ANFIS approach for SSSC controller design for the improvement of transient stability performance

In this paper, an Adaptive Neuro-Fuzzy Inference System (ANFIS) method based on the Artificial Neural Network (ANN) is applied to design a Static Synchronous Series Compensator (SSSC)-based controller for the improvement of transient stability. The proposed ANFIS controller combines the advantages of a fuzzy controller as well as the quick response and adaptability nature of an ANN. The ANFIS structures were trained using the generated database by the fuzzy controller of the SSSC. It is observed that the proposed SSSC controller improves greatly the voltage profile of the system under severe disturbances. The results prove that the proposed SSSC-based ANFIS controller is found to be robust to fault location and changes in operating conditions. Further, the simulation results obtained are compared with the conventional lead-lag controller under various disturbances, namely three-phase unbalanced faults and other unbalanced faults to show the effectiveness and robustness of the proposed approach for SSSC.