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Multibody modeling of varying complexity for dynamic analysis of large-scale wind turbines

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  • Jin, Xin
  • Li, Lang
  • Ju, Wenbin
  • Zhang, Zhaolong
  • Yang, Xiangang

Abstract

Guaranteeing a robust and reliable wind turbine design under increasingly demanding conditions requires an expert insight into dynamic loading effects of the complete turbine and its subsystems. Traditionally, aeroelastic codes are used to model the wind turbine, where the gearbox is reduced to a few or only one degree of freedom, as bring limitations to describe the dynamic behavior in detail. In this paper, the gearbox dynamic behavior is assessed by means of three multibody models of varying complexity, which are assessed based on modal and dynamic behaviors. This work shows that the fully flexible multibody dynamic model can better reflect the operating condition of the wind turbine. However, due to high calculation precision, the fully flexible multibody dynamic model consumes much times. Therefore, an artificial neural network method is proposed for the prediction of wind turbine dynamic behaviors. The results show that combination of the multibody method and the artificial neural network can reduce the simulation runtime, guaranteeing the accuracy meantime. Therefore, it is of great significance in engineering practice.

Suggested Citation

  • Jin, Xin & Li, Lang & Ju, Wenbin & Zhang, Zhaolong & Yang, Xiangang, 2016. "Multibody modeling of varying complexity for dynamic analysis of large-scale wind turbines," Renewable Energy, Elsevier, vol. 90(C), pages 336-351.
    • Handle: RePEc:eee:renene:v:90:y:2016:i:c:p:336-351
    DOI: 10.1016/j.renene.2016.01.003
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    References listed on IDEAS

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    1. Hansen, Anca D. & Michalke, Gabriele, 2007. "Fault ride-through capability of DFIG wind turbines," Renewable Energy, Elsevier, vol. 32(9), pages 1594-1610.
    2. Helsen, Jan & Vanhollebeke, Frederik & Marrant, Ben & Vandepitte, Dirk & Desmet, Wim, 2011. "Multibody modelling of varying complexity for modal behaviour analysis of wind turbine gearboxes," Renewable Energy, Elsevier, vol. 36(11), pages 3098-3113.
    3. Boukhezzar, B. & Lupu, L. & Siguerdidjane, H. & Hand, M., 2007. "Multivariable control strategy for variable speed, variable pitch wind turbines," Renewable Energy, Elsevier, vol. 32(8), pages 1273-1287.
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    Cited by:

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    2. Liu, Xianzeng & Yang, Yuhu & Zhang, Jun, 2018. "Resultant vibration signal model based fault diagnosis of a single stage planetary gear train with an incipient tooth crack on the sun gear," Renewable Energy, Elsevier, vol. 122(C), pages 65-79.
    3. W. Dheelibun Remigius & Anand Natarajan, 2022. "A review of wind turbine drivetrain loads and load effects for fixed and floating wind turbines," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 11(1), January.

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