Study of Wind Power Fluctuation Based on Simulated Annealing Algorithm and Each Filtering Algorithm

This paper investigates the wind power fluctuation problem based on the simulated annealing algorithm and multiple filtering algorithms, aiming to improve the output stability of wind farms and enhance the grid's ability to absorb wind energy. To this end, this paper proposes an energy storage system that makes use of decommissioned power batteries in a gradual manner, and constructs a cooperative scheduling model for wind farms and energy storage systems to optimise charging and discharging operations. Firstly, this paper applies low-pass filtering, Gaussian filtering and sliding average filtering algorithms to process the raw wind power data in order to weaken the noise interference and smooth the power output. Secondly, a simulated annealing algorithm is used to optimally configure the capacity of the energy storage system and finally determine the optimal solution for the rated capacity. The study makes gradual use of retired power batteries, combines multiple filtering algorithms and optimal configurations, systematically solves the problem of wind power fluctuation, and improves the ultimate benefit of wind power grid integration.