Support vector machine based fault section identification and fault classification scheme in six phase transmission line

A Naresh kumar (Institute of Aeronautical Engineering)
M Suresh Kumar (Sandip University)
M Ramesha (GITAM (Deemed to be University))
Bharathi Gururaj (ACS College of Engineering)
A Srikanth (Institute of Aeronautical Engineering)

IAES International Journal of Artificial Intelligence (IJ-AI)
Vol 10, No 4: December 2021

The higher complexity of a six phase transmission system (SPTS) construction and the large number of possible faults makes the protection task challenging. Moreover, the reverse & forward path faults in SPTS cannot be detected by traditional relay as it becomes under-reach. In this paper, a support vector machine (SVM) method including Haar wavelets for SPTS fault section identification and fault classification is focused. The positive-sequence component phase angle and currents at middle two buses are used to formulate a suggested method. Feasibility of suggested SVM is tested with a 138 kV, 300 km, 60 Hz, SPTS in MATLAB based Simulink platform. Several major parameters including far end and near end location conditions are taken to investigate the reach setting and accuracy of proposed SVM. This relaying method can detect the existence of fault in reverse & forward path in 1 ms time.