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Wind Energy Science The interactive open-access journal of the European Academy of Wind Energy
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https://doi.org/10.5194/wes-2019-47
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-2019-47
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  08 Aug 2019

08 Aug 2019

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This preprint was under review for the journal WES. A final paper is not foreseen.

Study on Multi-Objective Optimization Design and Passive Control of Wind Turbine Airfoil

Yong Peng1, Jun Wang1,2, Wei Wang2, and Guoqing Yin1 Yong Peng et al.
  • 1China-EU Institute for Clean and Renewable Energy, Huazhong University of Science and Technology, Wuhan, 430074, China
  • 2School of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China

Abstract. In this paper, the class-shape function transform (CST) parametric method is used to parameterize the airfoil configuration, and a new airfoil is randomly generated within a limited range. The 2D Reynolds-Averaged Navier-Stokes (RANS) computational fluid dynamics (CFD) solver is used to compute the quantities such as lift-to-drag ratio. The multi-objective genetic algorithm performs multi-objective optimization design on the airfoil plane shape to achieve high lift-to-drag ratio with low drag in operating ranges of angle of attack, and finally obtains the Pareto optimal solution set. The mixed function of index method is used to increase the thickness of the trailing edge of the airfoil. From the multi-objective solutions and blunt trailing edge solutions which represent the best trade-offs between the design objectives, one can select a set of airfoil shapes with a low relative drag force and with improved aerodynamic performance. Taking a typical airfoil NACA4418 as an example. The results show that the optimized airfoil has a better pressure distribution than the original airfoil, effectively increasing the lift coefficient and reducing the drag coefficient. After thickening the trailing edge of the optimized airfoil, the results show that the lift coefficient is improved at all angles of attack and the stall is delayed. And the blunt trailing edge airfoil has better lift-to-drag characteristics than the original airfoil and the optimized airfoil.

This preprint has been withdrawn.

Yong Peng et al.

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Yong Peng et al.

Yong Peng et al.

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Short summary
In this paper, the multi-objective genetic algorithm is coupled with the class shape transform method to optimize the wind turbine airfoil, and the trailing edge is thickened for the optimized airfoil. The results show that the lift coefficient and lift-to-drag ratio are improved at all angles of attack and the stall is delayed. And the blunt trailing edge airfoil has better lift-to-drag characteristics than the original airfoil and the optimized airfoil.
In this paper, the multi-objective genetic algorithm is coupled with the class shape transform...
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