基于模型参考自适应的大型风电机组独立变桨控制方法

韩兵, 马杰

分布式能源 ›› 2021, Vol. 6 ›› Issue (5) : 26-32.

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PDF(3371 KB)
分布式能源 ›› 2021, Vol. 6 ›› Issue (5) : 26-32. DOI: 10.16513/j.2096-2185.DE.2106558
学术研究

基于模型参考自适应的大型风电机组独立变桨控制方法

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Individual Pitch Control of Large Wind Turbine Based on Model Reference Adaptive

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摘要

大型风电机组风轮平面上不平衡的载荷,可以通过单独控制每个桨叶的桨距角(独立变桨控制(individual pitch control,IPC))来缓解,但风电机组对风速突然变化的动态响应通常都在时间上滞后。首先提出模型参考自适应的独立变桨优化控制方法,通过测量风轮平面的有效风速,引入前馈控制校正参数的自适应机制,估算延迟的估计值和补偿值;其次通过风轮转速和桨距角的前馈扰动补偿控制,修正由于风速预测滞后导致的发电功率波动和塔架的振动;最后通过实验结果证明,模型参考自适应的独立变桨优化控制技术,提高了大型风电机组独立变桨控制器的性能,在一定程度上提高了风电的利用效率,缓解大型风电机组主要部件的疲劳载荷。

Abstract

On large wind turbine rotor plane unbalanced loads, it can control each blade pitch angle (individual pitch control (IPC)) to ease, but the dynamic response of a sudden change in wind speed wind turbines are usually lag in time. Firstly, model reference optimization of individual pitch control method was given. By measuring the effective wind speed of the turbine plane, the adaptive mechanism of feedforward control correction parameters was introduced to estimate the estimated value and compensation value of the delay. Secondly, the generation power fluctuation and tower vibration caused by the lag of wind speed prediction were corrected by feedforward disturbance compensation control of rotor speed and pitch angle. Finally, the experimental results show that the model reference adaptive independent variable blade optimization control technology improves the performance of independent variable blade controller of large wind turbine, improves the utilization efficiency of wind power to a certain extent, and alleviates the fatigue load of major components of large wind turbine.

关键词

风电机组 / 独立变桨控制(IPC) / 前馈扰动 / 载荷 / 自适应控制

Key words

wind turbines / individual pitch control (IPC) / feedforward disturbance / load / adaptive control

引用本文

导出引用
韩兵, 马杰. 基于模型参考自适应的大型风电机组独立变桨控制方法[J]. 分布式能源. 2021, 6(5): 26-32 https://doi.org/10.16513/j.2096-2185.DE.2106558
Bing HAN, Jie MA. Individual Pitch Control of Large Wind Turbine Based on Model Reference Adaptive[J]. Distributed Energy Resources. 2021, 6(5): 26-32 https://doi.org/10.16513/j.2096-2185.DE.2106558
中图分类号: TM614   

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