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Evaluation of Model Predictions of the Unsteady Tidal Stream Resource and Turbine Fatigue Loads Relative to Multi-Point Flow Measurements at Raz Blanchard

Author

Listed:
  • Hannah Mullings

    (School of Engineering, The University of Manchester, Manchester M13 9PL, UK)

  • Samuel Draycott

    (School of Engineering, The University of Manchester, Manchester M13 9PL, UK)

  • Jérôme Thiébot

    (Laboratoire Universitaire de Sciences Appliquées de Cherbourg (LUSAC), University of Caen Normandy (UNICAEN), 50130 Cherbourg en Cotentin, France)

  • Sylvain Guillou

    (Laboratoire Universitaire de Sciences Appliquées de Cherbourg (LUSAC), University of Caen Normandy (UNICAEN), 50130 Cherbourg en Cotentin, France)

  • Philippe Mercier

    (Laboratoire Universitaire de Sciences Appliquées de Cherbourg (LUSAC), University of Caen Normandy (UNICAEN), 50130 Cherbourg en Cotentin, France)

  • Jon Hardwick

    (Renewable Energy Group, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Penryn Campus, Penryn TR10 9FE, UK)

  • Ed Mackay

    (Renewable Energy Group, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Penryn Campus, Penryn TR10 9FE, UK)

  • Philipp Thies

    (Renewable Energy Group, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Penryn Campus, Penryn TR10 9FE, UK)

  • Tim Stallard

    (School of Engineering, The University of Manchester, Manchester M13 9PL, UK)

Abstract

The next stage of development of the tidal stream industry will see a focus on the deployment of tidal turbines in arrays of increasing device numbers and rated power. Successful array development requires a thorough understanding of the resource within potential deployment sites. This is predictable in terms of flow speeds, based upon tidal constituents. However, the operating environment for the turbine is more complex than the turbine experiencing a uniform flow, with turbulence, shear and wave conditions all affecting the loading on the turbine components. This study establishes the accuracy with which several alternative modelling tools predict the resource characteristics which define unsteady loading—velocity shear, turbulence and waves—and assesses the impact of the model choice on predicted damage equivalent loads. In addition, the predictions of turbulence are compared to a higher fidelity model and the occurrence of flow speeds to a Delft3D model for currents and waves. These models have been run for a specific tidal site, the Raz Blanchard, one of the major tidal stream sites in European waters. The measured resource and predicted loading are established using data collected in a recent deployment of acoustic Doppler current profilers (ADCPs) as part of the Interreg TIGER project. The conditions are measured at three locations across the site, with transverse spacing of 145.7 m and 59.3 m between each device. Turbine fatigue loading is assessed using measurements and model predictions based on an unsteady blade element momentum model applied to near-surface and near-bed deployment positions. As well as across-site spatial variation of loading, the through life loading over a 5-year period results in an 8% difference to measured loads for a near-surface turbine, using conditions purely defined from a resource model and to within 3% when using a combination of modelled shear with measured turbulence characteristics.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:20:p:7057-:d:1258183
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    References listed on IDEAS

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    1. Thiébot, Jérôme & Bailly du Bois, Pascal & Guillou, Sylvain, 2015. "Numerical modeling of the effect of tidal stream turbines on the hydrodynamics and the sediment transport – Application to the Alderney Race (Raz Blanchard), France," Renewable Energy, Elsevier, vol. 75(C), pages 356-365.
    2. 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.
    3. Jon Hardwick & Ed B. L. Mackay & Ian G. C. Ashton & Helen C. M. Smith & Philipp R. Thies, 2021. "Quantifying the Effects of Wave—Current Interactions on Tidal Energy Resource at Sites in the English Channel Using Coupled Numerical Simulations," Energies, MDPI, vol. 14(12), pages 1-17, June.
    4. Thiébot, Jérôme & Guillou, Nicolas & Guillou, Sylvain & Good, Andrew & Lewis, Michael, 2020. "Wake field study of tidal turbines under realistic flow conditions," Renewable Energy, Elsevier, vol. 151(C), pages 1196-1208.
    5. Hannah Mullings & Tim Stallard, 2021. "Assessment of Dependency of Unsteady Onset Flow and Resultant Tidal Turbine Fatigue Loads on Measurement Position at a Tidal Site," Energies, MDPI, vol. 14(17), pages 1-13, September.
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