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Comparison of synthetic turbulence approaches for blade element momentum theory prediction of tidal turbine performance and loads

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  • Togneri, Michael
  • Pinon, Grégory
  • Carlier, Clément
  • Choma Bex, Camille
  • Masters, Ian

Abstract

Turbulence is a crucial flow phenomenon for tidal energy converters (TECs), as it influences both the peak loads they experience and their fatigue life. To best mitigate its effects we must understand both turbulence itself and how it induces loads on TECs. To that end, this paper presents the results of blade element momentum theory (BEMT) simulations of flume-scale TEC models subjected to synthetic turbulent flows. Synthetic turbulence methods produce three-dimensional flowfields from limited data, without solving the equations governing fluid motion. These flowfields are non-physical, but match key statistical properties of real turbulence and are much quicker and computationally cheaper to produce. This study employs two synthetic turbulence generation methods: the synthetic eddy method and the spectral Sandia method. The response of the TECs to the synthetic turbulence is predicted using a robust BEMT model, modified from the classical formulation of BEMT. We show that, for the cases investigated, TEC load variability is lower in stall operation than at higher tip speed ratios. The variability of turbine loads has a straightforward relationship to the turbulence intensity of the inflow. Spectral properties of the velocity field are not fully reflected in the spectra of TEC loads.

Suggested Citation

  • Togneri, Michael & Pinon, Grégory & Carlier, Clément & Choma Bex, Camille & Masters, Ian, 2020. "Comparison of synthetic turbulence approaches for blade element momentum theory prediction of tidal turbine performance and loads," Renewable Energy, Elsevier, vol. 145(C), pages 408-418.
    • Handle: RePEc:eee:renene:v:145:y:2020:i:c:p:408-418
    DOI: 10.1016/j.renene.2019.05.110
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    Citations

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    Cited by:

    1. Myriam Slama & Camille Choma Bex & Grégory Pinon & Michael Togneri & Iestyn Evans, 2021. "Lagrangian Vortex Computations of a Four Tidal Turbine Array: An Example Based on the NEPTHYD Layout in the Alderney Race," Energies, MDPI, vol. 14(13), pages 1-23, June.
    2. Perez, Larissa & Cossu, Remo & Grinham, Alistair & Penesis, Irene, 2021. "Seasonality of turbulence characteristics and wave-current interaction in two prospective tidal energy sites," Renewable Energy, Elsevier, vol. 178(C), pages 1322-1336.
    3. Edmunds, Matt & Williams, Alison J. & Masters, Ian & Banerjee, Arindam & VanZwieten, James H., 2020. "A spatially nonlinear generalised actuator disk model for the simulation of horizontal axis wind and tidal turbines," Energy, Elsevier, vol. 194(C).
    4. Perez, Larissa & Cossu, Remo & Grinham, Alistair & Penesis, Irene, 2022. "An investigation of tidal turbine performance and loads under various turbulence conditions using Blade Element Momentum theory and high-frequency field data acquired in two prospective tidal energy s," Renewable Energy, Elsevier, vol. 201(P1), pages 928-937.
    5. Hannah Mullings & Samuel Draycott & Jérôme Thiébot & Sylvain Guillou & Philippe Mercier & Jon Hardwick & Ed Mackay & Philipp Thies & Tim Stallard, 2023. "Evaluation of Model Predictions of the Unsteady Tidal Stream Resource and Turbine Fatigue Loads Relative to Multi-Point Flow Measurements at Raz Blanchard," Energies, MDPI, vol. 16(20), pages 1-30, October.
    6. David Menéndez Arán & Ángel Menéndez, 2021. "Surrogate-Based Optimization of Horizontal Axis Hydrokinetic Turbine Rotor Blades," Energies, MDPI, vol. 14(13), pages 1-16, July.
    7. Wang, Longyan & Xu, Jian & Luo, Wei & Luo, Zhaohui & Xie, Junhang & Yuan, Jianping & Tan, Andy C.C., 2022. "A deep learning-based optimization framework of two-dimensional hydrofoils for tidal turbine rotor design," Energy, Elsevier, vol. 253(C).
    8. Arturo Ortega & Joseph Praful Tomy & Jonathan Shek & Stephane Paboeuf & David Ingram, 2020. "An Inter-Comparison of Dynamic, Fully Coupled, Electro-Mechanical, Models of Tidal Turbines," Energies, MDPI, vol. 13(20), pages 1-19, October.
    9. Gaurier, Benoît & Carlier, Clément & Germain, Grégory & Pinon, Grégory & Rivoalen, Elie, 2020. "Three tidal turbines in interaction: An experimental study of turbulence intensity effects on wakes and turbine performance," Renewable Energy, Elsevier, vol. 148(C), pages 1150-1164.

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