Improved fault location algorithm for multi‐location faults, transforming faults and shunt faults in thyristor controlled series capacitor compensated transmission line

Abstract

Fault location estimation in series compensated transmission lines is quite difficult because a non-linear current dependent circuit appears between the substation and fault point. In particular, the faults which occur at different locations at the same time in different phases known as multi-location faults has not been addressed by researchers. Other types of fault that may occur in transmission lines are transforming faults where one type of fault transforms to another type fault after some time. In this study, a fault location estimation scheme using artificial neural network (ANN) is presented for multi-location faults, transforming faults as well as for commonly occurring shunt faults in thyristor controlled series capacitor (TCSC) compensated transmission line. DB-4 wavelet is used for pre-processing of the three-phase current and voltage signals. The shunt capacitance of the line is considered based on distributed parameter line model. Feasibility of the ANN-based fault location algorithm is tested under a wide variation of parameters, such as fault type, location, fault resistance and fault inception angle. Fault location errors are within 0.001–1% range.