A new high-frequency-based method for the very fast differential protection of power transformers

Abstract

A novel algorithm based on Teager energy operator (TEO) and hidden Markov model (HMM) is presented for the transformer differential protection. After detecting any increase in the amplitude of the transformer differential currents, it is needed to know if the over-current is because of an internal fault or an inrush phenomenon. In this paper, a combination of TEO and HMM is used to discriminate between the magnetizing inrush currents and the internal fault currents. TEO is used to extract high frequency components of the signal and present them as a curve, named as Teager output curve (TOC). Then TOC is used as the input for HMM. First, the HMM training process is implemented by an adequate number of the train signals and then, the unknown signals are identified by the testing process. Fault type identification is also performed by the use of TOC. TOC has a separated region for each of the three phases. TEO of the zero-sequence signal has a peak for the grounded and no peak for the un-grounded faults. Train and test signals are generated by the simulated system in PSCAD/EMTDC. Results by means of the simulated and experimental data show the robustness of the proposed algorithm.