兆瓦级风电机组风力桨叶多学科设计优化  

Multidisciplinary optimization design on blades of MW wind turbine

作　　者：刘冠麟[1,2] 鄂加强[1] 张彬[1] 

机构地区：[1]湖南大学机械与运载工程学院,湖南长沙410082 [2]湖南涉外经济学院机械工程学院,湖南长沙410205

出　　处：《中南大学学报（自然科学版）》2013年第1期140-148,共9页Journal of Central South University:Science and Technology

基　　金：湖南省重点实验室开放基金资助项目(2011KFJJ001)

摘　　要：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Sptotal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.

关 键 词：风力桨叶 多学科优化设计 混沌优化算法 气动性能 

分 类 号：TM614[电气工程—电力系统及自动化] TK83[动力工程及工程热物理—流体机械及工程]