摘要
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.
| 投稿的翻译标题 | Dynamic performance improvement method of energy storage DC/DC converter for grid-connected wind turbine with energy storage |
|---|---|
| 源语言 | 繁体中文 |
| 页(从-至) | 34-43 |
| 页数 | 10 |
| 期刊 | Electric Power Engineering Technology |
| 卷 | 44 |
| 期 | 2 |
| DOI | |
| 出版状态 | 已出版 - 28 3月 2025 |
| 已对外发布 | 是 |
关键词
- active disturbance rejection control
- dynamic neighborhood search
- improved grey wolf algorithm
- LLC type energy storage DC/DC converter
- offline automatic optimization
- wind turbine with energy storage
学术指纹
探究 '用于构网型配储风机的储能 DC/DC 变换器动态性能提升方法' 的科研主题。它们共同构成独一无二的指纹。引用此
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