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Wind turbine design through evolutionary algorithms based on surrogate CFD methods

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Abstract

An automatic design environment using evolutionary techniques has been developed for the design of Horizontal Axis Wind Turbine (HAWT) blades taking into account both the aerodynamics and the structural constraints of the blades. This design environment is based on a simple, fast, and robust aerodynamic simulator intended for the prediction of the performance of any turbine blade produced as an intermediate individual of the evolutionary search process. In order to reduce the computational costs, the results obtained by this simple simulator have been corrected through the application of Artificial Neural Network (ANN) based approximations. An additional stress analysis stage has been introduced in order to take into account the structural resistance of the blades as a constraint throughout the optimization process. Results of the simulations obtained using this technique, of the application of the automatic design procedure and of the performance of the wind turbines thus produced are presented. In a first test case the rotor designed through the proposed method is compared to the one obtained analytically for a given air speed. This comparison to an analytical optimum provides a good index in order to evaluate the performance of the method. In a second case the rotor is optimized for a typical wind speed distribution, which is a more realistic scenario where the cost performance of the resulting turbines needs to be evaluated.

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References

  • Abbot H, Von Doenho AE (1949) Theory of wing sections. Dover, New York

    Google Scholar 

  • Amoignon O (2010) AESOP—a numerical platform for aerodynamic shape optimization. Optim Eng 11:555–581

    Article  MathSciNet  MATH  Google Scholar 

  • Benini E, Toffolo A (2002) Optimal design of horizontal-axis wind turbines using blade-element theory and evolutionary computation. J Sol Energy Eng 124:359–363

    Article  Google Scholar 

  • Betz A (1920) Eine erweiterung der schraubenstrahl-theorie. Z Flugtech Mot.luftschiffahrt (ZFM) 11:105–110

    Google Scholar 

  • Burger C, Hartfield R (2006) Wind turbine airfoil performance optimization using the vortex lattice method and a genetic algorithm. In: Proceedings of 4th AIAA energy conversion engineering conference, San Diego, CA. AIAA paper no 2006-4051

    Google Scholar 

  • Caamaño P (2011) Caracterización de espacios de calidad y algoritmos evolutivos en problemas de optimización con codificación real. PhD thesis, Universidade da Coruña, Spain

  • Díaz Casás V, Lopez Peña F, Duro RJ, Lamas A (2005) Automatic Aerodynamic Design of a wind turbine through evolutionary techniques. In: Proceedings of 3rd IEEE international workshop on intelligent data acquisition and advanced computing systems: technology and applications, Sofia, Bulgaria, pp 454–459

    Chapter  Google Scholar 

  • Glauert H (1922) An aerodynamic theory of the airscrew. Aeronautical Research Committee Reports and Memoranda 786, ARCRM (Aeronautical Research Committee, Reports and Memoranda), London, United Kingdom

  • Glauert H (1926) The elements of airfoil and airscrew theory. Cambridge University Press, Cambridge

    Google Scholar 

  • Goldstein S (1929) On the vortex theory of screw propellers. Proc Roy Soc Lond Math Phys Sci 123:440–465

    Article  MATH  Google Scholar 

  • Hansen MOL (2008) Aerodynamics of wind turbines. Earthscan/James & James, London

  • Head MR (AERONAUTICAL RESEARCH COUNCIL LONDON (England)) (1958) Entrainment in the turbulent boundary layer. Defense Technical Information Center

  • Hess JL (1990) Panel methods in computational fluid dynamics. Annu Rev Fluid Mech 22:255–274

    Article  Google Scholar 

  • Hess JL, Smith AMO (1967) Calculation of potencial flow about arbitrary bodies. Prog Aerosp Sci 8:1–138

    Article  MATH  Google Scholar 

  • Huyse L (2001) Free-form airfoil shape optimization under uncertainty using maximum expected value and second-order second-moment strategies. Institute for Computer Applications in Science and Engineering Report N 2001-18. CASE NASA Langley Research Center Hampton, Virginia

