针对风速的时变性对风电机组气动载荷系数的影响及由此导致的风力发电机不平衡载荷增加问题,提出一种基于参数在线辨识模型的独立变桨系统载荷预测控制策略。首先,利用FFRLS算法在线辨识独立变桨系统的时变参数;然后,基于辨识参数构建多步预测模型;最后,通过滚动优化实时计算桨叶的桨距角。经基于FAST-Matlab联合仿真的NREL 5 MW风力发电机模型的实验,验证了基于在线辨识参数构建的多步预测模型的预测精度以及所设计控制策略在降低风力发电机不平衡载荷方面的优势。
Abstract
The article suggests a load prediction control strategy for the independent pitch system based on the online identification model of the parameters in an effort to address the impact of time-varying wind speed on the aerodynamic load coefficient of wind turbines and the ensuing increase in the unbalanced load of the wind turbine. Using FFRLS, the time-varying factors in the independent pitch system are first detected online. Based on these parameters, a multi-step prediction model is then built. Lastly, rolling optimization is used to determine the blade's pitch angle in real time. The experiments based on the NREL 5 MW wind turbine model in FAST-Matlab co-simulation validate the prediction accuracy of the multi-step prediction model constructed based on the online identification parameters and the benefits of the designed control strategy in mitigating the unbalanced load of the wind turbine.
关键词
独立变桨控制 /
参数辨识 /
模型预测控制 /
载荷 /
风力发电 /
桨距角
Key words
individual pitch control /
parameter identification /
model predictive control /
loads /
wind power /
pitch angle
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参考文献
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基金
中央引导地方科技发展基金（226Z2103G）; 国家自然科学基金（62103126）
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