Skip to main content
SpringerLink
Log in

A multi-objective optimization for HAWT blades design by considering structural strength

  • Published:
Journal of Mechanical Science and Technology Aims and scope Submit manuscript

Abstract

The challenge of wind turbine blade design is to balance the conflict between high capacity and heavy system loads introduced by the large scale rotor. To solve this problem, we present a multi-objective optimization method to maximize the Annual energy production (AEP) and minimize the blade mass. The well-known Blade element momentum (BEM) theory is employed to predict the aerodynamic performance and AEP of the blade. The blade is simplified as a thin Bernoulli beam. The cross section is modelled as a combination of composite layer, shear webs and spar caps typically. The strain of every cross section has been considered as a constraint to minimize the spar cap thickness for minimizing the blade mass. An improved genetic algorithm (NSGA-II) is applied to obtain the Pareto front set. Several solutions of the Pareto set are selected to compare with the reference blade (NREL 5MW blade). Performance of the rotors on design condition is simulated by STAR-CCM+ to verify the results of BEM theory. Optimal results show that the present blade, which is fully superior to the reference blade, can be selected from the Pareto set. The optimization design method can provide a superior blade with an increase by 2.48% of AEP and a reduction by 5.52% of the blade mass. It indicates the present optimization method is effective. Results of numerical simulations show that the spanwise flow would be increased obviously in tip region of the reference blade. The reason is that chord length variation in blade tip affects the flow and causes minor stall. The abrupt change of chord distribution in blade tip should be avoided to reduce the spanwise flow in initial blade design.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. B. Tony, Wind energy handbook, 2nd Ed., Wiley, New York, USA (2011).

    Google Scholar 

  2. C. Li, Z. Ye, W. G. Wei and Z. Jiang, Modern large-scale wind turbine design principe, Shanghai Scientific & Technology Publishers, Shanghai, China (2012).

    Google Scholar 

  3. M. S. Selig and L, Victoria, Application of a genetic algorithm to wind turbine design, J. of Energy Resources Technology, 118 (1) (1996) 22–28.

    Article  Google Scholar 

  4. P. Fuglsang and A. Madsen, Optimization method for wind turbine rotors, J. of Wind Engineering and Industrial Aerodynamics, 80 (1) (1999) 191–206.

    Article  Google Scholar 

  5. K. Jureczko, M. Pawlak and A. Mężyk, Optimisation of wind turbine blades, J. of Materials Processing Technology, 167 (2) (2005) 463–471.

    Article  Google Scholar 

  6. X. D. Wang, W. Z. Shen, W. J. Zhu and J. Chen, Shape optimization of wind turbine blades, Wind Energy, 12 (8) (2009) 781–803.

    Article  Google Scholar 

  7. G. Kenway and A. Martins, Aerostructural shape optimization of wind turbine blades considering site-specific winds, Proceedings of the 12th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Victoria, British Columbia, Canada (2008) 10–22.

    Google Scholar 

  8. J. Jeong, K. Park, S. Jun and D. H. Lee, Design optimization of a wind turbine blade to reduce the fluctuating unsteady aerodynamic load in turbulent wind, JMST, 26 (3) (2012) 827–838.

    Google Scholar 

  9. C. X. Yang, X. Lv, G. Tong and X. C. Song, Aerodynamic optimization design and calculation of a 2MW horizontal axial wind turbine rotor based on blade theory and particle swarm optimization, 2011 Power and Energy Engineering Conference of Asia-Pacific, Wuhan, Hebei, China (2011) 1–4.

    Google Scholar 

  10. W. Liu, W. Lin and X. Z. Tang, Optimized linearization of chord and twist angle profiles for fixed-pitch fixedspeed wind turbine blades, Renewable Energy, 57 (9) (2013) 111–119.

    Article  Google Scholar 

  11. S. Ahmad, M. Mirhosseini and Z. M. Moghimi, Aerodynamic design and economical evaluation of site specific horizontal axis wind turbine (HAWT), Energy Equipment and Systems, 2 (1) (2014) 43–56.

    Google Scholar 

  12. P. Giguere and M. S. Selig, Blade geometry optimization for the design of wind turbine rotors, Proceedings of AIAA/ASME Wind Energy Symposium, Nevada, USA (2000) 1–12.

    Google Scholar 

  13. E. Benini and T. Andrea, Optimal design of horizontalaxis wind turbines using blade-element theory and evolutionary computation, J. of Solar Energy Engineering, 124 (4) (2002) 357–363.

    Article  Google Scholar 

  14. R. W. Vesel and J. J. McNamara, Performance enhancement and load reduction of a 5 MW wind turbine blade, Renewable Energy, 66 (6) (2014) 391–401.

