Neuro-fuzzy control of SSSC and SNMS for transient stability improvement of power system transmission lines

New and efficient configurations of adaptive Static Synchronous Series Compensator (SSSC) and Superconducting Magnetic Energy Storage (SMES) controllers based on the Artificial Neural Network (ANN) and the fuzzy control is presented in this paper. The proposed Neuro-Fuzzy controllers combine the advantages of fuzzy controller and quick response and adaptability nature of ANN. The on-line Neuro-Fuzzy control of the SSSC and the SMES has been applied to this study. The ANN structures were trained using the generated database by fuzzy controllers of SSSC and SMES. The results prove that each of proposed SSSC and SMES Neuro-Fuzzy controllers can improve the tie line load ability and transient stability of the test system more efficient than fuzzy controller of the Flexible Alternating Current Transmission System (FACTS) devices.