Fault classification in power systems using EMD and SVM

• Main Authors: N. Ramesh Babu, B. Jagan Mohan
• Format: Article
• Language: English
• Published: Elsevier 2017-06-01
• Series: Ain Shams Engineering Journal
• Subjects: Fault classification; Empirical Mode Decomposition (EMD); Support Vector Machines (SVMs)
• Online Access: http://www.sciencedirect.com/science/article/pii/S2090447915001306

In recent years, power quality has become the main concern in power system engineering. Classification of power system faults is the first stage for improving power quality and ensuring the system protection. For this purpose a robust classifier is necessary. In this paper, classification of power system faults using Empirical Mode Decomposition (EMD) and Support Vector Machines (SVMs) is proposed. EMD is used for decomposing voltages of transmission line into Intrinsic Mode Functions (IMFs). Hilbert Huang Transform (HHT) is used for extracting characteristic features from IMFs. A multiple SVM model is introduced for classifying the fault condition among ten power system faults. Algorithm is validated using MATLAB/SIMULINK environment. Results demonstrate that the combination of EMD and SVM can be an efficient classifier with acceptable levels of accuracy.