考虑预测风速特性的风力机最大功率点自适应转矩前馈控制

IF 5 2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Liangwen Qi , Min Zhao , Songsong Wu , Xiaohan Zhang , Pengfei Meng , Yong Zhao , Wei Deng
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引用次数: 0

摘要

惯性的增长加剧了风力发电机缓慢的动态响应与快速变化的风速之间的冲突,从而降低了最大功率点跟踪(MPPT)的有效性。由于传统的最优转矩(OT)控制只关注稳态性能,而忽略了动态风特性,因此在低风速、高频率下,其MPPT跟踪带宽有限。为此,提出了一种自适应前馈转矩控制(AFTC)方法,根据风向变化动态调整MPPT跟踪带宽。该方法将卡尔曼观测器用于气动扭矩估计,并采用牛顿-拉夫森方法计算实时风速。单指数平滑法预测未来平均风速和等效湍流频率。这些预测值自适应地调度前馈增益,在不改变稳态平衡的情况下实现带宽适应。与传统OT控制和典型前馈控制的对比分析表明,ATFC在功率提升和转矩波动之间取得了较好的平衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive torque feed-forward control for wind turbine MPPT considering predicted wind speed characteristics
The growing inertia exacerbates the conflict between the slow dynamic response of wind turbines and rapidly changing wind speed, thereby diminishing the effectiveness of maximum power point tracking (MPPT). Conventional optimal torque (OT) control exhibits limited MPPT tracking bandwidth under low wind speeds with high frequency due to its exclusive focus on steady-state performance and neglect of dynamic wind characteristics. In this regard, an adaptive feed-forward torque control (AFTC) approach is proposed to dynamically adjust the MPPT tracking bandwidth in response to wind variations. The approach integrates a Kalman observer for aerodynamic torque estimation and employs the Newton-Raphson method to derive real-time wind speed. A single exponential smoothing method predicts future mean wind speed and equivalent turbulence frequency. These predicted values adaptively schedule the feed-forward gain, enabling bandwidth adaptation without altering steady-state equilibrium. Comparative analyses with the conventional OT control and the typical feed-forward control demonstrate that ATFC achieves a better trade-off between the power improvement and torque fluctuations.
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来源期刊
International Journal of Electrical Power & Energy Systems
International Journal of Electrical Power & Energy Systems 工程技术-工程:电子与电气
CiteScore
12.10
自引率
17.30%
发文量
1022
审稿时长
51 days
期刊介绍: The journal covers theoretical developments in electrical power and energy systems and their applications. The coverage embraces: generation and network planning; reliability; long and short term operation; expert systems; neural networks; object oriented systems; system control centres; database and information systems; stock and parameter estimation; system security and adequacy; network theory, modelling and computation; small and large system dynamics; dynamic model identification; on-line control including load and switching control; protection; distribution systems; energy economics; impact of non-conventional systems; and man-machine interfaces. As well as original research papers, the journal publishes short contributions, book reviews and conference reports. All papers are peer-reviewed by at least two referees.
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