常规风力机叶片的优化设计都是从二维翼型开始的,且翼型总是以升阻比最大为优化目标。然而,二维翼型的升阻比最大和三维叶片的高风能利用率与低气动载荷有本质的不同,采用以往的叶片优化方法常常会在提高风能利用率的同时,使叶片所受的气动载荷也提高。针对这一问题,提出基于多岛遗传算法和动量叶素理论,在给定风况条件下,以加权风能利用率最高与气动载荷最小为目标函数,以叶片各个截面的翼型型线及扭角作为设计变量,对三维叶片开展多目标优化方法设计研究。并对某实际NREL Phase VI叶片进行优化设计,结果表明：在给定风况下相比原叶片,优化叶片在风能利用率提升了3.06%的基础上,叶根弯矩降低了11.68%。在变转速与变风况下,优化叶片的气动效率整体提升,叶根弯矩明显降低。
Abstract
The optimization design of conventional wind turbine blades starts from a two-dimensional airfoil, which always takes the maximum lift-drag ratio as the optimization goal. However, the maximum lift-drag ratio of a two-dimensional airfoil is fundamentally different from the high wind energy utilization rate and low aerodynamic load of the three-dimensional blade. The previous blade optimization methods often improves the utilization rate of wind energy and the aerodynamic load. In response to this problem, based on the multi-island genetic algorithm and the blade momentum element theory, this paper proposes that under a given wind condition, the objective function is to take the most weighted wind energy utilization rate and the least aerodynamic load as the objective function, the airfoil profile and the torsion angle as design variables to design and research the method of optimization with multiple objects on the three-dimensional long blade. The optimized design of an actual NREL Phase VI blade shows that compared with the original blade under a given wind condition, the optimized blade has a 3.1% increase in wind energy utilization and a 11.7% reduction in blade root bending moment. Under variable speed and variable wind conditions, the overall aerodynamic efficiency of the optimized blade is improved, and the blade root bending moment is significantly reduced.
关键词
风力机叶片 /
翼型优化 /
遗传算法 /
风能利用率 /
叶根弯矩
Key words
wind turbine blades /
airfoil optimization /
genetic algorithm /
wind energy utilization rate /
blade root bending moment
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