Optimization of control strategies for hybrid energy storage systems based on model prediction

Distributed power systems are affected by weather changes and load variations, both of which can affect the power balance of a DC microgrid. The voltage on the DC bus is directly affected by the power imbalance, which can cause significant load damage if the voltage fluctuation is too large. Therefore, in order to maintain the dynamic power balance of the DC microgrid, this paper optimises the existing hierarchical control strategy for hybrid energy storage systems with model predictions. Firstly, a discrete-time prediction model of the hybrid energy storage system is established; secondly, a sequential structure model is used for hierarchical elimination of weight coefficients to select the best switching state while eliminating the weight factor of the objective function to maintain the good dynamic performance of the system; finally, several scenarios are simulated and the soundness of the method is confirmed by the conclusions.