Current transformer saturation detection by cross-correlation with independent target signal

The saturation of current transformers (CTs) leads to distortion in secondary current, potentially causing malfunction in protective relays within power systems. Detecting the saturated portions in the measured signal and reconstructing the primary reference current are essential to prevent relay malfunctions and ensure sensitivity during faults. Existing methods in the literature still face challenges in improving accuracy, especially in the presence of noise in the measured signal. The proposed method in this paper is more robust under noisy conditions compared to existing signal processing-based methods. It relies on a cross-correlation algorithm that uses an independent target signal. This method is parameter-less and independent of the CT's specifications. Additionally, no extra hardware equipment is required. The proposed method identifies the saturated portions in the measured secondary current in each cycle, enabling the reconstruction of the saturated current to obtain the reference primary current. A test system has been simulated, and the data are processed using MATLAB. Various test cases are executed, and the results confirm that the proposed method is highly effective in providing fast and accurate detection of CT saturation, with improved robustness against noise.