Application of pattern recognition method in classifying power system transient disturbance

Power system transient can cause serious damage to main power system apparatus and sensitive loads. There are many causes of power system transient including capacitor bank switching, switching of large inductive loads and lightning. This paper discusses the application of pattern recognition method, namely Support Vector Machine (SVM) to classify the cause of transient disturbance in power system. Two types of feature extractions are applied to provide the inputs to the SVM, i.e. the minimum and maximum peak voltage values and the wavelet energy level of the transients. The IEEE 30 bus system is modeled using the Power System Computer Aided Design (PSCAD) software to generate different type of transient data caused by capacitor switching and lightning. Feature extraction is performed using discrete wavelet transform (DWT) analysis. The results showed that the performance of the feature extraction using maximum and minimum peak voltage values is superior (80%) as compared to the wavelet energy (54%) to classify the cause of the transient.

[1]  Sami Ekici,et al.  Classification of power system disturbances using support vector machines , 2009, Expert Syst. Appl..

[2]  M. Samotyj,et al.  Impact of utility switched capacitors on customer systems. II. Adjustable-speed drive concerns , 1991 .

[3]  Shiun Chen,et al.  Wavelet Transform for Processing Power Quality Disturbances , 2007, EURASIP J. Adv. Signal Process..

[4]  T. Lobos,et al.  Automated classification of power-quality disturbances using SVM and RBF networks , 2006, IEEE Transactions on Power Delivery.

[5]  Zhen Ren,et al.  Power quality disturbance identification using wavelet packet energy entropy and weighted support vector machines , 2008, Expert Syst. Appl..

[6]  Sheng-Wu Xiong,et al.  Support vector machines based on subtractive clustering , 2005, 2005 International Conference on Machine Learning and Cybernetics.

[7]  J. W. Resende,et al.  Identification of power quality disturbances using the MATLAB wavelet transform toolbox , 2001 .

[8]  Weiming Tong,et al.  Detection and Classification of Power Quality Disturbances Based on Wavelet Packet Decomposition and Support Vector Machines , 2006, 2006 8th international Conference on Signal Processing.

[9]  V. M. Reddy,et al.  On the use of wavelets for the detection and analysis of power system transients , 1999, IEEE Power Engineering Society. 1999 Winter Meeting (Cat. No.99CH36233).

[10]  V. E. Wagner,et al.  Utility capacitor switching and adjustable-speed drives , 1991 .

[11]  Wilsun Xu,et al.  Method for voltage-sag-source detection by investigating slope of the system trajectory , 2003 .