Optimal design of wind turbine airfoils based on functional integral and curvature smooth continuous theory

Abstract The current airfoil design methods are based on one point of design angle of attack, in order to seek the local maximum aerodynamic performance without considering the whole aerodynamic performance within continuous design angle of attack. Based on airfoil functional integral and complicated profile curvature smooth continuity theory, a novel airfoil design method considering continuous angle of attack is presented. It not only can make the aerodynamic force convergence, but also has the whole aerodynamic performance increased. A parametric optimal mathematical model of wind turbine airfoil profiles is established to maximum the overall high aerodynamic performance. The aerodynamic comparison of the WQ-B airfoil series which are designed considering continuous angle of attack and the WQ-A airfoil series which are designed without considering continuous angle of attack is analyzed. Meanwhile, the comparison of WQ-B210 airfoil and DU96-W-210 airfoil is studied. Compared with WQ-A210 airfoil and DU96-W-210 airfoil, the WQ-B airfoil series exhibit high aerodynamic performance, especially for the average lift coefficient and lift–drag ratio. At last, the WQ-B airfoil series are used to a real 2MW wind turbine blade. The results are shown that, compared with the actual blade, the new wind turbine blade exhibit better whole performance. This study verifies the feasibility for the novel design method. Moreover, it also indicates that the WQ-B airfoil series have broad generality and substitutability.

[1]  Christian Bak,et al.  Development of the Risø wind turbine airfoils , 2004 .

[2]  Baker Jonathon Paul,et al.  Experimental Analysis of Thick Blunt Trailing-Edge Wind Turbine Airfoils , 2006 .

[3]  Elia Daniele,et al.  An airfoil shape optimization technique coupling PARSEC parameterization and evolutionary algorithm , 2014 .

[4]  W. A. Timmer,et al.  Summary of the Delft University Wind Turbine Dedicated Airfoils , 2003 .

[5]  J. L. Tangler,et al.  NREL airfoil families for HAWTs , 1995 .

[6]  I. H. Abbott,et al.  Theory of Wing Sections , 1959 .

[7]  Yue Shi,et al.  A modified particle swarm optimizer , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[8]  A. Velazquez,et al.  Viscous–inviscid method for the simulation of turbulent unsteady wind turbine airfoil flow , 2002 .

[9]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[10]  B. I. Soemarwoto,et al.  Airfoil design and optimization methods: recent progress at NLR , 1999 .

[11]  Young-Ho Lee,et al.  Design of a low Reynolds number airfoil for small horizontal axis wind turbines , 2012 .

[12]  W. A. Timmer,et al.  Roughness Sensitivity Considerations for Thick Rotor Blade Airfoils , 2003 .

[13]  H. Sobieczky Parametric Airfoils and Wings , 1999 .

[14]  J. Anderson,et al.  Fundamentals of Aerodynamics , 1984 .

[15]  Xiaofeng Guo,et al.  Improvement of airfoil design using smooth curvature technique , 2013 .

[16]  Steen Krenk,et al.  Dynamic Stall Model for Wind Turbine Airfoils , 2007 .

[17]  Jin Chen,et al.  Design and validation of the high performance and low noise CQU-DTU-LN1 airfoils , 2014 .

[18]  A. Jahangirian,et al.  Airfoil shape parameterization for optimum Navier–Stokes design with genetic algorithm , 2007 .

[19]  Jens Nørkær Sørensen,et al.  Integrated airfoil and blade design method for large wind turbines , 2014 .