A hybrid BEM-CFD virtual blade model to predict interactions between tidal stream turbines under wave conditions

Lombardi, Nicolo and Ordonez-Sanchez, Stephanie and Zanforlin, Stefania and Johnstone, Cameron (2020) A hybrid BEM-CFD virtual blade model to predict interactions between tidal stream turbines under wave conditions. Journal of Marine Science and Engineering, 8 (12). 969. ISSN 2077-1312 (https://doi.org/10.3390/jmse8120969)

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Abstract

Tidal turbine array optimization is crucial for the further development of the marine sector. It has already been observed that tidal turbines within an array can be heavily affected by excessive aerodynamic interference, thus leading to performance deterioration. Small-scale experimental tests aimed at understanding the physical mechanisms of interaction and identifying optimal distances between machines can be found in the literature. However, often, the relatively narrow channels of laboratories imply high blockage ratios, which could affect the results, making them unreliable if extrapolated to full-scale cases. The main aim of this numerical study was to analyze the effects of the blockage caused by the laboratory channel walls in cases of current and also current surface waves. For this purpose, the performance predictions achieved for two turbines arranged in line for different lateral offsets in case of a typical laboratory scale were compared to the predictions obtained for a full scale, unconfined environment. The methodology consisted in the adoption a hybrid Blade Element Momentum–Computational Fluid Dynamics (BEM-CFD) approach, which was based on the Virtual Blade Model of ANSYS-Fluent. The results indicate that (1) the performance of a downstream turbine can increase up to 5% when this has a lateral separation of 1.5D from an upstream device in a full-scale environment compared to a misleading 15% calculated for the laboratory set-up, and (2) the relative fluctuations of power and thrust generated by waves are not significantly affected by the domain dimensions.

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