Optimization of Pitch Control Parameters for a Wind Turbine Based on Tower Active Damping Control
Yingming Liu,
Shuyuan Zhang (),
Xiaodong Wang,
Hongfang Xie and
Tian Cao ()
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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
Energies, 2022, vol. 15, issue 22, 1-22
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.
Keywords: wind turbine; pitch-speed system; PI; damping; optimization strategy (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
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