Adaptive Control of Virtual Synchronous Generator Based RBF Neural Network

When the power of the distribution power generation system of the microgrid fluctuates greatly, the output power and frequency of the virtual synchronous generator (VSG) are prone to oscillate. Vibration can be suppressed by adjusting the moment of inertia and damping coefficient. However, due to the nonlinear relationship between these two parameters and frequency, this paper proposes a RBF neural network to improve the VSG moment of inertia and damping coefficient adaptive control strategy. Finally, MATLAB/Simulink simulation platform is used to build the microgrid model and improved VSG algorithm, and simulation experiments are carried out. The results verify the correctness and effectiveness of the proposed control strategy.