LAUSR

In the application of microgrid systems that include wind power, photovoltaic systems, diesel generators, and battery storage, the cooperative control and optimisation of power distribution between power sources is a major issue. Recently, the droop control has been used widely in microgrids. However, droop control relies mainly on the line parameter model between the grid and the load. Therefore, to improve the performance of the microgrid, the optimal control of microgrid operation based on the fuzzy sliding mode droop control method is considered in this paper. To begin, system parameters were obtained by modeling droop control with self-learning fuzzy control strategy. Then, to improve the accuracy of the power distribution in the multi-micro source system, the nonlinear differential smoothing control method was employed. Finally, by comparing the self-learning fuzzy sliding mode control based on drooping strategy and the traditional droop control method, it was demonstrated that the method proposed can effectively reduce the fluctuation of the bus voltage and improve the output voltage quality of the microgrid system.