Detection of Sags, Swells, and Transients Using Windowing Technique Based On Continuous S-Transform (CST)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33104
Detection of Sags, Swells, and Transients Using Windowing Technique Based On Continuous S-Transform (CST)

Authors: K. Daud, A. F. Abidin, N. Hamzah, H. S. Nagindar Singh

Abstract:

This paper produces a new approach for power quality analysis using a windowing technique based on Continuous S-transform (CST). This half-cycle window technique approach can detect almost correctly for initial detection of disturbances i.e. voltage sags, swells, and transients. Samples in half cycle window has been analyzed based continuous S-transform for entire disturbance waveform. The modified parameter has been produced by MATLAB programming m-file based on continuous s-transform. CST has better time frequency and localization property than traditional and also has ability to detect the disturbance under noisy condition correctly. The excellent time-frequency resolution characteristic of the CST makes it the most an attractive candidate for analysis of power system disturbances signals.

Keywords: Power quality disturbances, initial detection, half cycle windowing, continuous S-transform.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1335948

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2049

References:


[1] A. Moussa, M. el-Gammal, E. Abdallah, and A. El-SLoud, "Hardware-software structure for on-line power quality assessment”, in proceedings of the 2004 ASME/IEEE Joint,pp 147-152, (2004).
[2] S. Mishra, C. N. Bhende, and B. K. Panigrahi, "Detection and classification of power quality disturbance using s-transform and probabilistics neural network”, IEEE Trans. Power Delivery, vol.23, no.1, pp. 280-287, (2008).
[3] L. Mansinha, R. G. Stockwell, R. P. lowe, M. Eramian, and R. A. Schincariol, "Local s-spectrum anaysis of 1-D and 2-D data,” Physics of the Earth and Planetary Interiors, vol.103,pp.329-336, (1997).
[4] M. V. Chilukuri and P. K. Dash, "Multiresolution S-transform-based fuzzy recognition system for power quality events”, IEEE Trans. Power Del., vol.19(1), pp. 323-330, (2004).
[5] S. Kaerwarsa, "Classification of power quality disturbances using s-transform based artificial neural networks”, IEEE International Conf. of Intelligent Computing and Intelligent systems, pp.566-570, (2009).
[6] P.K. Dash, B.K. Panigrahi, and G.Panda, "Power quality analysis using S-transform”, IEEE Trans. On Power Delivery, vol. 18(2), pp. 406-411, (2003).
[7] R.G. Stockwell, L.Mansinha, and R.P. Lowe, "Localization of the complex spectrum: The S-transform,” IEEE Trans. Signal Processing vol.44, no.4, pp.998-1001, (1996).
[8] V. Matz, T. Radil, P. Ramos and A.Cruz Serra, "Automated power quality monitoring system for on-line detection and classification of disturbances”, IEEE Conf. Proceedings of Instrumentation and Measurement Technology (IMTC2007), pp.1-6, (2007).
[9] U. N. Khan, "Signal processing used in power quality monitoring”, Conf. Proceedings of the International Conference on Environment and Electrical Engineering, pp. 1-4, (2009).
[10] M. Nayak, B.S. Panigrahi, "Advanced signal processing technique for feature extraction in data mining,” International Journal of Computer applications, vol.19, no.9, pp.30-37, (2011).
[11] M.F. Faisal, and A. Mohamed, "Identification of sources of voltage sags in the Malaysian distribution networks using SVM based s-transform,” IEEE Region 10 Conference, (2009).
[12] T.Y. Vega, V. F. Roig, and H. B. San Segundo, "Evolution of signal processing techniques in power quality”, International Conf. on Electrical Power Quality and Utilisation, pp. 1-5, (2007).
[13] N. Huang, L. Lin, W. Huang, and J. Qi, "Review of power quality disturbance recognition using s-transform”, International Conf. on Control, Automation and Systems Engineering, pp.438-441, (2009).
[14] K. Daud, A. F. Abidin, N. Hamzah, and H. S. N. Singh, "New windowing technique detection of sags and swells based on continuous s-transform (CST)”, International Journal of New Computer Architectures and their Applications (IJNCAA), 2(4),pp. 550-555, (2012).