In order to introduce the mathematical model and the control structure of the static synchronous series compensator (SSSC), a novel power flow controller based on RBF neural network PID control strategy is proposed in this paper. And the structure of the controller is designed. The power system with SSSC is selected to work in active power control mode, and adopt closed loop control by using PID controller. The self-learning ability of RBF neural network can be used to improve the fixed parameters of traditional PID controller, The three parameters of the PID controller are adjusted on-line in real time, so that the active power of the transmission line can be quickly reached a given reference value. Finally, the controller is simulated and verified in the MATLAB/Simulink simulation environment. Compared with the traditional PID controller and BP neural network PID controller, the results show that the proposed control strategy has better adaptability and robustness.