基于FFRLS的独立变桨系统载荷预测控制

姜萍; 耿金鹏; 张天翼; 付磊

doi:doi:10.19912/j.0254-0096.tynxb.2024-1348

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基于FFRLS的独立变桨系统载荷预测控制

更新时间：2026-01-08

- 基于FFRLS的独立变桨系统载荷预测控制
- Vol. 46, Issue 12, Pages: 701-707(2025)
- 作者机构：
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- DOI：doi:10.19912/j.0254-0096.tynxb.2024-1348
  CLC： TM614
- Published Online：07 January 2026，
  
  Published：2025
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姜萍, 耿金鹏, 张天翼, et al. 基于FFRLS的独立变桨系统载荷预测控制[J]. 2025, 46(12): 701-707.
DOI：

姜萍, 耿金鹏, 张天翼, et al. 基于FFRLS的独立变桨系统载荷预测控制[J]. 2025, 46(12): 701-707. DOI： doi:10.19912/j.0254-0096.tynxb.2024-1348.

摘要

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.

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references

TANG S Z, TIAN D, HUANG M Y, et al.Load control optimization method for offshore wind turbine based on LTR[J]. Energy reports, 2021, 7: 4288-4297.

应有, 杨帆, 许国东. 大型风电机组独立变桨控制技术仿真与现场试验研究[J]. 太阳能学报, 2013, 34(5): 882-888.

孙欣宇, 向东, 丁伟, 等. 基于麻雀搜索算法的风电机组独立变桨控制研究[J]. 太阳能学报, 2023, 44(10): 266-274.

LI C C, HU J Q, YU J, et al.A review on the application of the mpc technology in wind power control of wind farms[J]. Journal of energy and power technology, 2021, 3(3): 1-22.

PETROVIĆ V, JELAVIĆ M, BAOTIĆ M.MPC framework for constrained wind turbine individual pitch control[J]. Wind energy, 2021, 24(1): 54-68.

周嘉玉, 郝万君. 基于NMPC-PID的大型风力机独立变桨控制[J]. 机床与液压, 2023, 51(3): 151-155.

王多睿, 王维庆, 蔡鑫. 基于NMPC-PID的风力机独立变桨距控制策略研究[J]. 太阳能学报, 2017, 38(9): 2520-2526.

LAI X, WENG J H, HUANG Y F, et al.A joint state-of-health and state-of-energy estimation method for lithium-ion batteries through combining the forgetting factor recursive least squares and unscented Kalman filter[J]. Measurement, 2022, 205: 112187.

张天翼. 风力发电系统模型预测变桨距控制策略研究[D]. 保定: 河北大学, 2024.

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