A new single-ended traveling wave-based protection algorithm for a system with few traveling wave recorders

Using artificial intelligence and traveling wave (TW) theory, a novel single-ended protection algorithm is proposed in this paper for a power system in which the number of TW recorders is smaller than the number of buses. Because of its unique performance, speed and resolution, Teager energy operator is used to extract successive TWs from the current signal. Hidden Markov model is then utilized as an intelligent and probabilistic method to discriminate between internal and external faults. In the case of internal faults, fault type classification and faulted phase selection are also performed in this paper. In this part, a fuzzy system is used as another intelligent method to classify fault types and identify faulted phases. The impact of CT and CCVT on current and voltage signals are also considered. Faulted signals are simulated by PSCAD/EMTDC software. Simulation results show that the proposed algorithm is not only accurate but also capable of making right decisions in special cases such as faults with low inception angles and close-in faults.