Discrimination of Internal Fault Current and Inrush Current in a Power Transformer Using Empirical Wavelet Transform

Transformers are crucial equipment in a power system, which require reliable solutions for their protection to ensure smooth operation. Identification between internal fault current and in rush current is a challenging problem in the design of transformer protection relay. Transformers are often tripped when inrush current flows in the system causing problems in operation and maintenance in addition to the customer disturbance. Conventional identification methods have limitations in providing accurate solution to this problem. This work investigates the scope of a classification method based on EWT and SVM in distinguishing internal fault current and inrush current in a power transformer. Validation of this method is done using generated synthetic data from MATLAB/SIMULINK. Feature extraction of the generated data is done using EWT algorithm. These features are used for training SVM. Later, accuracy of classification is checked using test vectors. Different kernel functions for SVM are also tested for improved accuracy.