disturbances using S-transform and CWT algorithms. The results of detection and classification, provides that S-transform is more accurate in detection and classification for most PQ disturbance than CWT algorithm, where as CWT algorithm more powerful in detection in some disturbances like notchingKeywords: CWT, Disturbances classification, Disturbances detection, Power quality, S-transform.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1083603
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2606References:
[1] T. Lin, and A. Domijan, "Real time Measurement of Power Disturbances Part 1. Survey and a Novel Complex Filter Approach", Electric Power Systems Research, Elsevier, Science Direct, 76, pp. 1027-1032. 2006.
[2] A. Moussa, M.El-Gammal, E. Abdallah, and A. El-SLoud, "Hardware - software structure for on-line power quality assessment", in Proc of the 2004 ASME/IEEE Joint, 2004, April 6-8, pp.147 - 152.
[3] R. G. Stockwell, L. Mansinha, and R. P. Lowe, "Localization of the Complex spectrum: The S-Transform", IEEE Trans. On Signal Processing, vol. 144, no. 4, pp. 998 - 1001. 1996.
[4] M. V. Chilukuri, and P. K. Dash, "Multiresolution S-Transform-Based Fuzzy Recognition System for Power Quality Events", IEEE Transactions on Power Delivery 19 1, pp. 323 - 330. 2004.
[5] Alexander D. Poularikas. 2000. The Transforms and applications Handbook, 2nd Ed. Boca Raton, Florida: CCR press LLC.
[6] I. W. C. Lee, and P. K. Dash, "S-Transform Based Intelligent System for Classification of Power Quality Disturbance Signals". IEEE Transactions on Power Delivery 18(2): 800-805. 2003.
[7] B. R. Jaya, K. Dusmanta and B. M. Karan, "Power System Disturbance Recognition Using Wavelet and S-Transform Techniques", International Journal of Emerging Electric Power Systems, 1(2). Article 1007. 2004.
[8] I. Daubechies, "The wavelet transforms, time-frequency localization and signal analysis", IEEE Transactions Information Theory 36(5): 961- 1005. 1990.
[9] R. G. Stockwell, "A basis for efficient representation of the Stransform", Journal of Digital Signal Processing, Elsevier INC: 371-393. 2006.
[10] M. E. Salem Abozaed, A. Mohamed and S. Abdul Samad, "Rule based system for power quality disturbance classification incorporating Stransform features" Expert Systems with Applications Journal, Elsevier, 37 (2010) 3229-3235.