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DSP-FPGA beads real-time power quality disturbances classifier

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper describes a real-time classification method of power quality (PQ) disturbances based on DSP-FPGA. The proposed method simultaneously uses the results obtained in the application of a series of RMS values and the discrete Fourier transform to the power signal waveform. A series of RMS values are used for estimation of the time-related parameters of the PQ disturbances and the discrete Fourier transform is used for confirmation of the frequency-related parameters of the PQ disturbances. Without adding the computational burden, both the elementary parameters of the power signal and the type of PQ disturbance are obtained easily. A simple and effective methodology for classification of nine typical kinds of PQ disturbances is proposed in this paper. Five distinguished time-frequency statistical features of each type of PQ disturbances are extracted. Using a rule-based decision tree (RBDT), the PQ disturbances pattern can be recognized easily and there is no need to use other complicated classifiers. Finally, the method is also tested using both simulated disturbances and disturbances measured using an initial development instrument. Different experimental results show the good performance of this proposed approach. Real-time calculating time based on DSP is also taken into consideration to show the effectiveness of the proposed method.
Rocznik
Strony
205--215
Opis fizyczny
Bibliogr. 20 poz., rys., tab., wykr.
Twórcy
autor
autor
autor
  • Huazhong University of Science and Technology, Department of Electrical and Electronic Engineering, Wuhan 430074, Hubei Province, China, zmcock@yahoo.com.cn
Bibliografia
  • [1] IEEE Recommended Practice for Monitoring Electric Power Quality, IEEE Std. 1159-1995, 1995.
  • [2] M. Kezunovic, Y. Liao: “A new method for classification and characterization of voltage sags”. Elect. Power Syst. Res., vol. 58, no. 1, 2001, pp. 27-35.
  • [3] M. Kezunovic, L. Yuan: “A novel software implementation concept for power quality study.” IEEE Trans. Power Del., vol. 17, no. 2, 2002, pp. 544-549.
  • [4] T.K. Abdel-Galil, M. Kamel, A.M. Youssef, E.F. El-Saadany, M.M.A. Salama: “Power quality disturbance classification using the inductive inference approach. IEEE Trans. Power Del., vol. 19, no. 4, 2004, pp. 1812-1818.
  • [5] S. Santoso, E.J. Powers, W.M. Grady, P. Hofmann: “Power quality assessment via wavelet transform analysis”. IEEE Trans. Power Del., vol. 11, no. 2, 1996, pp. 924-930.
  • [6] S.-J. Huang, C.-T. Hsieh, C.-L. Huang: “Application of wavelets to classify power system disturbances”. Elect. Power Syst. Res., vol. 47, no. 2, 1998, pp. 87-93.
  • [7] A.M. Gaouda, M.M.A. Salama, M.R. Sultan, A.Y. Chikhani: “Power quality detection and classification using wavelet-multiresolution signal decomposition.” IEEE Trans. Power Del., vol. 14, no. 4, 1999, pp. 1469-1476.
  • [8] I. Monedero, C. León, J. Ropero, A.García, J.M. Elena, J.C. Montaño: “Classification of electrical disturbances in real time using neural networks”. IEEE Trans. Power Del., vol. 18, no. 2, 2003, pp. 406-1296.
  • [9] S. Emmanouil, M.H.J. Bollen, I.Y.H. Gu: “Expert system for classification and analysis of power system events”. IEEE Trans. Power Del., vol. 17, no. 2, 2002, pp. 423-428.
  • [10] P.K. Dash, K.S. Mishra, M.M.A. Salama: “Classification of power system disturbances using a fuzzy expert system and a Fourier linear combiner”. IEEE Trans. Power Del., vol. 15, no. 2, 2000, pp. 472-477.
  • [11] P. Janik, T. Lobos: “Automated classification of power-quality disturbances using SVM and RBF networks.” IEEE Trans. Power Del., vol. 21, no. 3, 2006, pp. 1663-1669.
  • [12] J. Chung, E.J. Powers, W.M. Grady, S.C. Bhatt: “Power disturbance classifier using a rule-based method and wavelet packet-based hidden Markov model”. IEEE Trans. Power Del., vol. 17, no. 1, 2002, pp. 233-241.
  • [13] J.R. Quinlan: “Induction of decision trees”. Machine Learning, vol. 1, 1986, pp. 81-106.
  • [14] O. Martens, H. Trampark, A. Liimets, P. Nobel, A. Veskimester, A. Jarvalt: “DSP-based power-quality monitoring device”. Proc. WISP, Oct. 2007, pp. 1-5.
  • [15] D. Gallo, C. Landi, N. Rignano: “DSP based instrument for real-time PQ analysis”. Proc. ISIE, Jun. 2007, pp. 2481-2486.
  • [16] M. Karimi, H.Mokthari, M.R. Iravani: “Wavelet based on line disturbance detection for power quality applications.” IEEE Trans. Power Del., vol. 15, no. 4, 2000, pp. 1212-1220.
  • [17] E. Pérez, J. Barros: “A proposal for on-Line detection and classification of voltage events in power systems”. IEEE Trans. Power Del., vol. 23, no. 4, 2008, pp. 2132-2138.
  • [18] E. Styvaktakis, M.H.J. Bollen, I.Y.H. Gu: “Automatic classification of power system events using RMS voltage measurements”. Proc. IEEE Power Engineering Society Summer Meeting, 2002, pp. 824-829.
  • [19] G.T. Heydt , P.S. Fjeld , C.C. Liu, D. Pierce, L. Tu, G. Hensley: “Applications of the Windowed FFT to Electric Power Quality Assessment”. IEEE Trans. Power Del., 1999, vol. 14, no. 4, 1999, pp. 1411-1416.
  • [20] IEEE Recommended Practices and Requirements for Harmonic Control in Electrical Power Systems. IEEE Std. 519-1992, 1992.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BSW1-0065-0006
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