A hybrid SVM-TT transform-based method for fault location in hybrid transmission lines with underground cables

Abstract This paper proposes a hybrid fault location technique in an overhead line that contains an underground cable. Time-time (TT)- and S-transforms are used to extract information from the transient voltage signals measured at a single end. This information is used to train a support vector machine (SVM) which determines whether the fault occurs in the first or second half of the underground cable or overhead line. To enhance the classification accuracy, the SVM parameters are optimized using the particle swarm optimization (PSO). After the identification, the fault is located using Bewley’s lattice diagram and the transformed voltage signal. The performance of the proposed method is assessed under various parameters such as fault type, resistance, inception angle, and location. Simulation results validate the high accuracy of the proposed method in identifying the faulty section and locating the fault. Also, it is shown that the proposed technique outperforms other methods in the literature.