  • Jameson A (1988) Aerodynamic design via control theory. J Sci Comput 3:233–260

    Article  MATH  Google Scholar 

  • Marín J, Solé RV (1999) Macroevolutionary Algorithms: a new optimization method on fitness landscapes. IEEE Trans Evol Comput 4:272–286

    Article  Google Scholar 

  • Mengistu T, Ghaly W (2008) Aerodynamic optimization of turbomachinery blades using evolutionary methods and ANN-based surrogate models. Optim Eng 9:239–255

    Article  MathSciNet  MATH  Google Scholar 

  • Michel R (1951) Etude de la transition sur les profiles d’Aile. ONERA Report 1/1578A, Onera (Office National d’Etudes et Recherches Aérospatiales), France

  • Mohammadi B, Pironneau O (2001) Applied shape optimization for fluids. Oxford University Press, New York

    MATH  Google Scholar 

  • Montgomerie B (2004) Methods for root effects, tip effects and extending the angle of attack range ±180 deg, with application to aerodynamics for blades on wind turbines and propellers. Technical report, Swedish Defence Research Agency, Stockholm, Tech Rep FOI

  • Oyama A, Obayashi S, Nakahashi K, Nakamura T (2000) Aerodynamic optimization of transonic wing design based on evolutionary algorithm. In: Sivasundaram S (ed) Third international conference on nonlinear problems in aviation and aerospace, Daytona Beach, FL, USA, May 10–12

    Google Scholar 

  • Ozgener O (2006) A small wind turbine system (SWTS) application and its performance analysis. Energy Convers Manag 47:11–12, 1326-133,7

    Article  Google Scholar 

  • Peri D, Campana EF (2003) Multidisciplinary design optimization of a naval surface combatant. J Ship Res 47(1):1–12

    Google Scholar 

  • Prandtl L (1919) Tragflügeltheorie. Götinger Nachrichten, matematisch-physikalische Klasse. Translated to English (1921) as: Application of modern hydrodynamics to aeronautics. National Advisory Committee for Aeronautics Report N 116. US Government Printing Office

  • Squire HB, Young AD (1938) The calculation of the profile drag of aerofoils. His Majesty’s Stationery Office

  • Theodorsen T (1944) The theory of propellers. National Advisory Committee for Aeronautics Reports Ns 775, 776, 777 and 778. US Government Printing Office

  • Thwaites B (1952) On the momentum equation in laminar boundary layer flow. Aeronautical Research Committee Reports and Memoranda 2587, London

  • Weisser D (2003) A wind energy analysis of Grenada: an estimation using the Weibull density function. Renew Energy 28:1803–1812

    Article  Google Scholar 

  • Zhang G, Patuwo BE, Hu MY (1998) Forecasting with artificial neural networks: The state of the art. Int J Forecast 14:35–62

    Article  Google Scholar 

Download references

Acknowledgements

This work was partially funded by the Xunta de Galicia through project 10REM007CT and by the Spanish Ministry of Education under the MICIIN and Fondo Europeo de Desarrollo Regional FEDER project ENE2010-20680-C03-03.

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Authors and Affiliations

  1. Integrated Group for Engineering Research, University of Coruña, Ferrol, Spain

    Vicente Díaz-Casás, Jose-Antonio Becerra, Fernando Lopez-Peña & Richard J. Duro

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  1. Vicente Díaz-Casás
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  2. Jose-Antonio Becerra
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  3. Fernando Lopez-Peña
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  4. Richard J. Duro
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Correspondence to Vicente Díaz-Casás.

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Díaz-Casás, V., Becerra, JA., Lopez-Peña, F. et al. Wind turbine design through evolutionary algorithms based on surrogate CFD methods. Optim Eng 14, 305–329 (2013). https://doi.org/10.1007/s11081-012-9187-1

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