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| Optimization of low Reynolds number wind turbine airfoil under stochastic turbulence condition |
| Received:July 26, 2018 Revised:August 31, 2018 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7511/jslx20180726002 |
| KeyWord:wind turbine airfoil low Reynolds number stochastic turbulence multi-objective optimization surrogate model |
| Author | Institution |
| 唐新姿 |
湘潭大学 机械工程学院, 湘潭 |
| 李鹏程 |
湘潭大学 机械工程学院, 湘潭 |
| 陆鑫宇 |
湘潭大学 机械工程学院, 湘潭 |
| 彭锐涛 |
湘潭大学 机械工程学院, 湘潭 |
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| Abstract: |
| In order to improve the adaptability of small-scall wind turbines to stochastic turbulence conditions,the distribution of the angle of attack of the turbine blade airfoil under turbulence was analyzed based on the non-intrusive probabilistic collocation method.Using airfoil NACA0012 as the example,based on the Transition SST model,the Latin hypercube sampling,the Kriging model and the non-dominated sorting genetic algorithm NSGA-Ⅱ,the multi-objective optimization coupled with boundary layer transition prediction was carried out for high turbulence and low Reynolds number wind turbine airfoils.The results show that:The average wind energy capture efficiencies of the optimal airfoil at the design condition and the off-design condition increase by 3.01% and 4.76% respectively and the standard deviations decrease by 4.76% and 14.93% respectively,the turbulence adaptability of the optimal airfoil is enhanced.The proposed method provides a solution to match the airfoil design with the turbulent wind conditions,which provides an important reference for the design and application of low Reynolds number airfoil and small wind turbines under stochastic turbulence conditions. |
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