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Ocean Engineering
Article
License: CC BY NC ND
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Ocean Engineering
Article . 2019 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Numerical models to predict the performance of tidal stream turbines working under off-design conditions

Authors: Ordonez-Sanchez, S.; Ellis, R.; Porter, K. E.; Allmark, M.; O'Doherty, T.; Mason-Jones, A.; Johnstone, C.;

Numerical models to predict the performance of tidal stream turbines working under off-design conditions

Abstract

As previously experienced by the wind industry, it is envisaged that tidal stream turbine blades will present misalignments or blade deformations over time as they are constantly working under harsh and highly unsteady environments. Blade misalignment will affect the power capture of a tidal stream turbine and if not detected in time could affect other components of the drive train. Therefore, the aim of this paper is to compare the use of two numerical modelling techniques to predict the performance of a tidal stream turbine working under off-design conditions, in this case, the misalignment of one or more blades. The techniques used in this study are Blade Element Momentum Theory and Computational Fluid Dynamics. The numerical models simulate the performance of a three-bladed horizontal axis tidal stream turbine with one or two blades offset from the optimum pitch setting. The simulations were undertaken at 1.0 m/s flow speeds. The results demonstrated that both unsteady BEMT and steady or transient CFD are able to predict power coefficients when there is a certain level of misalignment in one or even two blades. However, both techniques failed to accurately predict a loss of power performance at high rotational speeds

Country
United Kingdom
Related Organizations
Keywords

690, 330, Hydraulic engineering. Ocean engineering, 620, Mechanical engineering and machinery, TJ, TC

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Top 10%
Green
hybrid