Framework for current transformer saturation detection and waveform reconstruction

Abstract

Due to current transformer (CT) saturation, the secondary current waveform may contain distortions which results in mal-operation of the protective system. This study presents a framework that attempts to detect and reconstruct saturated secondary current of the CT. To such aim, first an algorithm is proposed which detects and discriminates between normal and abnormal condition. This algorithm which is based on high-order derivatives and statistical criterion, classifies load change, inrush current and fault condition. In addition, this algorithm is designed so that it detects the first time that CT becomes saturated. After fault detection and phase fault selection, based on analytical and comprehensive formulations, the parameter of fault current signal is calculated in the sub-cycle. Moreover, the dynamic behaviour of the CT is considered in the waveform reconstruction. Several case studies are carried out to investigate the performance of the proposed method. Simulation results show that proposed method can effectively classify the inrush current and fault signal even in the CT saturation condition. Also, under different CT saturation condition, proposed method quickly and precisely detects and reconstructs saturated waveform without sacrificing details.