Measurement and Classification of Power Quality Disturbances Using Wavelet Based Neural Network

S. Deb*, S. Patra**
* PG Student, Department of Electrical Engineering, Birla Institute of Technology, Mesra, India.
** Associate Professor, Department of Electrical Engineering, Assam Engineering College, Guwahati, India.
Periodicity:November - January'2016
DOI : https://doi.org/10.26634/jps.3.4.4801

Abstract

This paper presents an approach for measuring and classifying power quality disturbances using discrete wavelet transform and artificial neural network. The various power quality events are considered they are voltage sag, swell, harmonics, sag with harmonics, swell with harmonics and interruption. Due to the power quality disturbances, the signal is distorted. The energy of the distorted signal is first evaluated with the help of the Multi-Resolution Analysis (MRA) technique of Discrete Wavelet Transform (DWT) and the Parseval's theorem. Second, the energy deviation of the distorted signal with respect to pure sinusoidal signal is at different levels calculated. From these energy features and transient duration the artificial neural network classifies and identifies the disturbances.

Keywords

Voltage Sag, Swell, Power Quality, Wavelet Transform, Discrete Wavelet Transform, Multi Resolution Analysis, Detail and Approximate Wavelet Co-Efficient, Artificial Neural Network.

How to Cite this Article?

Deb, S., and Patra, S. (2016). Measurement and Classification of Power Quality Disturbances Using Wavelet Based Neural Network. i-manager’s Journal on Power Systems Engineering, 3(4), 12-17. https://doi.org/10.26634/jps.3.4.4801

References

[1]. M.P. Collins, W.G. Hurley, and E. Jones, (1994). “The application of wavelet theor y to power quality diagnostics”. in Proc. of Universities Power Engineering Conf (UPEC).
[2]. Santoso, S, Power, E. J., and W M. Hofmann, (1996). “Power quality assessment via wavelet transform”. IEEE Transaction on Power Delivery, Vol.11, No.2.
[3]. P. Pillary, P. Ribeiro, and Q. Pan, (1996). “Power quality modeling using wavelets”. in Proc. of the 1996 IEEE Int. Conf on Harmonics and Quality of Power, Las Vegas, NV, USA.
[4]. N.S. Tunaboylu, and E.R. Collins, (1996). “The wavelet transform approach to detect and quantify voltage sags”, in Proc. of the 1996 IEEE Int. Conf on Harmonics and Quality of Power, Las Vegas, NV, USA.
[5]. S. Santoso, E.J. Powers, and W.M. Grady, (1996). “Power quality disturbance identification using wavelet transforms and artificial neural networks”. in Proc. of the 1996 IEEE Int. Conf on Harmonics and Quality of Power, Las Vegas, NV, USA.
[6]. L. Angrisani, P. Daponte, M. D'Apuzzo, and A. Testa, (1996). “A new wavelet transform based procedure for electrical power quality analysis”. in Proc. of the 1996 IEEE Int. Conf on Harmonics and Quality of Power, Las Vegas, NV, USA.
[7]. Ali Abur and Mladen Kezunovic, (1999). “A simulation and testing laboratory for addressing power quality issues in power system”. IEEE Transaction on Power System, Vol.14, No.1.
[8]. O. Poisson, P. Rioual and M. Meunier, (2000). “Detection and measurement of power quality disturbances using wavelet transform”. IEEE Trans. Power Delivery, Vol.15, No.3.
[9]. J.L.J. Driesen and R. J.M. Belmans, (2003). “Wavelet based power quantification approaches”. IEEE Trans. Power Delivery, Vol.52, No.4.
[10]. S. Mishra, C.N. Bhende and B.K. Panigrahi, (2008). “Detection and classification of power quality disturbances using S transform and probabilistic neural network”. IEEE Trans. Power Delivery, Vol.23, No.1.
[11]. N. Karthik, Shaik Abdul Gafoor, and M. Surya Kalavathi, (2011). “Classification of Power quality problems by wavelet Fuzzy expert system”. International Journal of Advances in Engineering Sciences, Vol.1, No. 3.
[12]. Subhamita Roy, and Sudipta Nath, (2012). “Classification of Power Quality Disturbances using Features of Signals”. International Journal of Scientific and Research Publications, Vol.2, No.11.
[13]. Resende, J. W., Chaves, M. L. R., and Penna, C., (2001). “Identification of power quality disturbances using the MATLAB wavelet transform toolbox”. in Proc. of the 2001 International Conference on Power System Transients.
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