Efficient hybrid strategy based on FFT and fuzzy logic techniques applied to fault diagnosis in power transmission line

Fault diagnosis and detection in electrical power systems need a development of new and robust supervision structures. In the last years, different intelligent monitoring methods have been successfully proposed to deal with the problem of fault diagnosis in power transmission lines. In this work, a new hybrid strategy called FFT-FL combining Fuzzy Logic (FL) approach with Fast Fourier Transform (FFT) is proposed and applied to fault diagnosis in power line network. The elaborated fault detection structure consists of indicating whether the electrical transmission is working correctly or a fault has occurred with an effective isolation step to determine the faulty zone in the line. Whereas, an identification step consists of determining faulty phase thus fault classification in the studied line network. The novel proposed algorithm (FFT-FL) is used to improve the fault diagnosis response time and to decouple between faults and disturbances. In this paper, a comparative study is presented between the two intelligent methods for detection, isolation and identification of faults using only FL and the hybrid FFT-FL structure. The obtained simulation results verify the effectiveness and the correctness of the proposed fault method for all types of faults in the power line networks and in different zones.