Transformer Differential Protection Using Geometrical Structure Analysis of Waveforms

Abstract

This article uses a different geometrical structure of inrush current with respect to that of fault current for the identification of transformer magnetizing inrush. For this purpose, the differential current is considered as a stochastic signal, and two schemes based on stochastic analysis of differential currents are proposed. The first scheme converts changes in the slope of inrush and fault currents, which is the main difference between converting them into a quantitative description by using the skewness concept of frequency curves. The second scheme introduces a feature criterion based on the kurtosis concept of frequency curves to identify the inrush from the fault current. This criterion quantifies another major difference between inrush and fault currents, which is the peakedness of the differential currents. Simulation studies and experimental results justify that the proposed schemes are able to identify inrush currents reliably, even those with a low second harmonic component. The schemes correctly open the differential protection shortly for the internal fault in operation energized with a fault, even in the case of an internal fault current with a high second harmonic component.

Adaptive differential protection for transformers in grid-connected wind farms

“…There are many methods reported for the identification of internal faults from the operating conditions of the system. Methods such as the differential current gradient, empirical Fourier transforms, parks vectors, geometrical structural analysis of waveform, wavelet transform probability concept and decision tree‐based discrimination, moving windows, and voltage and current ratios are proposed to discriminate internal faults from external faults, inrush, and over excitation conditions. Harmonic restraint methods are commonly used in industries for the detection of inrush and over excitation conditions of the transformers.…”