Variable-fidelity shape optimization of dual-rotor wind turbines. Issue 7 (17th October 2018)

• Record Type: Journal Article
• Authors: Thelen, Andrew; Leifsson, Leifur; Sharma, Anupam; Koziel, Slawomir
• Is Part Of: Engineering computations. Volume 35:Issue 7(2018)
• Page Start: 2514
• Page End: 2542
• Publication Date: 2018-10-17
• Subjects: Design optimization -- RANS -- Wind power -- Dual-rotor wind turbine -- Rotor design -- Variable-fidelity modelling; Computer-aided engineering -- Periodicals; Computer graphics -- Periodicals; 620.00285
• DOI: 10.1108/EC-12-2017-0502
• Languages: English
• ISSNs: 0264-4401

Abstract

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.