Aiming at the dynamic adjustable control parameters of virtual synchronous generator (VSG), many technologies have been proposed to optimize the rotational inertia and damping coefficient of VSG to improve the dynamic performance, but the optimization limit of dynamic performance has not been determined. In order to explore the optimal dynamic performance of VSG, the optimal solution problem of dynamic performance is converted into optimal solution set of rotational inertia and damping coefficient, and then the particle swarm optimization (PSO) algorithm is used to solve the problem. In order to examine the impact of damping coefficient and rotational inertia on the power system’s dynamic performance, the small signal model of VSG is developed in this research. Based on this, the PSO method is utilized to determine the ideal values for the damping coefficient and rotational inertia parameters for every switching cycle, and the inertia coefficient and damping coefficient are dynamically adjusted according to the solution set of the optimal control parameters obtained. This tactic improves the system’s dynamic performance in terms of frequency and active power production, and improves the stability of the system. Lastly, the efficacy and superiority of the suggested technique are confirmed by comparing it with other control systems that are currently in use using MATLAB/Simulink simulation.