A New Method of Current-Transformer Saturation Detection in the Presence of Noise

Abstract

The nonlinear characteristics of magnetization of a current transformer (CT) can cause waveform distortion in the secondary current, which may result in malfunction of protective relays. This phenomenon is known as CT saturation. The accurate saturation detection, with the use of digital-signal-processing techniques applied to secondary current, plays an important function in solving the problems caused by the saturation. This paper presents a new method of saturation detection, based on the first difference of the low-noise Lanczos filter. The formulation of the adaptive threshold according to the level of the signal-to-noise ratio (SNR) is presented and the detection algorithm is implemented, tested, and compared with the 3rd difference function method. The tests were performed using distorted secondary current signals generated by the real-time digital simulator and corrupted by several levels of white Gaussian noise. The results showed a high detection capability of the proposed algorithm regardless of the CT characteristics, the secondary burden, and the fault characteristics. In addition, the method showed to be robust against noise up to 40-dB SNR and suitable for real-time implementation.