Adaptive blade pitch control method based on an aerodynamic blade oscillator model for vertical axis wind turbines

Wenxing Hao, Chun Li and Fuzhong Wu

Renewable Energy, 2024, vol. 223, issue C

Abstract: In recent decades, the high fatigue loads (mainly derived from the blade normal force fluctuation) and low power coefficient at the low tip speed ratio with high incoming wind speeds have greatly hindered the development of vertical axis wind turbines. Regulating the blade's angle of attack using a pitch control method is an effective way to reduce the blade normal force amplitude and improve the power coefficient. This paper proposes an adaptive blade pitch control method based on an aerodynamic blade oscillator model and studies its performance and control mechanism using the computational fluid dynamics method combined with the dynamics of the aerodynamic oscillator. The results show that the pitch control provides positive performance for most parameter configurations with the power coefficient increased by 105% and the blade normal force amplitude reduced by 29.5% for the best parameter configuration; poor performance with one parameter configuration indicates that the virtual pitch center should not be too close to the acting point of the aerodynamic force, otherwise the flow state transformation will make the pitch variation unsatisfactory; with an appropriate parameter configuration, the adaptive pitch control adaptively decreases the pitch angle amplitude with the tip speed ratio increase and provides positive performance for varying tip speed ratios. The research provides a theoretical basis for the application of the adaptive pitch control on vertical axis wind turbines.

Keywords: Vertical axis wind turbines; Adaptive pitch control; Power coefficient; Blade fatigue loads; Computational fluid dynamics (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:223:y:2024:i:c:s0960148124001794

DOI: 10.1016/j.renene.2024.120114

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