Adaptive Control Strategy of Parallel Virtual Synchronizer of Wind–Solar–Storage Microgrid Based on Neural Network

In order to solve the problem that the impedance of each line of the parallel system of the wind–solar–storage virtual synchronous machine (VSG) is inconsistent, resulting in the power circulation between the parallel VSG, a multi-parameter collaborative adaptive control strategy for the parallel virtual synchronizers of a wind–solar–storage microgrid based on a neural network was proposed. Firstly, the topology of the virtual synchronous machine parallel system of the wind–solar–storage microgrid was built, and the VSG was analyzed. Then, the neural network algorithm was used to realize the adaptive adjustment of each parameter of VSG, which improves the uneven power distribution and the influence of circulation. Next, the parameters of multiple parallel VSG control systems were configured. Finally, MATLAB2021a/Simulink was used to model the system, and the VSG capacity under different scale conditions was simulated and analyzed. The simulation results show that when the capacity ratio of VSG1 and VSG2 is 1:1, the active power output is 9000 W, and the reactive power output is 7500 Var, which realizes accurate distribution, and when the capacity ratio of VSG1 and VSG2 is 2:1, the output values of active power and reactive power are 12,000 W/6000 W and 10,000 Var/5000 Var, and the output is carried out according to the ratio of 2:1, which shows that the control strategy can effectively improve the power allocation accuracy, suppressing circulation.