Study on the nonlinear structural coupling for wind turbine blade under large deflections by using novel finite difference method

Hang Meng, Jiaxing Wu, Guangchuan Cao, Xintao Li, Guangxing Wu and Yongqian Liu

Renewable Energy, 2024, vol. 223, issue C

Abstract: Wind energy is one of the most promising renewable energy sources in the world. To generate more electricity, the wind turbines are getting larger and larger in recent decades (Jokar et al., 2022). With the wind turbine size growing, the length of the blade is getting slender. The large deflections of slender wind turbine blade will inevitably lead to geometric nonlinearities (Jiang et al. 2022), e.g. nonlinear coupling between torsion and deflection, which complicates the governing equations of motion. To simplify the solution of the nonlinear equations, in the current research, a novel finite-difference method was proposed to solve the nonlinear equations of static beam model for wind turbine blade under large deflections. Firstly, the governing equations of large wind turbine blade have been derived by Newtonian method, which provide more insight into the mechanism of the structure motion. Secondly, owing to its simplicity, finite-difference and Newton–Raphson method were employed to discretize and solve the proposed equations respectively. Finally, the proposed finite-difference method was successfully validated by the popular VABS-based geometric exact beam theory (GEBT) method, which has a more complicated formulation. The nonlinear structural couplings were studied by the proposed method. The results illustrate that the torsion-deflection coupling is strongly nonlinear which plays an important role in the loading and displacement of wind turbine blade under large deflections. The current research will provide guidance for the design of next-generation wind turbine blade.

Keywords: Large wind turbine blade; Large deformation; Nonlinear beam (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:223:y:2024:i:c:s0960148124001605

DOI: 10.1016/j.renene.2024.120095

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