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Coupled computational fluid dynamics/multibody dynamics method for wind turbine aero-servo-elastic simulation including drivetrain dynamics

Author

Listed:
  • Li, Y.
  • Castro, A.M.
  • Martin, J.E.
  • Sinokrot, T.
  • Prescott, W.
  • Carrica, P.M.

Abstract

A high-fidelity simulation framework is presented to investigate wind turbine aero-servo-elastic behavior, coupling dynamic overset computational fluid dynamics (CFD) and multibody dynamics (MBD) approaches. The Gearbox Reliability Collaborative (GRC) project gearbox was up-scaled in size and installed in the NREL 5-MW offshore wind turbine to demonstrate drivetrain dynamics. Generator torque and blade pitch controllers were implemented to simulate operational conditions of commercial wind turbines. Interactions between wind turbulence, rotor aerodynamics, elastic blades, drivetrain dynamics at the gear-level and servo-control dynamics were studied. Results show that gear contact causes dynamic transmission error within the drivetrain, and results in a decreased turbine thrust and rotational speed. The generator torque controller optimizes efficiency below rated wind speed, while the blade pitch controller properly regulates the turbine near rated power and generator speed at higher than rated wind speed under both uniform and turbulent winds. The pitch controller effectively reduces turbine thrust, blade tip deflections, and velocity deficit of the wake, benefiting both stand-alone turbines and wind farms. The tool and methodology developed show promise to study complex aerodynamic/mechanic systems, being the first time a complete wind turbine simulation includes CFD of the rotor/tower aerodynamics, wind turbulence, elastic blades, gearbox dynamics and feedback control.

Suggested Citation

  • Li, Y. & Castro, A.M. & Martin, J.E. & Sinokrot, T. & Prescott, W. & Carrica, P.M., 2017. "Coupled computational fluid dynamics/multibody dynamics method for wind turbine aero-servo-elastic simulation including drivetrain dynamics," Renewable Energy, Elsevier, vol. 101(C), pages 1037-1051.
  • Handle: RePEc:eee:renene:v:101:y:2017:i:c:p:1037-1051
    DOI: 10.1016/j.renene.2016.09.070
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    References listed on IDEAS

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    1. 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.
    2. Li, Y. & Castro, A.M. & Sinokrot, T. & Prescott, W. & Carrica, P.M., 2015. "Coupled multi-body dynamics and CFD for wind turbine simulation including explicit wind turbulence," Renewable Energy, Elsevier, vol. 76(C), pages 338-361.
    3. Kim, Taeseong & Hansen, Anders M. & Branner, Kim, 2013. "Development of an anisotropic beam finite element for composite wind turbine blades in multibody system," Renewable Energy, Elsevier, vol. 59(C), pages 172-183.
    4. Li, Yuwei & Paik, Kwang-Jun & Xing, Tao & Carrica, Pablo M., 2012. "Dynamic overset CFD simulations of wind turbine aerodynamics," Renewable Energy, Elsevier, vol. 37(1), pages 285-298.
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    Cited by:

    1. Yunxuan Dong & Jianzhou Wang & Chen Wang & Zhenhai Guo, 2017. "Research and Application of Hybrid Forecasting Model Based on an Optimal Feature Selection System—A Case Study on Electrical Load Forecasting," Energies, MDPI, vol. 10(4), pages 1-27, April.
    2. He, Jiao & Jin, Xin & Xie, S.Y. & Cao, Le & Lin, Yifan & Wang, Ning, 2019. "Multi-body dynamics modeling and TMD optimization based on the improved AFSA for floating wind turbines," Renewable Energy, Elsevier, vol. 141(C), pages 305-321.
    3. Andrés Guggeri & Martín Draper, 2019. "Large Eddy Simulation of an Onshore Wind Farm with the Actuator Line Model Including Wind Turbine’s Control below and above Rated Wind Speed," Energies, MDPI, vol. 12(18), pages 1-21, September.
    4. He, Guolin & Ding, Kang & Wu, Xiaomeng & Yang, Xiaoqing, 2019. "Dynamics modeling and vibration modulation signal analysis of wind turbine planetary gearbox with a floating sun gear," Renewable Energy, Elsevier, vol. 139(C), pages 718-729.
    5. Rodriguez, Steven N. & Jaworski, Justin W., 2019. "Strongly-coupled aeroelastic free-vortex wake framework for floating offshore wind turbine rotors. Part 1: Numerical framework," Renewable Energy, Elsevier, vol. 141(C), pages 1127-1145.
    6. 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.
    7. de Oliveira, Marielle & Puraca, Rodolfo C. & Carmo, Bruno S., 2023. "A study on the influence of the numerical scheme on the accuracy of blade-resolved simulations employed to evaluate the performance of the NREL 5 MW wind turbine rotor in full scale," Energy, Elsevier, vol. 283(C).
    8. Fan Zhang & Juchuan Dai & Deshun Liu & Linxing Li & Xin Long, 2019. "Investigation of the Pitch Load of Large-Scale Wind Turbines Using Field SCADA Data," Energies, MDPI, vol. 12(3), pages 1-20, February.
    9. Yao Li & Caichao Zhu & Xu Chen & Jianjun Tan, 2020. "Fatigue Reliability Analysis of Wind Turbine Drivetrain Considering Strength Degradation and Load Sharing Using Survival Signature and FTA," Energies, MDPI, vol. 13(8), pages 1-21, April.

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