Intelligent grey-box modeling and linear state-space representation of dominating mechanical dynamics for large-scale wind turbine

被引：1
|
作者：
Pan C.-Y. [1 ]
Hu Y. [1 ]
Xi Y.-H. [1 ]
机构：
[1] School of Control and Computer Engineering, North China Electric Power University, Beijing
来源：
Hu, Yang (hooyoung@ncepu.edu.cn) | 1600年 / South China University of Technology卷 / 37期
基金：
中国国家自然科学基金;
关键词：
Dominating mechanical dynamics; Intelligent grey-box parameter identification; Joint state-space model; Piece-wise affine model; Wind power generation;
D O I：
10.7641/CTA.2019.90328
中图分类号：
学科分类号：
摘要：
As the development of wind power gradually changes from quantitative expansions to qualitative improvements, more attention has been paid to the fine control of wind turbines, and reasonable modeling of wind turbine dynamics is an important foundation. The dominating mechanical dynamics modeling of wind turbines is studied and its complete state-space representation is established in this paper. Firstly, the characteristics of wind turbine subsystems are analyzed and the piece-wise affine model of the aerodynamic torque is built in terms of aerodynamic characteristics, which is utilized to characterize the static characteristics. Then, the intelligent grey-box parameter identification procedure is systematically formulated. With regard to the multi-input multi-output drive-train system, the weighted optimization objective is utilized for identification to acquire its state-space model with the physical meaning, which is combined with aerodynamic model to form the joint state-space model. Finally, based on the simulation of 5 MW wind turbine model in FAST, the modeling strategy is verified, and the results show the constructed joint model can achieve a good fitting effect for the actual dynamic characteristics. © 2020, Editorial Department of Control Theory & Applications South China University of Technology. All right reserved.
引用
收藏
页码：1260 / 1269
页数：9
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