A Hybrid BEM-CFD Virtual Blade Model to Predict Interactions between Tidal Stream Turbines under Wave Conditions

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 aime...

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Main Authors: Nicolo’ Lombardi, Stephanie Ordonez-Sanchez, Stefania Zanforlin, Cameron Johnstone
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Journal of Marine Science and Engineering
Subjects:
Online Access:https://www.mdpi.com/2077-1312/8/12/969
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author Nicolo’ Lombardi
Stephanie Ordonez-Sanchez
Stefania Zanforlin
Cameron Johnstone
author_facet Nicolo’ Lombardi
Stephanie Ordonez-Sanchez
Stefania Zanforlin
Cameron Johnstone
author_sort Nicolo’ Lombardi
collection DOAJ
description 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 1.5<i>D</i> 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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spelling doaj.art-494e66563e26433489d986031759a0d62023-11-20T22:33:35ZengMDPI AGJournal of Marine Science and Engineering2077-13122020-11-0181296910.3390/jmse8120969A Hybrid BEM-CFD Virtual Blade Model to Predict Interactions between Tidal Stream Turbines under Wave ConditionsNicolo’ Lombardi0Stephanie Ordonez-Sanchez1Stefania Zanforlin2Cameron Johnstone3Department of Energy, Systems, Territory and Constructions Engineering, University of Pisa, 56122 Pisa, ItalyEnergy Systems Research Unit, University of Strathclyde, Glasgow G1 1XJ, UKDepartment of Energy, Systems, Territory and Constructions Engineering, University of Pisa, 56122 Pisa, ItalyEnergy Systems Research Unit, University of Strathclyde, Glasgow G1 1XJ, UKTidal 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 1.5<i>D</i> 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.https://www.mdpi.com/2077-1312/8/12/969CFDVirtual Blade Modelhorizontal axis tidal turbineBEMwake interactionsoffset
spellingShingle Nicolo’ Lombardi
Stephanie Ordonez-Sanchez
Stefania Zanforlin
Cameron Johnstone
A Hybrid BEM-CFD Virtual Blade Model to Predict Interactions between Tidal Stream Turbines under Wave Conditions
Journal of Marine Science and Engineering
CFD
Virtual Blade Model
horizontal axis tidal turbine
BEM
wake interactions
offset
title A Hybrid BEM-CFD Virtual Blade Model to Predict Interactions between Tidal Stream Turbines under Wave Conditions
title_full A Hybrid BEM-CFD Virtual Blade Model to Predict Interactions between Tidal Stream Turbines under Wave Conditions
title_fullStr A Hybrid BEM-CFD Virtual Blade Model to Predict Interactions between Tidal Stream Turbines under Wave Conditions
title_full_unstemmed A Hybrid BEM-CFD Virtual Blade Model to Predict Interactions between Tidal Stream Turbines under Wave Conditions
title_short A Hybrid BEM-CFD Virtual Blade Model to Predict Interactions between Tidal Stream Turbines under Wave Conditions
title_sort hybrid bem cfd virtual blade model to predict interactions between tidal stream turbines under wave conditions
topic CFD
Virtual Blade Model
horizontal axis tidal turbine
BEM
wake interactions
offset
url https://www.mdpi.com/2077-1312/8/12/969
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