Abstract
The discrimination of inrush currents and internal fault currents in transformers is an important feature of a transformer protection scheme. The harmonic current restrained feature is used in conventional differential relay protection of transformers. A literature survey shows that the discrimination between the inrush currents and internal fault currents is still an area that is open to research. In this paper, the classification of internal fault currents and magnetic inrush currents in the transformer is performed by using an extended Kalman filter (EKF) algorithm. When a transformer is energized under normal conditions, the EKF estimates the primary side winding current and, hence, the absolute residual signal (ARS) value is zero. The ARS value will not be equal to zero for internal fault and inrush phenomena conditions; hence, the EKF algorithm will be used for discriminating the internal faults and inrush faults by keeping the threshold level to the ARS value. The simulation results are compared with the theoretical analysis under various conditions. It is also observed that the detection time of internal faults decreases with the severity of the fault. The results of various test cases using the EKF algorithm are presented. This scheme provides fast protection of the transformer for severe faults.
Highlights
Transformers require an efficient protection system from faulty conditions in the power system network
The simulation model for discrimination of magnetic inrush current, 2% internal fault, 4% internal fault, and 6% internal fault along with current waveforms is given in Figure 19a,b and the respective absolute residual signal (ARS) signals obtained from various sources are depicted in Figure 20, which indicates that the residual signal keeps increasing with the severity of the fault
The extended Kalman filter (EKF) was implemented for the discrimination of inrush currents and internal faults current of a single-phase transformer
Summary
Transformers require an efficient protection system from faulty conditions in the power system network. The discrimination of the inrush currents from the internal faults in power transformers was suggested based on the runs test method, which is derived from the inherent differences between the waveforms [6]. The extraction of features with the measured data from the differential currents of a power transformer is suggested by using random the forest-based fault discrimination (RFBFD) technique [22]. New techniques, such as LES, DWT and EKF, are suggested for analysis and estimation of the current from the measured waveform. The simulation results are presented to evaluate the EKF for different conditions of the transformer
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