Metaheuristic Optimization of Wind Turbine Airfoils with Maximum-Thickness and Angle-of-Attack Constraints

Jinane Radi (), Jesús Enrique Sierra-García (), Matilde Santos (), Carlos Armenta-Déu and Abdelouahed Djebli
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Jinane Radi: Energetic Laboratory, Department of Physics, University of Abdelmalek Saadi, Tetouan 93002, Morocco
Jesús Enrique Sierra-García: Department of Digitalization, University of Burgos, 09001 Burgos, Spain
Matilde Santos: Institute of Knowledge Technology, University Complutense of Madrid, 28040 Madrid, Spain
Carlos Armenta-Déu: Faculty of Physics Sciences, University Complutense of Madrid, 28040 Madrid, Spain
Abdelouahed Djebli: Energetic Laboratory, Department of Physics, University of Abdelmalek Saadi, Tetouan 93002, Morocco

Energies, 2024, vol. 17, issue 24, 1-21

Abstract: The shape of the blade strongly influences the aerodynamic behavior of wind turbines; therefore, it is essential to optimize its design to maximize the energy harvested from the wind. Some works address this optimized design problem using CFD, a tool that requires a lot of computational resources and time and starts from scratch. This work describes a new automated design method to generate aerodynamic profiles of wind turbines using existing blades as a base, which speeds up the design process. The optimization is performed using heuristic techniques, and the aim is to improve the characteristics of the blade shape which impact resilience and durability. Specifically, the glide ratio is maximized to capture maximum energy while ensuring specific design parameters, such as maximum thickness or optimal angle of attack. This methodology can obtain results more quickly and with lower computational cost, in addition to integrating these two design parameters into the optimization process, aspects that have been largely neglected in previous works. The analytical model of the blades is described by a class of two-dimensional shapes suitable for representing airfoils. The drag and lift coefficients are estimated, and a metaheuristic optimization technique, genetic algorithm, is applied to maximize the glide ratio while reducing the difference from the desired design parameters. Using this methodology, three new airfoils have been generated and compared with the existing starting models, S823, NACA 2424, and NACA 64418, achieving improvements in the maximum lift and maximum glide ratio of up to 13.8% and 39%, respectively. For validation purposes, a small 10 kW horizontal-axis wind turbine is simulated using the best design of the blades. The comparison with the existing blades focuses on the calculation of the generated power, the power coefficient, torque, and torque coefficient. For the new airfoils, improvements of 6.7% in the power coefficient and 5.5% in the torque coefficient were achieved. This validates the methodology for optimizing the blade airfoils.

Keywords: airfoil; metaheuristic optimization; genetic algorithm; blade; wind turbine; wind energy (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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