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A novel multi-objective optimization algorithm incorporating vector method and evolution strategies,referred as vector dominant multi-objective evolutionary algorithm(VD-MOEA),is developed and applied to the aerodynamic-structural integrative design of wind turbine blades.A set of virtual vectors are elaborately constructed,guiding population to fast move forward to the Pareto optimal front and dominating the distribution uniformity with high efficiency.In comparison to conventional evolution algorithms,VD-MOEA displays dramatic improvement of algorithm performance in both convergence and diversity preservation when handling complex problems of multi-variables,multi-objectives and multi-constraints.As an example,a 1.5 MW wind turbine blade is subsequently designed taking the maximum annual energy production,the minimum blade mass,and the minimum blade root thrust as the optimization objectives.The results show that the Pareto optimal set can be obtained in one single simulation run and that the obtained solutions in the optimal set are distributed quite uniformly,maximally maintaining the population diversity.The efficiency of VD-MOEA has been elevated by two orders of magnitude compared with the classical NSGA-II.This provides a reliable high-performance optimization approach for the aerodynamic-structural integrative design of wind turbine blade.
A novel multi-objective optimization algorithm incorporating vector method and evolution strategies, referred as vector dominant multi-objective evolutionary algorithm (VD-MOEA), is developed and applied to the aerodynamic-structural integrative design of wind turbine blades. A set of virtual vectors are elaborately constructed, guiding population to fast move forward to the Pareto optimal front and dominating the distribution uniformity with high efficiency. In contrast to conventional evolution algorithms, VD-MOEA displays dramatic improvement of algorithm performance in both convergence and diversity preservation when handling complex problems of multi-variables, multi-objectives and multi- constraints. As a example, a 1.5 MW wind turbine blade was subsequently designed taking the maximum annual energy production, the minimum blade mass, and the minimum blade root thrust as the optimization objectives.The results show that the Pareto optimal set can be obtained in one single simulation run and that the obtained solutions in the optimal set are distributed quite uniformly, maximally maintain the population diversity. The efficiency of VD-MOEA has been elevated by two orders of magnitude compared with the classical NSGA-II. This provides a reliable high-performance optimization approach for the aerodynamic-structural integrative design of wind turbine blade.