Research on Nonlinear Pitch Control Strategy for Large Wind Turbine Units Based on Effective Wind Speed Estimation

With the increasing capacity of wind turbines, key components including the rotor diameter, tower height, and tower radius expand correspondingly. This heightened inertia extends the response time of pitch actuators during rapid wind speed variations occurring above the rated wind speed. Consequently, wind turbines encounter significant output power oscillations and complex structural loading challenges. To address these issues, this paper proposes a novel pitch control strategy combining an effective wind speed estimation with the inverse system method. The developed control system aims to stabilize the power output and rotational speed despite wind speed fluctuations. Central to this approach is the estimation of the aerodynamic rotor torque using an extended Kalman filter (EKF) applied to the drive train model. The estimated torque is then utilized to compute the effective wind speed at the rotor plane via a differential method. Leveraging this wind speed estimate, the inverse system technique transforms the nonlinear wind turbine dynamics into a linearized, decoupled pseudo-linear system. This linearization facilitates the design of a more agile pitch controller. Simulation outcomes demonstrate that the proposed strategy markedly enhances the pitch response speed, diminishes output power oscillations, and alleviates structural loads, notably at the tower base. These improvements bolster operational safety and stability under the above-rated wind speed conditions.

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Publication Details

Journal
Electronics
Published
2025-06-17
DOI
https://doi.org/10.3390/electronics14122460
Citations
3
Primary Topic
Wind Turbine Control Systems
Type
article
Field-Weighted Citation Impact
2.19
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article

Research on Nonlinear Pitch Control Strategy for Large Wind Turbine Units Based on Effective Wind Speed Estimation

Longjun Li, Yandong Liu, Xiangtian Deng, Haoran Wang et al.
3 citations
Electronics
Wind Turbine Control Systems
2.19
article

Research on Nonlinear Pitch Control Strategy for Large Wind Turbine Units Based on Effective Wind Speed Estimation

Longjun Li, Yandong Liu, Xiangtian Deng, Haoran Wang, Zhaobing Cai, Xuxin Yue, Ruiqi Cai, Ruibo Liu
article en
3 citations

Abstract

With the increasing capacity of wind turbines, key components including the rotor diameter, tower height, and tower radius expand correspondingly. This heightened inertia extends the response time of pitch actuators during rapid wind speed variations occurring above the rated wind speed. Consequently, wind turbines encounter significant output power oscillations and complex structural loading challenges. To address these issues, this paper proposes a novel pitch control strategy combining an effective wind speed estimation with the inverse system method. The developed control system aims to stabilize the power output and rotational speed despite wind speed fluctuations. Central to this approach is the estimation of the aerodynamic rotor torque using an extended Kalman filter (EKF) applied to the drive train model. The estimated torque is then utilized to compute the effective wind speed at the rotor plane via a differential method. Leveraging this wind speed estimate, the inverse system technique transforms the nonlinear wind turbine dynamics into a linearized, decoupled pseudo-linear system. This linearization facilitates the design of a more agile pitch controller. Simulation outcomes demonstrate that the proposed strategy markedly enhances the pitch response speed, diminishes output power oscillations, and alleviates structural loads, notably at the tower base. These improvements bolster operational safety and stability under the above-rated wind speed conditions.

ElectronicsVol. 14(12)
China Three Gorges Corporation (China) (CN), Wuhan University of Technology (CN)
Openalex Percentile: Top 12%
Wind Turbine Control Systems
2.19
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Research on Nonlinear Pitch Control Strategy for Large Wind Turbine Units Based on Effective Wind Speed Estimation — Longjun Li, Yandong Liu, et al. · Electronics (2025) | TGRS Research Map | TGRS