SavedAdd your journal

Journals / International Journal Of Renewable Energy Research / 2026 / Cilt: 3 Sayı: 3

New Approach to High-Fidelity Aerodynamic Design Optimization of a Wind Turbine Blade

Mohammad Hassan Djavareshkian
Amir Latifi Bidarouni
Mohammad Raza M.r.saber
Pages
725–734
Publication Date
2013-09-01
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The comparison of the results of this turbine with optimized one, illustrates a significant improvement in power factor.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:A new approach to high-fidelity aerodynamic design optimization of a wind turbine blade configuration is offered.
📊
Key Findings & Data:The Results which are obtained from 2D Computational Fluid Dynamics (CFD) have been utilized to train a Neural Network (NN).
💡
Conclusion & Impact:The comparison of the results of this turbine with optimized one, illustrates a significant improvement in power factor.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Wind turbine blade · NVD · BEM

Abstract

A new approach to high-fidelity aerodynamic design optimization of a wind turbine blade configuration is offered. This method combines Blade Element Momentum (BEM) theory with the high fidelity aerodynamic shape optimization of an airfoil. The chord length and the twist angle of the blade at various radiuses have been calculated by BEM. The Navier Stokes equations are solved to simulate both two and three dimensional flows. The Results which are obtained from 2D Computational Fluid Dynamics (CFD) have been utilized to train a Neural Network (NN). E387Eppler is used as the base cross section of the blade. In the process of airfoil optimization, Genetic Algorithm (GA) is coupled with trained NN to attain the best airfoil shape at each angle of the attack. The simulation and validation of the base wind turbine with calculated pitch angle, twist angle, chord profile and base airfoil have been performed. The comparison of the results of this turbine with optimized one, illustrates a significant improvement in power factor.

🔖

Cite This Article

Djavareshkian, M. H., Bidarouni, A. L., M.r.saber, M. R. (2013). New Approach to High-Fidelity Aerodynamic Design Optimization of a Wind Turbine Blade. International Journal Of Renewable Energy Research, Cilt: 3 Sayı: 3, 725–734. https://ajindex.com/articles/1653669

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (28)

  1. H. Sun, "Wind turbine airfoil design using response surface method", Journal of Mechanical Science and Technology, 25, 1335-1340, 2011
  2. R.K. Singh, M.R. Ahmed, M.A. Zullah, Y.-H. Lee, "Design of a low Reynolds number airfoil for small horizontal axis wind turbines", Renewable Energy, 42, 66-76, 2012
  3. A.F.P. Ribeiro, A.M. Awruch, H.M. Gomes, "An airfoil optimization technique for wind turbines", Applied Mathematical Modelling, 36, 4898-4907, 2012
  4. M. Endo, Wind Turbine Airfoil Optimization by Particle Swarm Method. Case Western Reserve University, 2011.
  5. J.C.C. Henriques, F. Marques da Silva, A.I. Estanqueiro, L.M.C. Gato, "Design of a new urban wind turbine airfoil using a pressure-load inverse method", Renewable Energy, 34, 2728-2734, 2009
  6. J.C. Jouhaud, P. Sagaut, M. Montagnac, J. Laurenceau, "A surrogate-model based multidisciplinary shape optimization method with application to a 2D subsonic airfoil", Computers & Fluids, 36, 520-529, 2007
  7. C. Yan, H. Kyle, P. Russell, L. Yongsheng, B. Lihui, "Design Optimization of a Vertical Axis Wind Turbine Using a Genetic Algorithm and Surrogate Models", in: 12th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference and 14th AIAA/ISSMO Multidisciplinary Conference, American Institute of Aeronautics and Astronautics, 2012. and Optimization
  8. S. Koziel, L. Leifsson, Airfoil Shape Optimization Using Modeling Variable-Fidelity Response Prediction, in: X.-S. Yang, S. Koziel (Eds.) Computational Optimization and Applications in Engineering and Industry, Springer Berlin Heidelberg, pp. 99-124, 2011 and Shape-Preserving
  9. C. Thumthae, T. Chitsomboon, "Optimal angle of attack for untwisted blade wind turbine", Renewable Energy, 34, 1279-1284, 2009
  10. B. Biegel, M. Juelsgaard, M. Kraning, S. Boyd, J. Stoustrup, "Wind turbine pitch optimization, in: Control Applications (CCA)", IEEE International Conference on, pp. 1327-1334, 2011
  11. R.K. Singh, M.R. Ahmed, "Blade design and performance testing of a small wind turbine rotor for low wind speed applications", Renewable Energy, 50, 812- 819, 2013
  12. M. Jureczko, M. Pawlak, A. Mężyk, "Optimisation of wind turbine blades", Journal of Materials Processing Technology, 167 463-471, 2005
  13. X. Liu, L. Wang, X. Tang, "Optimized linearization of chord and twist angle profiles for fixed-pitch fixed-speed wind turbine blades", Renewable Energy, 57, 111-119, 2013
  14. A. Sharifi, M.R.H. Nobari, "Prediction of optimum section pitch angle distribution along wind turbine blades", Energy Conversion and Management, 67, 342- 350, 2013
  15. M.O.L. Hansen, Aerodynamics of wind turbines [electronic resource], Earthscan, 2008.
  16. B. Bavanish, K. Thyagarajan, "Optimization of power coefficient on a horizontal axis wind turbine using bem theory", Renewable and Sustainable Energy Reviews, 26, 169-182, 2013
  17. J.R.P. Vaz, J.T. Pinho, A.L.A. Mesquita, "An extension of BEM method applied to horizontal-axis wind turbine design", Renewable Energy, 36, 1734-1740, 2011
  18. J.C. Dai, Y.P. Hu, D.S. Liu, X. Long, "Aerodynamic loads calculation and analysis for large scale wind turbine based on combining BEM modified theory with dynamic stall model", Renewable Energy, 36 1095-1104, 2011
  19. M. Djavareshkian, "A new NVD scheme in pressure- based finite-volume methods", 14th Aurtalasian Fluid Mechanics Conference, Adelaide University, Adelaide, Ausrtalia, pp. 339-342, 10-14 December,2001
  20. B.P. Leonard, "A survey of finite differences with upwinding for numerical modeling of the incompressible convection diffusion equation" in C. Taylor and K. Morgan leds Technices in Transient and Turbulent Flow, Pineridgequess, Swansea, U.K., 2, 1-35, 1981
  21. R.M. Hicks, P.A. Henne, "Wing Design by Numerical Optimization", Journal of Aircraft, 15 407-412, 1978
  22. R.L. Haupt, S.E. Haupt, Practical Genetic Algorithms, A John Wiley & Sons, Inc., Publication, 2004.
  23. M.T. Hagan, H.B. Demuth, M. Beale, Neural network design, PWS Publishing Co., 1996.
  24. Y. Hao, M.W. Bogdan, Levenberg?Marquardt Training, in: Intelligent Systems, CRC Press, 2011, pp. 1-16.
  25. Experimental data base for computer program assessment, in, tech.rep.,AGARD.
  26. H. Sun, "Wind turbine airfoil design using response surface method", Journal of Mechanical Science and Technology, 25, 1335-1340, 2011
  27. B. Bavanish, K. Thyagarajan, "Optimization of power coefficient on a horizontal axis wind turbine using bem theory", Renewable and Sustainable Energy Reviews, 26, 169-182, 2013
  28. M. Djavareshkian, "A new NVD scheme in pressure- based finite-volume methods", 14th Aurtalasian Fluid Mechanics Conference, Adelaide University, Adelaide, Ausrtalia, pp. 339-342, 10-14 December,2001