Transmission line faults detection, classification, and location using Discrete Wavelet Transform

Abstract

Transmission line is a vital component that acts as a bridge between the generating stations and end users. In the power system, reliability and stability must be ensured to provide continuity of service. Transmission lines run over several kilometers will have the chance for occurrence of fault. In order to maintain stability, faults should be cleared at short span of time with recent advancements in signal processing. In this paper, a novel technique for the protection of transmission lines is proposed. The proposed system uses Discrete Wavelet Transform (DWT) which is widely used in recent times for power system protection. DWT is used here to extract the hidden factors from the fault signals by performing decomposition at different levels. Daubechies wavelet “dB6” is used with single level decomposition and adaptive threshold is calculated to discriminate and detect the faulty phase. The location of faults is carried out by obtaining the local fault information and remote location fault information along with the transmission line length. The system is independent of any statistical system data and has negligible fault resistance. Test system is modeled and fault signals are generated to test the reliability of the algorithm. The proposed system promises the result by detecting, classifying and locating all the ten faults possible in the transmission line of the power system.