Fast Detection and Compensation of Current Transformer Saturation Using Extended Kalman Filter

Abstract

In this paper, an efficient method based on the Kalman filter (KF) theory is proposed for fast and accurate detection and compensation of current transformer (CT) saturation. During the unsaturated regions, the algorithm uses the current sample points together with extended Kalman filter (EKF) for obtaining a model, which suitably represents the current signal behavior. The acquired model is used to reconstruct the original current waveform during the saturated regions. The onset and end points of the CT saturation intervals are detected by defining a criterion based on the estimation error of the EKF algorithm. The proposed method is very profitable as it requires only one sample point to detect the CT saturation and it also copes with the problems of measurement noises and harmonics. These advantages are confirmed by a large number of test cases obtained using PSCAD/EMTDC software as well as by real-time hardware implementation.