Abstract
This paper introduces a new airfoil series to optimize the aerodynamic shape of wind turbine blades. It is verified that the CQU-A airfoil series exhibits high aerodynamic performance by using the wind tunnel experimental data and RFOIL. The geometry of a 2 MW wind turbine blade with new airfoil families is designed preliminarily based on the shape of Tjaereborg 2 MW rotor. A multi-objective optimized model combining the maximum power coefficient of the wind turbine with minimum area of the blade surface is proposed for the pitch regulated wind turbine. An optimized code is developed based on the corrected blade element momentum (BEM) theory and particle swarm optimization (PSO) algorithm. The optimization results show that, compared with that of the original rotor and the Tjaereborg rotor, not only the power coefficient and annual power production is improved, but also the area of the blade surface is reduced. The decreased area indicates that the mass of the optimized blades is reduced. It is beneficial for increasing the fatigue life and reducing cost of composite materials if the internal structure of the wind turbine blades is unchanged. Furthermore, the load of the blade root is effectively controlled by using this alternative optimization program.
Similar content being viewed by others
References
P. Fuglsang and H. A. Madsen, Optimization method for wind turbine rotors, J. of Wind Engineering and Industrial Aerodynamics, 80 1999 191–206.
E. Benini and A. Toffolo, Optimal design of horizontalaxis wind turbine using blade-element theory and evolutionary computation, J. of Solar Energy Engineering, 124 2002 357–363.
[3] P. Fuglsang et al., Site-specific design optimization of wind turbines, Wind Energy, 5 2002 261–279.
B. Kamoun, A. Helali and D. Afungchui, Optimum project for horizontal axis wind turbines ‘OPHWT’, Renewable Energy, 30 2005 2019–2043.
W. Xudong et al., Shape optimization of wind turbine blades, Wind Energy, 12 2009 781–803.
[6] B. Kim et al., Aerodynamic design and performance analysis of multi-MW class wind turbine blade, JMST, 25 8 2011 1995–2002.
[7] J. Jeong et al., Design optimization of a wind turbine blade to reduce the fluctuating unsteady aerodynamic load in turbulent wind, JMST, 26 23 2012 827–838.
[8] S. Lee et al., Design optimization of wind turbine blades for reduction of airfoil self-noise, JMST, 27 2 2013 413–420.
X. Liu, L. Wang and X. Pang, Optimized linearization of chord and twist angle profiles for fixed-pitch fixed-speed wind turbine blades, Renewable Energy, 57 2013 111–119.
K. Maki and R. Sbragio, N. Vlahopoulos, System design of a wind turbine using a multi-level optimization approach, Renewable Energy, 43 2012 101–110.
H. I. Kwon, J. Y. You and O. J. Kwon, Enhancement of wind turbine aerodynamic performance by a numerical optimization technique, JMST, 26 2 2012 455–462.
Y. Nam, J. Kim and C. L. Bottasso, Maximal power extraction strategy in the transition region and its benefit on the AEP (Annul energy product), JMST, 25 6 2011 1613–1619.
M. Jureczko, M. Pawlak and A. Mezyk, Optimisation of wind turbine blades, J. of Materials Processing Technology, 167 2005 463–471.
C. C. Liao, X. L. Zhao and J. Z. Xu, Blade layers optimization of wind turbines using FAST and improved PSO Algorithm, Renewable Energy, 42 2012 227–233.
[15] H. Glauert, Airplane propellers, In Aerodynamic Theory, Durand Wf(ed.), Dover: New York (1963) 169–360.
[16] M. Hansen, Aerodynamic of wind turbines, Earthscan (2008).
W. Z. Shen, R. Mikkelsen, J. N. Sørensen and C. H. Bak, Tip loss correction for wind turbine computations, Wind Energy, 8 2005 457–475.
[18] J. Chen et al., Improvement of airfoil design using smooth curvature technique, Renewable Energy, 51 2013 426–435.
W. A. Timmer and A. P. Schaffarczyk, The effect of roughness at high reynolds numbers on the performance of aerofoil DU 97-W-300Mod, Wind Energy, 136 2004 295–30.
W. A. Timmer and V. T. Prjom, Summary of the delft university wind turbine dedicated airfoils, J. of Solar Energy Engineering, 125 2003 488–496.
J. Kennedy and R. Ebcrhart, Particle swarm optimization, Proceedings of the IEEE Intemational Conference on Neural Networks (1995) 1942–1948.
Y. Shi and R. Eberhart, Modified particle swarm optimizer. In Proceedings of the IEEE international conference on evolutionary computation, Piscataway, IEEE (1998) 69–73.
A. Chatterjee and P. Siarry, Nonlinear inertia weight variation for dynamic adaptation in particle swarm optimization, Computers and Operations Research, 33 3 2006 859–871.
Author information
Authors and Affiliations
Corresponding authors
Additional information
Recommended by Associate Editor Kyu Hong Kim
Quan Wang received his B.S. in Mechanical Engineering in 2007 from Yangtze University, his M.S. and Ph.D. in Mechanical Engineering in 2009 and 2013, respectively, from Chongqing University. He now does teaching and research related with mechanical work. His research interests cover mechanical system optimization design, aerodynamic and structural design of wind turbine blade.
Jun Wang is a professor in Mechanical Engineering at HuBei University of Technology. He received his B.S. in Aircraft Design from BeiJing University of Aeronautics and Astronautics (2002), and M.S. in Mechanical Engineering from Tennessee Technological University (2007) and his Ph.D. in Mechanical Engineering from Tennessee Technological University (2010). His research interests include mechanisms, robotics, manufacturing and renewable energy.
Rights and permissions
About this article
Cite this article
Wang, Q., Wang, J., Chen, J. et al. Aerodynamic shape optimized design for wind turbine blade using new airfoil series. J Mech Sci Technol 29, 2871–2882 (2015). https://doi.org/10.1007/s12206-015-0616-x
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12206-015-0616-x