Neural network αth-order inverse control of thyristor controlled series compensator

This paper focuses on using neural network αth-order inverse control strategy (X. Dai et al., Neural network αth-order inverse system method for the control of nonlinear continuous systems, IEE Proceedings—Control Theory and Application (in press); J. Liu, X. Dai, Feasibility of neural network αth-order inverse system control method, Power Syst. Autom. 21 (5) (1997) 15–18; C. Li, Y. Feng, Inverse System Method of Multi-Variable Nonlinear Control, Tsinghua University Press, China, 1991) in the control of thyristor controlled series compensator (TCSC) of transmission system. The identification of neural network αth-order inverse system and the design of additional linear controller are studied for the cases of a single-machine infinite bus system as well as a single-machine infinite bus system simplified from an actual power system. The action of this new strategy on power system stability is also studied. Simulation results show comparing with conventional PID control strategy, the control strategy proposed in this paper is strongly adaptive and the stability of the power systems can be greatly enhanced.