为了提高兆瓦级风电机组风力桨叶整体性能,以兆瓦级风电机组风力桨叶气动性能、质量、桨片根部的极限推力和噪声水平为目标函数建立多学科设计优化模型,并充分考虑各学科之间的耦合效应,采用自适应混沌优化算法对多学科设计优化模型进行求解.研究结果表明:兆瓦级风电机组风力桨叶风能利用系数Cp增加12.5％,质量M减小11.00％,桨叶根部的极限推力载荷F减少12.60％,噪声Stotal减小10.48％；兆瓦级风电机组风力桨叶翼型的升力系数和气动性能得到了较大优化.%In order to improve the whole performance of the blades of MW wind turbine, a multidisciplinary design optimization (MDO) model was established based on objective function such as aerodynamic performance, mass, blade root thrust and the level of noise. Based on the coupled effect between each subject, the blades of MW wind turbine were designed by using MDO based on self-adaptive chaotic optimization algorithm. The results show that for the blades of MW wind turbine, power coefficient increase by 12.50%, mass reduces by 11.00%, blade root thrust reduces by 12.60%, and the level of noise reduces by 10.48%. The lift coefficient and aerodynamic performance are greatly optimized.
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