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A study of dynamic response of a wind turbine blade based on the multi-body dynamics method

Author

Listed:
  • Xu, Jin
  • Zhang, Lei
  • Li, Xue
  • Li, Shuang
  • Yang, Ke

Abstract

The geometric nonlinear problem caused by large deformation and the aeroelastic issue under extreme wind conditions are becoming more and more prominent, as the flexibility of wind turbine blades enhances. To solve this problem, a model of Blade analysis with Multi-Body (BaMB) method is built by the rigid multi-body dynamics method in absolute coordinates. The model describes geometric nonlinearity and complex geometry of blades, and accurate results can be obtained by the model after blades are reasonably divided. Based on this model, the geometric nonlinearity of a 100 kW blade under static loading and the aeroelastic response under extreme operating gust (EOG) condition are investigated numerically and compared with experimental results. The results show that BaMB model is able to predict more accurate deformation than beam models under static loading when the deformation of the blade increases, especially when the blade is loaded with more than 120% of the maximum design load and the tip deflection is larger than 15.36% of the blade spans. At 210% of the maximum design load, the BaMB model can predict the deformation at the accuracy of 1.48% with respect to the test; however, the accuracies of the Euler-Bernoulli beam and the Timoshenko beam are 18.3% and 16.79%, respectively. Even in the case of large deformation, the BaMB model can reach the accuracy close to the finite element method (FEM) with high computational efficiency. The aeroelastic response of the blade under EOG condition is analyzed, and the results show that the BaMB model predicts reliable aeroelastic characteristics of the blade compared with commercial software.

Suggested Citation

  • Xu, Jin & Zhang, Lei & Li, Xue & Li, Shuang & Yang, Ke, 2020. "A study of dynamic response of a wind turbine blade based on the multi-body dynamics method," Renewable Energy, Elsevier, vol. 155(C), pages 358-368.
  • Handle: RePEc:eee:renene:v:155:y:2020:i:c:p:358-368
    DOI: 10.1016/j.renene.2020.03.103
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    References listed on IDEAS

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    3. Kaewniam, Panida & Cao, Maosen & Alkayem, Nizar Faisal & Li, Dayang & Manoach, Emil, 2022. "Recent advances in damage detection of wind turbine blades: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).

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