Analysis of Power Quality Disturbances Using Spectrogram and S-transform


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Abstract


The performance analysis of spectrogram and S-transform for power quality disturbances such as swell, sag, interruption, harmonic, inter-harmonic, and transient based on IEEE Std 1159-2009 are presented. These analyses are performed to identify the best performance for detection of power quality disturbances. This is important to provide the improvement of power quality which capable to accurately measured, detect the power quality phenomena. Therefore the accurate detection of power quality disturbances can be developed based on the best techniques. By using both techniques, the temporal and spectral information are obtained. From the time frequency representation (TFR) the signal parameters are estimated such as instantaneous root means square voltage (RMS), total waveform distortion (TWD), total harmonic distortion (THD) and total non harmonic distortion (TnHD).The signal characteristics are calculated from signal parameters to verify the performances of both techniques, the APE results are used to identify the accuracy of these techniques. By perform the analysis; the result show the S-transform is a better tool to analyze the transient disturbances whereas for voltage variation and harmonic disturbances the spectrogram gives higher accuracy result. As a conclusion both techniques are capable to analyzed power quality disturbances, and it clearly shows that, the S-transform has an advantages in term of time-frequency resolution which capable to detect and localized various kind of power quality disturbances and it essential for the development of advanced real-time monitoring. 


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Keywords


Power Quality, S-Transform, Time Frequency, Spectrogram, Resolution

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References


Suresh Kumar, V., Ramela, K.R., Zobaa, A.F., A cuk converter to improve the ride-through capability of low power adjustable speed drives for voltage sag and swell, (2013) International Review of Electrical Engineering (IREE), 8 (4), pp. 1302-1310.

K. Oyedoja, Obiyemi,Obiseye, "Wavelet Transform in The Detection of Electrical Power Quality Disturbances," International Journal of Engineering and Applied Sciences, 2012.

C. M. GHEORGHE Daniel, CZIKER Andrei, VASILIU Răzvan, "Virtual Instrument for Power Quality Assesment " Journal of Sustainable Energy 2012.

D. Mishra, "Sag, Swell and Interruption Detection Using Wavelet in LabVIEW," International Journal of Computer & Electrical Engineering, vol. 5, 2013.

A. F. A. K. Daud, N. Hamzah, H. S. Nagindar Singh, "New Windowing Technique Detection of Sags and Swells Based on Continuous S-transform (CST) " International Journal of New Computer Architectures and their Applications 2012.

R. S. Latha, C. S. Babu, and K. D. S. Prasad, "Detection & analysis of power quality disturbances using wavelet transforms and SVM," 2011.

Z. Leonowicz, T. Lobos, and K. Wozniak, "Analysis of non-stationary electric signals using the S-transform," COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, vol. 28, pp. 204-210, 2009.

S. E. A.Arabi Parizi , S.Hasheminejad, "Power Quality Disturbance Classification Using S-transform and Fuzzy System Oriented By PSO Algorithm," International Journal on Technical and Physical Problems of Engineering, 2012.

Hapeez, M.S., Hamzah, N.R., Hashim, H., Abidin, A.F., A new approach of wavelet De-Noising on various types of acoustic emission partial discharges signals, (2013) International Review of Electrical Engineering (IREE), 8 (3), pp. 1133-1141.

Yong, P., Linna, H., Lifang, W., Application of wavelet entropy and RBF technique based on initial current travelling wave for transmission line protection, (2013) International Review of Electrical Engineering (IREE), 8 (5), pp. 1616-1623.

Adewole, A.C., Tzoneva, R., Distribution network fault detection and diagnosis using wavelet energy spectrum entropy and neural networks, (2014) International Review of Electrical Engineering (IREE), 9 (1), pp. 165-173.

A. H. Alex Wenda , M.A Hannan , Azah Mohamed , Salina Abdul Samad, "Web Based Automatic Classification of Power Quality Disturbances Using S-transform and Rule Based Expert System," Journal of Information & Computational Science, 2011.

H. S. Li Jiasheng, Xiao Weichu and Qiu Biao, "The Application Study of S-transform Modulus Time Frequency Matrix in Detecting Power Quality Transient Disturbances," Information Technology Journal, vol. 11, pp. 354-358, 2012.

"IEEE Recommended Practice for Monitoring Electric Power Quality," IEEE Std 1159-2009 (Revision of IEEE Std 1159-1995), pp. c1-81, 2009.

A. R. Abdullah, A. Z. Sha''ameri, and N. M. Saad, "Power quality analysis using spectrogram and gabor transformation," in Applied Electromagnetics, 2007. APACE 2007. Asia-Pacific Conference on, 2007, pp. 1-5.

A. R. Abdullah and A. Z. Sha''ameri, "Power quality analysis using linear time-frequency distribution," in Power and Energy Conference, 2008. PECon 2008. IEEE 2nd International, 2008, pp. 313-317.

N. H. T. Huda, A. R. Abdullah, and M. H. Jopri, "Power quality signals detection using S-transform," in Power Engineering and Optimization Conference (PEOCO), 2013 IEEE 7th International, 2013, pp. 552-557.

R. G. Stockwell, "A basis for efficient representation of the S-transform," Digital Signal Processing, vol. 17, pp. 371-393, 2007.


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