Optimizing wind turbine blade performance: A multi-objective approach for power, load and stall characteristics

Siyuan Wu, Chang Cai, Lei Zhang, Zhiqiang Hu, Xiangyu Sun, Xiaohui Zhong, Chaoyi Peng, Keqilao Meng, Jianyu Kou and Li, Qing’an

Energy, 2025, vol. 331, issue C

Abstract: Ultra-long flexible wind turbine blades are essential for advancing large-scale and offshore wind energy projects. Despite significant progress, optimizing these blades remains a complex challenge due to the need to balance multiple performance objectives simultaneously. In this study, we developed a multi-objective optimization approach for wind turbine blade design that quantitatively addresses power, load, and stall characteristics. To validate the methodology, it was applied to the design of a 2MW wind turbine blade, and the optimized design was compared with a base blade. Sensitivity analysis of the optimization weight parameters was also conducted to enhance the robustness of the approach. The results indicate notable improvements in key performance metrics, including a 1.7% increase in average power generation, a 2.1% reduction in the maximum flap-wise moment at the blade root, and a 1.5°decrease in the running angle of attack. Moreover, the critical tip speed ratio (TSR) decreased by 0.6, aligning with the stall angle and indicating enhanced stall performance. This study not only demonstrates the effectiveness of the multi-objective coupling optimization method but also introduces innovative techniques for stall risk assessment and optimal TSR control, thereby contributing to the advancement of wind turbine blade design.

Keywords: Wind turbine; Blade design; Multi-objective optimization; Genetic algorithm; Stall assessment (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:331:y:2025:i:c:s0360544225025137

DOI: 10.1016/j.energy.2025.136871

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