Multi-objective differential evolution optimization based on uniform decomposition for wind turbine blade design

Wind turbine blade design is a complicated multi-objective optimization task. In this article, a novel gradient-based multi-objective evolution algorithm based on both uniform decomposition and differential evolution is proposed for the design of wind turbine blades, to overcome unsatisfactory conve...

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Veröffentlicht in:	Energy (Oxford) Jg. 120; S. 346 - 361
Hauptverfasser:	Wang, Long, Wang, Tongguang, Wu, Jianghai, Chen, Guoping
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Oxford Elsevier Ltd 01.02.2017 Elsevier BV
Schlagworte:	Algorithms blades Convergence Decomposition Design Design optimization Differential evolution Evolutionary algorithms Exploration Multi-objective optimization Multiple objective analysis Population distribution Studies Turbine blades Turbines Uniform decomposition Wind power Wind turbine design Wind turbines Differential evolution Multi-objective optimization Wind turbine design Uniform decomposition
ISSN:	0360-5442, 1873-6785
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Abstract	Wind turbine blade design is a complicated multi-objective optimization task. In this article, a novel gradient-based multi-objective evolution algorithm based on both uniform decomposition and differential evolution is proposed for the design of wind turbine blades, to overcome unsatisfactory convergence performance and diversity of solutions usually existing in conventional evolution algorithms. A uniform decomposition mechanism is developed to achieve homogeneous discretion of the objective space for the purpose of controlling population distribution. Meanwhile, a differential evolution mechanism based on neighbourhood and gradient is developed to achieve exploration-exploitation balance and enhance optimization efficiency of the algorithm proposed. Two-objective, three-objective, and four-objective optimizations for the 1.5 MW wind turbine blade designs reveal that the proposed algorithm exhibits improved distribution, convergence, and converging efficiency compared to the conventional evolution algorithms such as NSGA-II. Additionally, the improvements are more significant with more objectives involved, demonstrating that the proposed algorithm can serve as a universal, high performance algorithm for the multi-objective optimization of wind turbine blade design. •A novel multi-objective evolution algorithm proposed for wind turbine blade design.•Uniform decomposition developed and used in wind turbine design for first time.•A gradient-based differential evolution for enhancing optimization efficiency.•Two-to four-objective blade optimizations successfully conducted.•High-performance blades obtained through the proposed optimization method.
AbstractList	Wind turbine blade design is a complicated multi-objective optimization task. In this article, a novel gradient-based multi-objective evolution algorithm based on both uniform decomposition and differential evolution is proposed for the design of wind turbine blades, to overcome unsatisfactory convergence performance and diversity of solutions usually existing in conventional evolution algorithms. A uniform decomposition mechanism is developed to achieve homogeneous discretion of the objective space for the purpose of controlling population distribution. Meanwhile, a differential evolution mechanism based on neighbourhood and gradient is developed to achieve exploration-exploitation balance and enhance optimization efficiency of the algorithm proposed. Two-objective, three-objective, and four-objective optimizations for the 1.5 MW wind turbine blade designs reveal that the proposed algorithm exhibits improved distribution, convergence, and converging efficiency compared to the conventional evolution algorithms such as NSGA-II. Additionally, the improvements are more significant with more objectives involved, demonstrating that the proposed algorithm can serve as a universal, high performance algorithm for the multi-objective optimization of wind turbine blade design. Wind turbine blade design is a complicated multi-objective optimization task. In this article, a novel gradient-based multi-objective evolution algorithm based on both uniform decomposition and differential evolution is proposed for the design of wind turbine blades, to overcome unsatisfactory convergence performance and diversity of solutions usually existing in conventional evolution algorithms. A uniform decomposition mechanism is developed to achieve homogeneous discretion of the objective space for the purpose of controlling population distribution. Meanwhile, a differential evolution mechanism based on neighbourhood and gradient is developed to achieve exploration-exploitation balance and enhance optimization efficiency of the algorithm proposed. Two-objective, three-objective, and four-objective optimizations for the 1.5 MW wind turbine blade designs reveal that the proposed algorithm exhibits improved distribution, convergence, and converging efficiency compared to the conventional evolution algorithms such as NSGA-II. Additionally, the improvements are more significant with more objectives involved, demonstrating that the proposed algorithm can serve as a universal, high performance algorithm for the multi-objective optimization of wind turbine blade design. •A novel multi-objective evolution algorithm proposed for wind turbine blade design.•Uniform decomposition developed and used in wind turbine design for first time.•A gradient-based differential evolution for enhancing optimization efficiency.•Two-to four-objective blade optimizations successfully conducted.•High-performance blades obtained through the proposed optimization method.
Author	Wang, Long Chen, Guoping Wu, Jianghai Wang, Tongguang
Author_xml	– sequence: 1 givenname: Long orcidid: 0000-0002-5805-6862 surname: Wang fullname: Wang, Long email: longwang@nuaa.edu.cn – sequence: 2 givenname: Tongguang surname: Wang fullname: Wang, Tongguang – sequence: 3 givenname: Jianghai surname: Wu fullname: Wu, Jianghai – sequence: 4 givenname: Guoping surname: Chen fullname: Chen, Guoping
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Keywords	Differential evolution Multi-objective optimization Wind turbine design Uniform decomposition
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Snippet	Wind turbine blade design is a complicated multi-objective optimization task. In this article, a novel gradient-based multi-objective evolution algorithm based...
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SubjectTerms	Algorithms blades Convergence Decomposition Design Design optimization Differential evolution Evolutionary algorithms Exploration Multi-objective optimization Multiple objective analysis Population distribution Studies Turbine blades Turbines Uniform decomposition Wind power Wind turbine design Wind turbines
Title	Multi-objective differential evolution optimization based on uniform decomposition for wind turbine blade design
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