A Hybrid Signal Processing Technique for Identification and Categorization of Faults in IEEE-9 Bus System

Abstract

A hybrid signal processing technique (HSPT) is proposed in this manuscript for identification and categorization of faults in electrical transmission network. A fault indicator (FI) is suggested by decomposition of the currents by application of Alienation coefficient (ACF), Stockwell transform (ST) and Hilbert transform (HT) for identification of faults. An indicator for ground involvement during faulty condition (SGFI) is being suggested to detect the type of fault. The categorization of faults is done by utilizing faulty phase numbers and SGFI. It is found that the proposed technique is effective in identification of faults and to classify them in different scenarios together with fault on A-phase to ground (AGF), double phase fault (ABF), fault on two phases and ground (ABGF), three phase fault (ABCF) and three phase fault including ground (ABCGF). Study is done and validated on IEEE-9 bus system using MATLAB/Simulink environment. The effectiveness and applicability of the proposed technique with respect to different parameters of faults such as Fault Incidence Angle, Fault Impedance, Line loading, Generator Supply and Noise level is also checked. The results shows that proposed scheme is able to detect and classify the faults in different faulty events.