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Variable-fidelity shape optimization of dual-rotor wind turbines

Abstract

Purpose Dual-rotor wind turbines (DRWTs) are a novel type of wind turbines that can capture more power than their single-rotor counterparts. Because their surrounding flow fields are complex, evaluating a DRWT design requires accurate predictive simulations, which incur high computational costs. Currently, there does not exist a design optimization framework for DRWTs. Since the design optimization of DRWTs requires numerous model evaluations, the purpose of this paper is to identify computationally efficient design approaches. Design/methodology/approach Several algorithms are compared for the design optimization of DRWTs. The algorithms vary widely in approaches and include a direct derivative-free method, as well as three surrogate-based optimization methods, two approximation-based approaches and one variable-fidelity approach with coarse discretization low-fidelity models. Findings The proposed variable-fidelity method required significantly lower computational cost than the derivative-free and approximation-based methods. Large computational savings come from using the time-consuming high-fidelity simulations sparingly and performing the majority of the design space search using the fast variable-fidelity models. Originality/value Due the complex simulations and the large number of designable parameters, the design of DRWTs require the use of numerical optimization algorithms. This work presents a novel and efficient design optimization framework for DRWTs using computationally intensive simulations and variable-fidelity optimization techniques.

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Category:
Articles
Type:
artykuł w czasopiśmie wyróżnionym w JCR
Published in:
ENGINEERING COMPUTATIONS no. 35, pages 2514 - 2542,
ISSN: 0264-4401
Language:
English
Publication year:
2018
Bibliographic description:
Andrew T., Leifur L., Anupam S., Kozieł S.: Variable-fidelity shape optimization of dual-rotor wind turbines// ENGINEERING COMPUTATIONS. -Vol. 35, nr. 7 (2018), s.2514-2542
DOI:
Digital Object Identifier (open in new tab) 10.1108/ec-12-2017-0502
Verified by:
Gdańsk University of Technology

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