Optimization of Energy Storage Controller Parameters to Suppress Low-frequency Oscillation of High-proportion Wind-solar Access System

To offer a comprehensive understanding of the role energy storage devices play in mitigating the system's low-frequency oscillations, the study delves into a high-proportion wind-solar grid-connected system of four machines and two regions. A mathematical model outlining the battery energy storage controller parameters is constructed and time-domain simulations are performed on the platform. Utilizing the eigenvalue analysis method, the eigenvalues and damping ratios provide a theoretical basis for quantitatively analyzing the optimization of energy storage controller parameters. To enhance the damping effect of the energy storage device, this paper introduces an Improved Particle Swarm Optimization (IPSO) for optimizing the parameters across each link of the energy storage damping controller. The IPSO algorithm optimizes parameters by aiming for the minimal Integrated Time and Absolute Error (ITAE) index of the multi-controller. Simulation results reveal that the optimized energy storage device has markedly amplified the suppression of the system's low-frequency oscillation, thus significantly improving system stability.