High-fidelity CFD simulations of two wind turbines in arrays using nonlinear frequency domain solution method

Win Naung, Shine; Nakhchi, Mahdi Erfanian; Rahmati, Mohammad

Abstract

Aerodynamics of a wind turbine within windfarms is strongly influenced by the wake of neighbouring turbines. In particular, the performance of a wind turbine can be dramatically reduced depending on its location in the wake region of an upstream turbine. A detailed investigation of the effect of the upstream turbine on the downstream turbine with respect to their distances is essential for the design and optimisation of wind farm layouts. Conventional time domain solution methods, such as Unsteady Reynolds Averaged Navier Stokes (URANS) based Computational Fluid Dynamics (CFD) model of wind turbines in arrays, can provide a detailed analysis of this interaction effect. These methods are, however, impractical due to a high computational cost required for modelling turbines in array configurations. In this paper, a novel modelling and computational method is proposed to simulate two wind turbines in arrays by considering them as a multi-stage turbine. A nonlinear frequency domain solution method is then employed to model flow nonlinearities due to their interactions. The distances between the turbines are varied, and the effects of the upstream wind turbine on the downstream one are thoroughly investigated. Extensive validations of the nonlinear frequency domain solution method against the conventional time domain solution method reveal that the proposed frequency domain solution method provides accurate results while reducing the computational cost by one to two orders of magnitude.

Citation

Win Naung, S., Nakhchi, M. E., & Rahmati, M. (2021). High-fidelity CFD simulations of two wind turbines in arrays using nonlinear frequency domain solution method. Renewable Energy, 174, 984-1005. https://doi.org/10.1016/j.renene.2021.04.067

• Journal Article Type: Article
• Acceptance Date: Apr 11, 2021
• Online Publication Date: Apr 22, 2021
• Publication Date: Aug 31, 2021
• Deposit Date: Oct 15, 2023
• Publicly Available Date: Oct 17, 2023
• Journal: Renewable Energy
• Print ISSN: 0960-1481
• Electronic ISSN: 1879-0682
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 174
• Pages: 984-1005
• DOI: https://doi.org/10.1016/j.renene.2021.04.067
• Public URL: https://uwe-repository.worktribe.com/output/11177129