Enhanced CT Saturation Detection Based on Fault Current Decomposition and Digital Filtering

Accurate current transformer (CT) saturation identification is crucial for reliable power system protection. Conventional methods often struggle with CT detection accuracy under varying conditions, leading to relay malfunction. To address these limitations, this article presents a novel analytical approach that models fault current as the sum of three components: a sinusoidal term, a decaying dc term, and a saturation-induced error term. A tailored filter is designed to eliminate the sinusoidal component, enabling precise identification of saturation periods. The proposed method is validated through theoretical analysis, mathematical derivations, and simulations using the Jiles-Atherton hysteresis model in PSCAD, ensuring realistic CT behavior. Real-world fault records and experimental analysis are further utilized to assess the practical performance. Comparative analysis against the existing techniques demonstrates improved accuracy, robustness, and computational efficiency. Experimental results confirm the effectiveness of the suggested method in practical scenarios, with successful operation in both ac and dc saturations identification. By improving CT saturation detection, this research enhances relay performance, reduces protection malfunction, and strengthens power system stability. The proposed approach offers a practical and computationally efficient solution for modern protection schemes, addressing key gaps in the existing methodologies.