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

Year 2013, Volume: 3 Issue: 3, 725 - 734, 01.09.2013

Mohammad Hassan Djavareshkian Amir Latifi Bidarouni Mohammad Raza M.r.saber

https://izlik.org/JA36NJ22UF

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.

Keywords

Wind turbine blade; NN; GA; NVD; BEM

References

• H. Sun, "Wind turbine airfoil design using response surface method", Journal of Mechanical Science and Technology, 25 , 1335-1340, 2011
• 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
• A.F.P. Ribeiro, A.M. Awruch, H.M. Gomes, "An airfoil optimization technique for wind turbines", Applied Mathematical Modelling, 36, 4898-4907, 2012
• M. Endo, Wind Turbine Airfoil Optimization by Particle Swarm Method. Case Western Reserve University, 2011.
• 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
• 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
• 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
• 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
• C. Thumthae, T. Chitsomboon, "Optimal angle of attack for untwisted blade wind turbine", Renewable Energy, 34, 1279-1284, 2009
• 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
• 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
• M. Jureczko, M. Pawlak, A. Mężyk, "Optimisation of wind turbine blades", Journal of Materials Processing Technology, 167 463-471, 2005
• 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
• 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
• M.O.L. Hansen, Aerodynamics of wind turbines [electronic resource], Earthscan, 2008.
• 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
• 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
• 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
• 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
• 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
• R.M. Hicks, P.A. Henne, "Wing Design by Numerical Optimization", Journal of Aircraft, 15 407-412, 1978
• R.L. Haupt, S.E. Haupt, Practical Genetic Algorithms, A John Wiley & Sons, Inc., Publication, 2004.
• M.T. Hagan, H.B. Demuth, M. Beale, Neural network design, PWS Publishing Co., 1996.
• Y. Hao, M.W. Bogdan, Levenberg?Marquardt Training, in: Intelligent Systems, CRC Press, 2011, pp. 1-16.
• Experimental data base for computer program assessment, in, tech.rep.,AGARD.