高空风电系统的优化控制研究进展与挑战
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国家自然科学基金资助项目(61973052)


Research Progress and Challenges for the Optimal Control of Airborne Wind Energy Systems
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    摘要:

    为了实现“碳达峰,碳中和”的战略目标,我国将持续推动可再生能源的高比例发展,构建以新能源为主的新型电力系统.作为可再生的清洁源,风能的开发和利用已成为研究的重要方向.研究表明远离地面的高空中风速更加强劲并且更均匀,风向也更稳定,因此,风力发电的进一步突破可以通过用风筝捕获高空风能来实现.为了确保高空风能系统安全、经济、高效地运行,对其控制系统设计的要求极高.本文阐述了国际上几种主流高空风电技术的发电原理、发展进程以及现状.通过对典型的Yo-Yo式结构进行动力学建模,分析了各类非线性控制技术的原理和特点,具体描述了非线性模型预测控制原理和轨迹跟踪控制的仿真结果.总结了未来高空风能控制技术面临的控制算法计算量大,控制系统可靠性研究缺乏以及智能化水平不高等关键问题.

    Abstract:

    In order to achieve the strategic goal of "carbon peak and carbon neutrality", the development of a high proportion of renewable energy will be promoted continuously in our country. Therefore a new power system based on new energy will formed gradually. As a renewable clean source, the development and utilization of wind energy has become an important research direction. Studies have shown that the wind speed in the higher altitude is stronger and the wind direction is more stable. Therefore, breakthroughs in wind power generation can be achieved by capturing highaltitude wind energy. In order to ensure the safe, economical and efficient operation of the highaltitude kite power generation system, the design of its control system has extremely high requirements. This paper starts from the basic principles, development history and application status of several highaltitude wind power technologies. Then, a typical Yo-Yo structure kite is modeled. Based on this model, the principles and characteristics of various nonlinear control technologies are analyzed, and the principle of nonlinear model predictive control and simulation results of trajectory tracking control are described in detail. It summarizes that the key problems of highaltitude wind energy control include that control algorithm calculation is too consuming, the research of control system reliability is lack and the control methods are not intelligent.

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庞岩,杨禹鹏,杜智伟.高空风电系统的优化控制研究进展与挑战[J].动力学与控制学报,2024,22(6):1~10; Pang Yan, Yang YuPeng, Du ZhiWei. Research Progress and Challenges for the Optimal Control of Airborne Wind Energy Systems[J]. Journal of Dynamics and Control,2024,22(6):1-10.

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  • 收稿日期:2023-05-02
  • 最后修改日期:2023-11-07
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  • 在线发布日期: 2024-07-04
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