Research on the Power System Fault Classification Based on HHT and SVM Using Wide-area Information

DOI: 10.4236/epe.2013.54B026   PDF   HTML     3,874 Downloads   5,023 Views   Citations


A power system fault classification method based on the Hilbert-Huang transformation (HHT) and support vector machine (SVM) is proposed in this paper. According to different types of faults taking place in area and the outer area, this paper uses HHT to extract the instantaneous amplitude and Hilbert marginal spectrum of the current signal. Then a fault classifier consisting of a series of SVM classifiers that are optimized by using cross validation method is constructed. Finally, inputting the feature vector sets that are conversed by the HHT into the fault classifier, the fault type and locate the fault area will be distinguished. The simulation results show that this approach is very effective to classify the fault type especially when the sample is small.

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Y. Guo, C. Li, Y. Li and S. Gao, "Research on the Power System Fault Classification Based on HHT and SVM Using Wide-area Information," Energy and Power Engineering, Vol. 5 No. 4B, 2013, pp. 138-142. doi: 10.4236/epe.2013.54B026.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] X. Z. Yi and X. Q. Li, “Diagnosis of Power Supply Line Fault Based on Wavelet Analysis and Support Vector Machine,” Journal of Beijing institute of Petro-chemical Technology, Vol. 13, No. 3, 2005, pp. 36-40.
[2] Y. H. Liu, Y. Y. Wang and Z. H. Song, “Adaptive Fault Feature Extraction Based on Stationary Wavelet Packet Decomposition and Hilbert Transform,” Transacions of China Electrotechnical Society, Vol. 24, No. 2, 2009, pp. 145-149.
[3] X. L. Zhang, X. J. Zeng, H. J. Ma, et al., “Power Grid Faults Location with Traveling Wave Based on Hilbert-Huang Transform,” Automation of electric power systems, Vol. 32, No. 8, 2008, pp. 64-67
[4] S. Han, L. Q. He, B. Sun, et al., “Hilbert-Huang Transform Based Nonlinear and Non-Stationary Analysis of Power System Low Frequency Oscillation and Its Application,” Power System Technology, Vol. 32, No. 4, 2008, pp. 56-60.
[5] Y. X. Su, Z. G. Liu, K. L. Li, et al., “Application of Hilbert-Huang Transform in Harmonic Detection of Electrified Railway,” Power System Technology, Vol. 32, No. 18, 2008, pp. 30-35
[6] Z. J. Kang, L. Xu, J. C. Fan, et al., “Fault Location for High Voltage Transmission Lines With the Series Compensation Capacitor Based on Hilbert-Huang Transform and Neural Network,” Power System Technology, Vol. 33, No. 20, 2009, pp. 142-146
[7] J. Manikandan and B. Venkataramani, “Design of a Modified One-against-all SVM Classifier,” Proceedings of the 2009 IEEE International Conference on Systems, man, and cybernetics, 2009, pp. 1869-1874
[8] D. C. Yang, C. Rehtanz, Y. Li, W. Tang and R. Q. Qu, “Researching on Low Frequency Oscillation in Power System Based on Improved HHT Algorithm,” Proceedings of the CSEE, Vol. 31, No.10, 2011, pp.102-108.
[9] H. Jiang, X. Q. Wang and J. C. Peng, “Method to Measure Voltage Flicker Based on Hilbert-Huang Transform,” Power System Technology, Vol. 35, No. 9, 2012, pp. 250-256.
[10] Q. Zhang and Y. Q. Yang, “Research of the Kernel Fuction of Support Vector Machine,” Electric Power Science and Engineering, Vol. 28, No. 5, 2012, pp. 42-45.
[11] T. Y. Li, C. L. Chen, W. L. Cheng, et al., “Application of cross Validation in Power Quality Denoisin,” Automation of Electric Power Systems, Vol. 319, No. 16, 2007, pp. 75-78.
[12] J. Ma, X.Wang and Z. P. Wang, “A New Fault Phase Identification Method Based on Phase Current Difference,” Proceedings of the CSEE, Vol. 31, No. 10, 2011, pp. 102-108
[13] Y. Wang, Y. X. Zhang and S. X. Xu, “Fault Location and Phase Selection for Parallel Transmission Lines Based on Wide Area Measurement System,” Automation of Electric Power Systems, Vol. 34, No. 6, 2010, pp. 65-69.

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