基于改进的粒子群算法的风力机叶片优化设计

Wind Turbine Blades Optimization Design based on Improved Partical Swarm Algorithm

基于有限叶片变环量气动计算模型,加入攻角随风速的变化处理,根据风电场中来流速度的概率分布,并以风力机最大年发电量为目标,建立优化模型,使用改进的粒子群算法进行搜索,寻找全局最优解。采用改进的粒子群算法设计的优化程序,设计了1.3MW定桨失速型风力机叶片,并与现有的风力机叶片作比较。优化后,风力机叶片的弦长明显减小,达到额定风速后的功率输出情况,也满足了定桨失速型风力机的功率控制要求,说明本文所述的优化设计方法的有效性和实用性。

Based on limited blades variable radical circulation distribution pneumatic computation module and according to the wind speed distribution change handle with the specific wind site,A optimization model was built with the reference of probability distribution of coming current speed in wind electric field and the finial objective of maximum windmill annual power generation,which using improved PSO algorithm to search global optimum relation. Adopted the optimization program designed by using improved PSO algorithm,designed the blade of 1.3 MW wind turbine,and compared with an existing 1.3 MW wind turbine. The results showed that after optimization,chord lengths of wind turbine blade decrease sharply, power output at specified wind speed satisfied the power output control requirement o{ constant blade distance wind turbine, which verified the validity and functionalities of the optimization model.