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...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
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
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung: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.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:0360-5442
1873-6785
DOI:10.1016/j.energy.2016.11.087