Dynamic performance improvement method of energy storage DC/DC converter for grid-connected wind turbine with energy storage

The internal storage system of a wind turbine usually needs to be connected to the DC bus using a DC/DC converter. However，due to the poor dynamic performance of the energy storage DC/DC converter using traditional PI control，it is easy to cause a large drop in bus voltage or even the risk of undervoltage shutdown during the grid inertia/frequency support process. This paper proposes adopting auto-disturbance rejection control to improve the anti-disturbance performance and dynamic performance of LLC type energy storage DC/DC converter，and employing the improved gray wolf algorithm to perform offline self-optimization on the six core parameters of the auto-disturbance rejection controller. The algorithm introduces dynamic neighborhood search into the position update strategy of the traditional gray wolf algorithm，which effectively improves the convergence speed of the self-optimization algorithm. The proposed improved gray wolf optimized auto-disturbance rejection control method can effectively shorten the bus voltage recovery time，quickly coordinate the energy exchange between the storage wind turbine and the grid，and effectively improve the bus voltage stability and inertia/frequency support capability of the storage wind turbine. The MATLAB/Simulink simulation results verify the feasibility and effectiveness of the control method proposed in this paper.