WANG Long, WANG Tong-guang, LUO Yuan. Improved NSGA-Ⅱ in Multi-Objective Optimization Studies of Wind Turbine Blades[J]. Applied Mathematics and Mechanics, 2011, 32(6): 693-701. doi: 10.3879/j.issn.1000-0887.2011.06.006
Citation: WANG Long, WANG Tong-guang, LUO Yuan. Improved NSGA-Ⅱ in Multi-Objective Optimization Studies of Wind Turbine Blades[J]. Applied Mathematics and Mechanics, 2011, 32(6): 693-701. doi: 10.3879/j.issn.1000-0887.2011.06.006

Improved NSGA-Ⅱ in Multi-Objective Optimization Studies of Wind Turbine Blades

doi: 10.3879/j.issn.1000-0887.2011.06.006
  • Received Date: 2011-01-15
  • Rev Recd Date: 2011-04-14
  • Publish Date: 2011-06-15
  • The non-dominated sorting genetic algorithm was improved with controlled elitism and dynamic crowding distance,obtaining a novel multi-objective optimization design algorithm for wind turbine blades.As an example,a 5 MW wind turbine blade design,taking maximum power coefficient and minimum blade mass as the optimization objectives,was presented.It is illustrated from the optimal results that this algorithm has a good performance in handling multi-objective optimization of wind turbine and it gives a Pareto-optimal solutions set rather than the optimum solution from the conventional multi-objective optimization problems.The wind turbine blade optimization method presented provides a new idea and general algorithm for multi-objective optimization of wind turbine.
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