scholarly journals Validation and accommodation of vortex wake codes for wind turbine design load calculations

2020 ◽  
Author(s):  
Anonymous
2020 ◽  
Vol 5 (2) ◽  
pp. 699-719 ◽  
Author(s):  
Koen Boorsma ◽  
Florian Wenz ◽  
Koert Lindenburg ◽  
Mansoor Aman ◽  
Menno Kloosterman

Abstract. The computational effort for wind turbine design load calculations is more extreme than it is for other applications (e.g., aerospace), which necessitates the use of efficient but low-fidelity models. Traditionally the blade element momentum (BEM) method is used to resolve the rotor aerodynamic loads for this purpose, as this method is fast and robust. With the current trend of increasing rotor size, and consequently large and flexible blades, a need has risen for a more accurate prediction of rotor aerodynamics. Previous work has demonstrated large improvement potential in terms of fatigue load predictions using vortex wake models together with a manageable penalty in computational effort. The present publication has contributed towards making vortex wake models ready for application to certification load calculations. The observed reduction in flapwise blade root moment fatigue loading using vortex wake models instead of the blade element momentum (BEM) method from previous publications has been verified using computational fluid dynamics (CFD) simulations. A validation effort against a long-term field measurement campaign featuring 2.5 MW turbines has also confirmed the improved prediction of unsteady load characteristics by vortex wake models against BEM-based models in terms of fatigue loading. New light has been shed on the cause for the observed differences and several model improvements have been developed, both to reduce the computational effort of vortex wake simulations and to make BEM models more accurate. Scoping analyses for an entire fatigue load set have revealed the overall fatigue reduction may be up to 5 % for the AVATAR 10 MW rotor using a vortex wake rather than a BEM-based code.


2020 ◽  
Author(s):  
Koen Boorsma ◽  
Florian Wenz ◽  
Koert Lindenburg ◽  
Mansoor Aman ◽  
Menno Kloosterman

Abstract. The computational effort for wind turbine design loads calculations is more extreme than it is for other applications (e.g. aerospace) which necessitates the use of efficient but low-fidelity models. Traditionally the Blade Element Momentum (BEM) method is used to resolve the rotor aerodynamics loads for this purpose, as this method is fast and robust. With the current trend of increasing rotor size, and consequently large and flexible blades, a need has risen for a more accurate prediction of rotor aerodynamics. Previous work has demonstrated large improvement potential in terms of fatigue load predictions using vortex wake models together with a manageable penalty in computational effort. The present publication has contributed towards making vortex wake models ready for application to certification load calculations. The observed reduction in flapwise blade root moment fatigue loading using vortex wake models instead of the Blade Element Momentum method from previous publications has been verified using a numerical wind tunnel, i.e. Computational Fluid Dynamics (CFD) simulations. A validation effort against a long term field measurement campaign featuring 2.5 MW turbines has also confirmed the improved prediction of unsteady load characteristics by vortex wake models against BEM based models in terms of fatigue loading. New light has been shed on the cause for the observed differences and several model improvements have been developed, both to reduce the computational effort of vortex wake simulations and to make BEM models more accurate. Scoping analyses for an entire fatigue load set have revealed the overall fatigue reduction may be up to 5 % for the AVATAR 10 MW rotor using a vortex wake rather than a BEM based code.


2012 ◽  
Vol 55 (3-4) ◽  
pp. 396-404 ◽  
Author(s):  
Tugrul U. Daim ◽  
Elvan Bayraktaroglu ◽  
Judith Estep ◽  
Dong Joon Lim ◽  
Jubin Upadhyay ◽  
...  
Keyword(s):  

2013 ◽  
Vol 7 (2) ◽  
pp. 170-177 ◽  
Author(s):  
Alessio Balleri ◽  
Allann Al‐Armaghany ◽  
Hugh Griffiths ◽  
Kinfai Tong ◽  
Takashi Matsuura ◽  
...  

Author(s):  
Wei Jun Zhu ◽  
Wen Zhong Shen ◽  
Jens Nørkær Sørensen

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