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The Influence of Intra-Array Wake Dynamics on Depth-Averaged Kinetic Tidal Turbine Energy Extraction Simulations

Author

Listed:
  • Marco Piano

    (Centre for Applied Marine Sciences, Marine Centre Wales, Bangor University, Menai Bridge LL59 5AB, UK)

  • Peter E. Robins

    (School of Ocean Sciences, Bangor University, Menai Bridge LL59 5AB, UK)

  • Alan G. Davies

    (Centre for Applied Marine Sciences, Marine Centre Wales, Bangor University, Menai Bridge LL59 5AB, UK)

  • Simon P. Neill

    (School of Ocean Sciences, Bangor University, Menai Bridge LL59 5AB, UK)

Abstract

Assessing the tidal stream energy resource, its intermittency and likely environmental feedbacks due to energy extraction, relies on the ability to accurately represent kinetic losses in ocean models. Energy conversion has often been implemented in ocean models with enhanced turbine stress terms formulated using an array-averaging approach, rather than implementing extraction at device-scale. In depth-averaged models, an additional drag term in the momentum equations is usually applied. However, such array-averaging simulations neglect intra-array device wake interactions, providing unrealistic energy extraction dynamics. Any induced simulation error will increase with array size. For this study, an idealized channel is discretized at sub 10 m resolution, resolving individual device wake profiles of tidal turbines in the domain. Sensitivity analysis is conducted on the applied turbulence closure scheme, validating results against published data from empirical scaled turbine studies. We test the fine scale model performance of several mesh densities, which produce a centerline velocity wake deficit accuracy (R 2 ) of 0.58–0.69 (RMSE = 7.16–8.28%) using a k-Ɛ turbulence closure scheme. Various array configurations at device scale are simulated and compared with an equivalent array-averaging approach by analyzing channel flux differential. Parametrization of array-averaging energy extraction techniques can misrepresent simulated energy transfer and removal. The potential peak error in channel flux exceeds 0.5% when the number of turbines n TECs ≈ 25 devices. This error exceeds 2% when simulating commercial-scale turbine array farms (i.e., >100 devices).

Suggested Citation

  • Marco Piano & Peter E. Robins & Alan G. Davies & Simon P. Neill, 2018. "The Influence of Intra-Array Wake Dynamics on Depth-Averaged Kinetic Tidal Turbine Energy Extraction Simulations," Energies, MDPI, vol. 11(10), pages 1-21, October.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:10:p:2852-:d:177365
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    References listed on IDEAS

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    Cited by:

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    2. Karina Soto-Rivas & David Richter & Cristian Escauriaza, 2019. "A Formulation of the Thrust Coefficient for Representing Finite-Sized Farms of Tidal Energy Converters," Energies, MDPI, vol. 12(20), pages 1-17, October.
    3. Craig Hill & Vincent S. Neary & Michele Guala & Fotis Sotiropoulos, 2020. "Performance and Wake Characterization of a Model Hydrokinetic Turbine: The Reference Model 1 (RM1) Dual Rotor Tidal Energy Converter," Energies, MDPI, vol. 13(19), pages 1-21, October.

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