Detection and Classification of Power Quality Disturbances Using S-Transform and Wavelet Algorithm
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 notching
[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.
[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.
@article{"International Journal of Electrical, Electronic and Communication Sciences:63776", author = "Mohamed E. Salem Abozaed", title = "Detection and Classification of Power Quality Disturbances Using S-Transform and Wavelet Algorithm", 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 notching", keywords = "CWT, Disturbances classification, Disturbances detection, Power quality, S-transform.", volume = "7", number = "6", pages = "775-6", }