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中文摘要：
一种结合了精英控制策略和动态拥挤距离方法的改进的快速支配排序算法（Fast and elitist non-dominat-ed sorting genetic algorithm,NSGA-Ⅱ）被用于风力机复杂的多目标优化设计中。作为此算法的应用算例,以风轮的年发电量最大、叶片的质量最小和叶片根部的极限推力最小为目标,分别进行了两目标和三目标的1.5 MW风力机叶片的优化设计。研究表明：两目标优化给出的Pareto最优解集分布在一条曲线上,而三目标的优化结果基本分布在一个有明显边界的五阶曲面上。同时也可以看出,此算法在处理风力机多目标优化问题取得了良好的效果,给出的是一个Pareto最优解集,而不是传统优化方法追求的单个最优解,为风力机多目标优化设计提供通用的算法。
英文摘要：
An improved fast and elitist non-dominated sorting genetic algorithm（NSGA-Ⅱ） incorporating controlled elitism and dynamic crowding distance strategies is applied in the field of multi-objective optimization design of wind turbine blades.As an example of the algorithm,taking the maximum annual energy production,the minimum blade mass,and the minimum blade root thrust as the optimization objectives,the 1.5 MW wind turbine blades are designed with both twoobjective and three-objective conditions.The results indicate that the Pareto-optimal solutions of two-objective conditions distribute on the curves,and the solutions of three-objective case are on a five-order surface with evident boundaries.Meanwhile,this algorithm gives a Pareto-optimal solution set rather than the particular optimum solution from the multi-objective design problems,which can provide a new idea for multi-objective optimization of wind turbine.
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