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Numerical investigations of coupled aeroelastic performance of wind turbines by elastic actuator line model

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  • Zheng, Jiancai
  • Wang, Nina
  • Wan, Decheng
  • Strijhak, Sergei

Abstract

With the economic considerations of wind power generation, blades of wind turbines are gradually becoming longer and more flexible. Therefore, it is necessary to research the influence of coupling aerodynamic and elastic structure of blades of wind turbines. Moreover, in a wind farm, the turbulent wind is generated by the irregular movement of the atmosphere, which makes the elastic deformations of blades and the complex wake interference effect between wind turbines. Therefore, the coupled aeroelastic performance of the blade is applied to analyze the interaction of the wake flow field of two tandem wind turbines based on the elastic actuator line model and the Euler-Bernoulli beam theory. Firstly, the correctness of the coupled aeroelastic model is illustrated by comparing the aeroelastic response with OpenFAST software. Secondly, the influence of aeroelastic performances is researched on the structural deformations of blades. It is found that the aerodynamic power and thrust decrease after considering the deformations of blades. Furthermore, the interference effect on the thrust is more evident than aerodynamic power. Thirdly, the far wake region is affected apparently when the deformations of blades are taken into consideration, which causes the tip vortex interference phenomenon to delay. Finally, compared with the uniform inflow condition, the displacement and speed of the deformations of the blades are both increased under the turbulent inflow condition. Meanwhile, the disturbance of the wake vortex in the far wake region by the turbulent wind is stronger. Besides, by comparing the differences between the four vortex identification methods, it is significant that the ΩR method can better capture the vortex system behind the rotor plane without manual intervention threshold selection. The vortex structure also represents the vorticity of the wake vortex evolution.

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  • Zheng, Jiancai & Wang, Nina & Wan, Decheng & Strijhak, Sergei, 2023. "Numerical investigations of coupled aeroelastic performance of wind turbines by elastic actuator line model," Applied Energy, Elsevier, vol. 330(PB).
    • Handle: RePEc:eee:appene:v:330:y:2023:i:pb:s030626192201618x
    DOI: 10.1016/j.apenergy.2022.120361
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    1. Stevens, Richard J.A.M. & Martínez-Tossas, Luis A. & Meneveau, Charles, 2018. "Comparison of wind farm large eddy simulations using actuator disk and actuator line models with wind tunnel experiments," Renewable Energy, Elsevier, vol. 116(PA), pages 470-478.
    2. Xu Ning & Decheng Wan, 2019. "LES Study of Wake Meandering in Different Atmospheric Stabilities and Its Effects on Wind Turbine Aerodynamics," Sustainability, MDPI, vol. 11(24), pages 1-26, December.
    3. Borg, Michael & Collu, Maurizio & Kolios, Athanasios, 2014. "Offshore floating vertical axis wind turbines, dynamics modelling state of the art. Part II: Mooring line and structural dynamics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 1226-1234.
    4. Yimei Wang & Yongqian Liu & Li Li & David Infield & Shuang Han, 2018. "Short-Term Wind Power Forecasting Based on Clustering Pre-Calculated CFD Method," Energies, MDPI, vol. 11(4), pages 1-19, April.
    5. Antonini, Enrico G.A. & Romero, David A. & Amon, Cristina H., 2019. "Improving CFD wind farm simulations incorporating wind direction uncertainty," Renewable Energy, Elsevier, vol. 133(C), pages 1011-1023.
    6. Ducoin, A. & Shadloo, M.S. & Roy, S., 2017. "Direct Numerical Simulation of flow instabilities over Savonius style wind turbine blades," Renewable Energy, Elsevier, vol. 105(C), pages 374-385.
    7. Dose, B. & Rahimi, H. & Herráez, I. & Stoevesandt, B. & Peinke, J., 2018. "Fluid-structure coupled computations of the NREL 5 MW wind turbine by means of CFD," Renewable Energy, Elsevier, vol. 129(PA), pages 591-605.
    8. Til Kristian Vrana & Damian Flynn & Emilio Gomez‐Lazaro & Juha Kiviluoma & Davy Marcel & Nicolaos Cutululis & J. Charles Smith, 2018. "Wind power within European grid codes: Evolution, status and outlook," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 7(3), May.
    9. José F. Herbert-Acero & Oliver Probst & Pierre-Elouan Réthoré & Gunner Chr. Larsen & Krystel K. Castillo-Villar, 2014. "A Review of Methodological Approaches for the Design and Optimization of Wind Farms," Energies, MDPI, vol. 7(11), pages 1-87, October.
    10. Meng, Hang & Lien, Fue-Sang & Li, Li, 2018. "Elastic actuator line modelling for wake-induced fatigue analysis of horizontal axis wind turbine blade," Renewable Energy, Elsevier, vol. 116(PA), pages 423-437.
    11. Wang, Lin & Liu, Xiongwei & Kolios, Athanasios, 2016. "State of the art in the aeroelasticity of wind turbine blades: Aeroelastic modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 195-210.
    12. Borg, Michael & Shires, Andrew & Collu, Maurizio, 2014. "Offshore floating vertical axis wind turbines, dynamics modelling state of the art. part I: Aerodynamics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 1214-1225.
    13. Ederer, Nikolaus, 2014. "The right size matters: Investigating the offshore wind turbine market equilibrium," Energy, Elsevier, vol. 68(C), pages 910-921.
    14. Jie Tian & Dao Zhou & Chi Su & Mohsen Soltani & Zhe Chen & Frede Blaabjerg, 2017. "Wind Turbine Power Curve Design for Optimal Power Generation in Wind Farms Considering Wake Effect," Energies, MDPI, vol. 10(3), pages 1-19, March.
    15. 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.
    16. Sang Lee & Peter Vorobieff & Svetlana Poroseva, 2018. "Interaction of Wind Turbine Wakes under Various Atmospheric Conditions," Energies, MDPI, vol. 11(6), pages 1-15, June.
    17. Yang Huang & Decheng Wan, 2019. "Investigation of Interference Effects Between Wind Turbine and Spar-Type Floating Platform Under Combined Wind-Wave Excitation," Sustainability, MDPI, vol. 12(1), pages 1-30, December.
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    1. Li, Zhiguo & Gao, Zhiying & Dai, Yuanjun & Wen, Caifeng & Zhang, Liru & Wang, Jianwen, 2023. "Unsteady aeroelastic performance analysis for large-scale megawatt wind turbines based on a novel aeroelastic coupling model," Renewable Energy, Elsevier, vol. 218(C).

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