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Optimization of Pitch Control Parameters for a Wind Turbine Based on Tower Active Damping Control

Author

Listed:
  • Yingming Liu

    (School of Electrical Engineering, Shenyang University of Technology, Liao Shen West Road 111, Shenyang 110027, China)

  • Shuyuan Zhang

    (School of Electrical Engineering, Shenyang University of Technology, Liao Shen West Road 111, Shenyang 110027, China)

  • Xiaodong Wang

    (School of Electrical Engineering, Shenyang University of Technology, Liao Shen West Road 111, Shenyang 110027, China)

  • Hongfang Xie

    (School of Electric Power, Shenyang Institute of Technology, Pu Chang Road 18, Shenyang 110136, China)

  • Tian Cao

    (School of Electrical Engineering, China University of Mining and Technology, University Road 1, Xuzhou 221116, China)

Abstract

Given the difficulty of accurately setting multiple control parameters in wind turbines, a design method for a pitch controller considering tower load reduction is proposed, which enhances the control performance and reduces both the tower vibration and load. Firstly, the pitch-speed system and the tower fore-aft active damping control are built. In addition, the explicit equation of the tower fore-aft active damping gain is deduced to calculate its initial value. Secondly, the pitch-speed system is identified as an inertial time-delay system using the least squares method. Subsequently, the pitch PI control parameters are set using the Chien–Hrones–Reswick method. Thirdly, the pitch PI control parameters and the tower fore-aft active damping gains are optimized based on the kindred-protected genetic algorithm, which improves the accuracy of the control parameters. Meanwhile, the Pareto method is used to coordinate the control objectives by allocating the weight. Furthermore, the adaptive control is built by fitting the parameters with the wind speed points using the least squares method to enhance the control performance. Finally, the effectiveness of the proposed design method is verified by comparing the control performance with the tower vibration and load.

Suggested Citation

  • Yingming Liu & Shuyuan Zhang & Xiaodong Wang & Hongfang Xie & Tian Cao, 2022. "Optimization of Pitch Control Parameters for a Wind Turbine Based on Tower Active Damping Control," Energies, MDPI, vol. 15(22), pages 1-22, November.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:22:p:8686-:d:977614
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    References listed on IDEAS

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    1. Murtadha Al-Kaabi & Virgil Dumbrava & Mircea Eremia, 2022. "A Slime Mould Algorithm Programming for Solving Single and Multi-Objective Optimal Power Flow Problems with Pareto Front Approach: A Case Study of the Iraqi Super Grid High Voltage," Energies, MDPI, vol. 15(20), pages 1-33, October.
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