Research on Linear Programming and Grey Wolf Optimization Algorithm in Energy Storage System Configuration

This paper focuses on the research and application of linear optimization algorithm and grey Wolf optimization algorithm, takes the energy storage system configuration optimization of the park energy system as the research object, and discusses in detail the similarities and differences and advantages of the energy storage system configuration under the three modes of independent operation, joint operation and collaborative configuration of wind storage. Firstly, a linear programming model for optimizing system configuration was established to determine the optimal energy storage power and capacity. In addition, under the consideration of State of Charge (SOC) and other constraints, the grey Wolf optimization algorithm was applied to further optimize the energy storage system configuration of independent parking lots to improve the accuracy and reliability of the optimization results. Secondly, the optimal energy storage configuration of the independent park is analyzed in detail, and the optimal energy storage scheme is deduced through the solution of the model and algorithm, which reflects the superiority of linear programming and grey Wolf optimization algorithm. The final focus is on developing a coordinated future configuration scheme for wind and solar storage. At the same time, the peak and valley electricity factor is introduced into the linear programming model, and the optimized grey Wolf algorithm is used to obtain the optimized energy scheduling and energy storage utilization strategy of the park's power generation and electricity price changes in the next five years.