Protection Scheme for Shunt Faults in Six-Phase Transmission System Based on Wavelet Transform and Support Vector Machine

The rising demand of electrical energy has put considerable stress on the existing network. In this regard, six-phase transmission system with the ability to transmit 73% more power has been proved to be a better alternative than the classical three phase transmission network and that too without any major modifications in the existing set-up. However, the protection protocol of six-phase transmission system is quite complex, due to the larger number of possible faults. In this context, this paper presents a protection scheme based on combined framework of discrete wavelet transform (DWT) and support vector machine (SVM). The approach aims at performing the tasks of detection and classification of shunt faults in six-phase transmission system. The use SVM is motivated by the fact that it has emerged as an efficient, powerful and fast machine learning tool for finding solution to the complex classification problems. The effectiveness of the proposed scheme have been examined for wide variation in fault parameters such as fault location, fault resistance and inception angle. The test results reveal the effectiveness of the proposed scheme in providing information regarding the system status and immunity to parameter perturbations.