Series Compensated Line Protection Using Support Vector Machine

Recently, series compensation is widely used in transmission. However, this creates several problems to conventional protection approaches.This book presents a comprehensive distance and overcurrent protection approach for series compensated transmission line using support vector machine (SVM).SVM is considered as a new powerful Artificial Intelligence (AI) technique. In a short period of time, SVM has been applied to numerous applications such as transformer faultdiagnosis, power system disturbances, relay coordination, transient stability of power system and fault classification of transmission line. This is due to the advantages of SVM over traditional approaches. The SVMs are trained with different kernel functions with different parameter values to get the most optimized model. Simulation studies have been considered for different operating conditions, including wide variations of load angle, fault inception angle, fault resistance and fault location.In addition to series compensated transmission line protection studies, the book also includes fault analysis of high voltage transmission linewithout compensation.

(S'11)He received B.Sc.(Hons) and M.Sc. in Electrical Engineering from Ain Shams University, Faculty of Engineering in 2007 and 2011 respectively.He is currently working towards the PhD degree in University of Toronto. He has authored many journal and conference papers.His area of research includes intelligent techniques to power system protection.