A correlation based method for discrimination between inrush and short circuit currents in differential protection of power transformer using Discrete Wavelet Transform: Theory,simulation and experimental validation

This paper presents a new method for discrimination between magnetic inrush current and internal fault current in the differential protection of power transformer. The proposed method is based on the Wavelet Transform and correlation coefficient. In this study Discrete Wavelet Transform is used to describe the current signal in terms of different time and frequency components. In the proposed method, the energy signals of these components are employed. In the proposed method, a statistical parameter known as correlation coefficient is used to establish a criterion for the proposed discriminative algorithm. The correlation coefficient is used for express the relationship between wavelet coefficients energy at different scales of the signal resolution. Then pattern of these relations is utilized as a measure to discriminate the inrush current from fault current. For investigation the accuracy of the proposed algorithm different cases of inrush and internal fault currents is simulated by PSCAD/EMTDC software. Also, the proposed method is tested by the gathered data from experimental test at the laboratory. Current signals obtained from the simulation as well as the results obtained from the experimental test are employed by the proposed discriminative algorithm. Analysis of the simulation and experimental results show that the proposed method accurately identifies inrush and fault currents in the distance of the power transformer protection in a time period less than quarter of power frequency cycle. In addition to the sensitivity and high reliability, the proposed method has low computation work and does not required determining the threshold for each new power system.