An Auto-correlation Function Based Technique for Discrimination of Internal Fault and Magnetizing Inrush Current in Power Transformers

摘要

This article presents an efficient method for discriminating magnetizing inrush and internal fault currents in three-phase transformers based on the auto-correlation function. For each phase, the auto-correlation function of the differential current is calculated for a specified range of lags. Their standard deviation is determined in the next step. Criterion function is simply defined as the difference between the maximum and minimum of the auto-correlation function lags standard deviations for the three phases. Performance of the proposed method is evaluated and compared with eight well-known methods by a large number of simulation and experimental data, covering different cases. The results confirm that the proposed technique is more efficient than the other methods from speed response, reliability, and accuracy points of view. To eliminate the current transformer saturation impact on the performance of the method, the currents are compensated by a current transformer saturation correction algorithm. Also, the proposed algorithm is evaluated in the case of a transformer that is fed through a feeder with series capacitors.