ANFIS-Based Compensation Algorithm for Current-Transformer Saturation Effects

This paper proposes an efficient compensation algorithm based on an adaptive network-based fuzzy inference system capable of converting a sampled current waveform that is distorted by current-transformer (CT) saturation to a compensated current waveform. Quick response time, no cumulative estimation error, desired sample-by-sample output, no dependency of CT parameters/characteristics and secondary burdens, and simplicity are some attractive features of the proposed method. The accuracy and robustness of the introduced compensation algorithm are demonstrated through extensive test cases reflecting a wide range of variations in fault conditions and CT parameters. The proposed algorithm has also been implemented and tested on a digital signal processor board.