Establishing confidence in predictions of fatigue loading for floating tidal turbines based on large-eddy simulations and unsteady blade element momentum

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

To optimise a tidal site for development, tidal stream turbines need to be placed within arrays with the spacing between turbines being critical to maximise energy yield whilst minimising expenses associated to cabling, mooring or maintenance. Turbines deployed downstream of other turbines are exposed to upstream turbine wakes. experiencing low velocities and high shear and turbulence which cause fatigue loads. Turbine loading due to these challenging conditions can be well-predicted using high-fidelity models such as Large-Eddy Simulation (LES). However, such models have a notable computational cost that prevents use for optimising the location of turbines within an array. Here, we investigate the accuracy of a computationally efficient Blade Element Momentum (BEM) to predict unsteady loads on a double-rotor floating tidal turbine, adopting inflow data from LES and comparing to loads resolved in the LES using an Actuator Line Model (ALM). Results show that mean thrust and bending moment are well predicted by the BEM in comparison to the LES-ALM results.

Original languageEnglish
Title of host publicationTrends in Renewable Energies Offshore - Proceedings of the 5th International Conference on Renewable Energies Offshore, RENEW 2022
EditorsC. Guedes Soares
PublisherCRC Press and Balkema
Pages915-924
Number of pages10
ISBN (Print)9781032420035
DOIs
Publication statusPublished - 2023
Event5th International Conference on Renewable Energies Offshore, RENEW 2022 - Lisbon, Portugal
Duration: 8 Nov 202210 Nov 2022

Publication series

NameTrends in Renewable Energies Offshore - Proceedings of the 5th International Conference on Renewable Energies Offshore, RENEW 2022

Conference

Conference5th International Conference on Renewable Energies Offshore, RENEW 2022
Country/TerritoryPortugal
CityLisbon
Period8/11/2210/11/22

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