A new traveling-wave-based protection algorithm based on intelligent systems

A novel traveling-wave (TW)-based protection algorithm for power transmission lines using intelligent systems is proposed in this paper. The first part of the algorithm identifies internal faults from external ones and the other part is used for fault type classification and faulted phases selection. In order to extract TW signals, Teager energy operator (TEO) is used. Then hidden Markov model (HMM) is utilized to identify internal faults from external faults according to the output of TEO. Fault type classification and faulted phases selection are other important tasks in protection algorithms. In this paper, a very accurate and robust classification algorithm based on fuzzy systems is presented. This algorithm uses different ratios of modal components of the faulted current signal as the input variable of fuzzy systems. The test system is simulated in PSCAD software and the algorithm is implemented in MATLAB. Testing the proposed algorithm with a large number of test signals in different fault conditions shows the robustness of both internal fault identification and fault type classification algorithms.