Identification of current transformers saturation intervals using morphological gradient and morphological decomposition

This paper proposes a novel method to detect the saturation intervals of current transformer (CT) secondary current. The method features the waveform properties of the distorted secondary current, which has abrupt changes where saturation begins and ends. Two algorithms, the improved morphological gradient and the morphological decomposition, are designed to extract the saturation intervals, respectively, and the detection results are combined using the AND logic to give the final detection result. The proposed saturation detection scheme is implemented and tested on a sample power system model built in PSCAD/EMTDC. The simulation results show that the proposed method can accurately detect the onsets and ends of saturations under a variety of operation conditions.