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

WANG Long; WANG Tong-guang; LUO Yuan

doi:10.3879/j.issn.1000-0887.2011.06.006

Volume 32 Issue 6

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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

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

doi: 10.3879/j.issn.1000-0887.2011.06.006

Jiangsu Key Laboratory of Hi-Tech Research for Wind Turbine Design, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, P. R. China

Received Date: 2011-01-15
Rev Recd Date: 2011-04-14
Publish Date: 2011-06-15

Abstract

Abstract

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.
- wind turbine,
- multi-objective optimization,
- Pareto-optimal solutions,
- NSGA-Ⅱ

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References(20)

References

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