Optimization of aerodynamic and anti-flutter performance of wind turbine blade airfoils using a Hybrid Bi-Directional Cooperative Constrained Multi-Objective Evolutionary Algorithm

Hongjie Su, Jianlong Ma, Jianwen Wang, Zhiying Gao, Wenli Pan, Qiuyan Li and Long Yang

Energy, 2025, vol. 333, issue C

Abstract: To achieve optimal aerodynamic and anti-flutter performance of large wind turbine blades, and effectively address conventional optimization problems, this paper proposes method that combines a Hybrid Bi-Directional Cooperative Constrained Multi-Objective Evolutionary Algorithm (HBC-CMOEA) with an optimized Non-Uniform Rational B-Spline (NURBS) parameterization technique. This approach establishes a mathematical model aimed at optimizing the aerodynamic and anti-flutter performance of airfoils. The results reveal that the proposed HBC-CMOEA outperforms other seven state-of-the-art Constrained Multi-objective Evolutionary Algorithms (CMOEAs) in most test cases, demonstrating its superior capabilities. The optimization significantly enhanced the aerodynamic and anti-flutter performance of DU25 and DU21 airfoils used in the NREL 5 MW blade while adhering to the maximum airfoil thickness requirement. Additionally, the DU21 airfoil achieved a 17.5 % increase in the optimal lift-to-drag ratio and a 1.12 % increase in the polar moment of inertia compared with the original levels. Similarly, the DU25 airfoil exhibited a 17.9 % improvement in the optimal lift-to-drag ratio and a 1.4 % increase in the polar moment of inertia. This approach offers an effective and innovative solution for designing new airfoils, as well as safer, more efficient, and diverse options for designers of land and offshore wind turbine blades.

Keywords: Wind turbine airfoil; Multi-objective optimization; Aerodynamic performance; Anti-flutter performance (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:333:y:2025:i:c:s0360544225029792

DOI: 10.1016/j.energy.2025.137337

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