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Design and Assessment of a LIDAR-Based Model Predictive Wind Turbine Control

Author

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  • Jie Bao

    (Wind Energy and Control Centre, Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow G1 1XW, UK)

  • Hong Yue

    (Wind Energy and Control Centre, Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow G1 1XW, UK)

Abstract

The development of the Light Detection and Ranging (LIDAR) technology has enabled wider options for wind turbine control, in particular regarding disturbance rejection. The LIDAR measurements provide a spatial, preview wind information, based on which the controller has a better chance to cope with the wind disturbance before it affects the turbine operation. In this paper, a model predictive controller for above-rated wind turbine control was developed with the use of pseudo-LIDAR wind measurements data. A predictive control algorithm was developed based on a linearised wind turbine model, in which the disturbance from the incoming wind was computed by the LIDAR simulator. The optimal control action was applied to the nonlinear turbine model. The developed controller was compared with the baseline control and a previously developed LIDAR-assisted control combining a feedback-and-feedforward design. Our simulation studies on a 5 MW nonlinear wind turbine model, under different wind conditions, demonstrated that the developed LIDAR-based predictive control achieved improved performance in the presence of small variations in the out-of-plane rotor torque and fore-aft tower acceleration, as well as a smoother generator speed regulation and satisfied pitch activity control constraints.

Suggested Citation

  • Jie Bao & Hong Yue, 2022. "Design and Assessment of a LIDAR-Based Model Predictive Wind Turbine Control," Energies, MDPI, vol. 15(17), pages 1-19, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:17:p:6429-:d:905571
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    References listed on IDEAS

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    1. Bottasso, C.L. & Pizzinelli, P. & Riboldi, C.E.D. & Tasca, L., 2014. "LiDAR-enabled model predictive control of wind turbines with real-time capabilities," Renewable Energy, Elsevier, vol. 71(C), pages 442-452.
    2. Xiaobing Kong & Lele Ma & Xiangjie Liu & Mohamed Abdelkarim Abdelbaky & Qian Wu, 2020. "Wind Turbine Control Using Nonlinear Economic Model Predictive Control over All Operating Regions," Energies, MDPI, vol. 13(1), pages 1-21, January.
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    1. Abhinandan Routray & Yiza Srikanth Reddy & Sung-ho Hur, 2023. "Predictive Control of a Wind Turbine Based on Neural Network-Based Wind Speed Estimation," Sustainability, MDPI, vol. 15(12), pages 1-22, June.

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