    Article  Google Scholar 

  15. R. Fischer, K. Timoleon and M. S. Anthony, Multiobjective optimisation of horizontal axis wind turbine structure and energy production using aerofoil and blade properties as design variables, Renewable Energy, 62 (2) (2014) 506–515.

    Article  Google Scholar 

  16. M. Sessarego, K. R. Dixon, D. E. Rival and D. H Wood, A A hybrid multi-objective evolutionary algorithm for windturbine blade optimization, Engineering Optimization, 47 (8) (2014) 1–20.

    MathSciNet  Google Scholar 

  17. X. Shen, J. G. Chen, X. C. Zhu, P. Y. Liu and Z. H. Du, Multi-objective optimization of wind turbine blades using lifting surface method, Energy, 90 (1) (2015) 1111–1121.

    Article  Google Scholar 

  18. Q. Wang, J. Wang, J. Chen, S. Luo and J. F. Sun, Aerodynamic shape optimized design for wind turbine blade using new airfoil series, Journal of Mechanical Science and Technology, 29 (7) (2015) 2871–2882.

    Article  Google Scholar 

  19. J. M. Jonkman, S. Butterfield, W. Musial and G. Scott, Definition of a 5-MW reference wind turbine for offshore system development, National Renewable Energy Laboratory, Colorado, USA (2009).

    Google Scholar 

  20. E. A. Bossanyi, GH Bladed user manual, Garrad Hassan and Partners Limited, Bristol, UK (2009).

    Google Scholar 

  21. J. Jonkman and B. Marshall, FAST user’s guide, National Renewable Energy Laboratory, Colorado, USA (2005).

    Google Scholar 

  22. M. O. Hansen, Aerodynamics of wind turbines, Routledge, New York, USA (2015).

    Google Scholar 

  23. D. M. Eggleston and S. Forrest, Wind turbine engineering design, Van Nostrand Reinhold, New York, USA (1987).

    Google Scholar 

  24. Z. H. Du and M. S. Selig, A 3-D stall-delay model for horizontal axis wind turbine performance prediction, Reno, Nevada, USA (1998).

    Book  Google Scholar 

  25. L. A. Viterna and R. D. Corrigan, Fixed pitch rotor performance of large horizontal axis wind turbines, Proceedings of the DOE/NASA Workshop on Large Horizontal Axis Wind Turbine, Cleveland, USA (1982).

    Chapter  Google Scholar 

  26. I. Troen and E. L. Petersen, European wind atlas, Risø National Laboratory, Roskilde, Denmark (1989).

    Google Scholar 

  27. D. T. Griffith and D. A. Thomas, The Sandia 100-meter all-glass baseline wind turbine blade: SNL100-00, Sandia National Laboratories, Livermore, California, USA (2011).

    Google Scholar 

  28. L. Librescu and S. Ohseop, Thin-walled composite beams: theory and application, Springer, Berlin, German (2006).

    MATH  Google Scholar 

  29. K. Deb, A. Pratap, S. Agarwal and T. Meyarivan, A A fast and elitist multiobjective genetic algorithm: NSGA-II, Evolutionary Computation, 6 (2) (2002) 182–197.

    Article  Google Scholar 

  30. K. Deb and G. Tushar, Controlled elitist non-dominated sorting genetic algorithms for better convergence, Evolutionary Multi-Criterion Optimization, Springer Berlin, Berlin (2001).

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China

    Yang Yang, Chun Li, Wanfu Zhang, Jun Yang, Zhou Ye, Weipao Miao & Kehua Ye

  2. Shanghai Key Laboratory of Multiphase Flow and Heat Transfer in Power Engineering, Shanghai, 200093, China

    Chun Li, Wanfu Zhang, Jun Yang & Zhou Ye

Authors
  1. Yang Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chun Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wanfu Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jun Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Zhou Ye
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Weipao Miao
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Kehua Ye
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chun Li.

Additional information

Recommended by Associate Editor Beomkeun Kim

Yang Yang is a Ph.D. candidate at the University of Shanghai for Science and Technology. His research area is wind turbine blade design.

Chun Li is currently a Professor at the University of Shanghai for Science and Technology. His research fields include the flow control of wind farms, stall of VAWT and aeroelasticity of wind turbines.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yang, Y., Li, C., Zhang, W. et al. A multi-objective optimization for HAWT blades design by considering structural strength. J Mech Sci Technol 30, 3693–3703 (2016). https://doi.org/10.1007/s12206-016-0731-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12206-016-0731-3

Keywords

Search

Navigation