A Model Predictive Control-based Strategy for Wind Power Smoothing Considering Hybrid Energy Storage Lifetime

To more effectively address the issue of power fluctuations in wind power grid integration and optimize the lifespan of energ y storage, we present a hybrid energy storage power optimization framework that balances fluctuation smoothing and energy storage lifespan. Initially, the wind power output is smoothed using Model Predictive Control (MPC), with the objective function augmented by an adaptive adjustment algorithm that employs weight coefficients related to the state of charge. This enhancement enhances the continuous and stable operation of the energy storage system, determining the aggregate output of the hybrid configuration. Subsequently, the parameters of a weighted sliding filter are refined using a combined Particle Swarm and Simu lated Annealing strategy(PSO-SA), which facilitates dynamic power allocation between supercapacitors and lithium batteries. Finally, simulations based on actual wind power data verify that the proposed strategy effectively reconciles the trade -off between hybrid energy storage lifespan and fluctuation stabilization, while fully accounting for the distinct characteristics of the two energy storage devices to enhance their longevity.