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State of the Art in the Optimisation of Wind Turbine Performance Using CFD
- Source :
- Archives of Computational Methods in Engineering. 27:413-431
- Publication Year :
- 2019
- Publisher :
- Springer Science and Business Media LLC, 2019.
-
Abstract
- Wind energy has received increasing attention in recent years due to its sustainability and geographically wide availability. The efficiency of wind energy utilisation highly depends on the performance of wind turbines, which convert the kinetic energy in wind into electrical energy. In order to optimise wind turbine performance and reduce the cost of next-generation wind turbines, it is crucial to have a view of the state of the art in the key aspects on the performance optimisation of wind turbines using Computational Fluid Dynamics (CFD), which has attracted enormous interest in the development of next-generation wind turbines in recent years. This paper presents a comprehensive review of the state-of-the-art progress on optimisation of wind turbine performance using CFD, reviewing the objective functions to judge the performance of wind turbine, CFD approaches applied in the simulation of wind turbines and optimisation algorithms for wind turbine performance. This paper has been written for both researchers new to this research area by summarising underlying theory whilst presenting a comprehensive review on the up-to-date studies, and experts in the field of study by collecting a comprehensive list of related references where the details of computational methods that have been employed lately can be obtained.
- Subjects :
- Wind power
business.industry
Computer science
020209 energy
Applied Mathematics
Electric potential energy
Computer Science Applications1707 Computer Vision and Pattern Recognition
02 engineering and technology
Computational fluid dynamics
Turbine
Field (computer science)
Computer Science Applications
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Optimisation algorithm
State (computer science)
business
Marine engineering
Subjects
Details
- ISSN :
- 18861784 and 11343060
- Volume :
- 27
- Database :
- OpenAIRE
- Journal :
- Archives of Computational Methods in Engineering
- Accession number :
- edsair.doi.dedup.....13c781fa89efda3784b1a7db20304435
- Full Text :
- https://doi.org/10.1007/s11831-019-09316-0