IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v200y2022icp1602-1617.html
   My bibliography  Save this article

A low-order wake interaction modeling framework for the performance of ocean current turbines under turbulent conditions

Author

Listed:
  • Razi, P.
  • Ramaprabhu, P.
  • Tarey, P.
  • Muglia, M.
  • Vermillion, C.

Abstract

Understanding the effects of ambient turbulence (expressed often in terms of the turbulence intensity It) is critical to the development of predictive models for the performance of Ocean Current Turbine (OCTs). This paper describes a new, wake interaction modeling framework capable of capturing the detailed effects of turbulence on various performance parameters associated with OCTs that may be arranged in any arbitrary configuration. The model accounts for the effects of turbulence on the structure of the turbine wakes, specifically the extents of near- and far-wake regions, and the dependence of the transition point between the two regions on It. The analytical description for turbine wake is combined with an existing wake interaction model, the Unrestricted Wind Farm Layout Optimization (UWFLO) model to predict the global power output from an array of OCTs. The resulting modelling framework accurately captures the effect of inlet turbulence on the OCT farm power and efficiency, and can be applied to any array configuration. Results from the model are validated against Large Eddy Simulations (LES) in which the OCTs are modeled using the Blade Element Momentum (BEM) model, while the inlet flow is superposed with a synthetic turbulence field designed to approximate turbulence properties obtained from observational measurements of the Gulf Stream. The simulations show that OCT wakes recover faster at higher levels of inlet turbulence due to the enhanced entrainment and mixing between ambient flow and the wake, an effect that is captured by the modified UWFLO model.

Suggested Citation

  • Razi, P. & Ramaprabhu, P. & Tarey, P. & Muglia, M. & Vermillion, C., 2022. "A low-order wake interaction modeling framework for the performance of ocean current turbines under turbulent conditions," Renewable Energy, Elsevier, vol. 200(C), pages 1602-1617.
    • Handle: RePEc:eee:renene:v:200:y:2022:i:c:p:1602-1617
    DOI: 10.1016/j.renene.2022.10.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S096014812201494X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2022.10.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Togneri, Michael & Lewis, Matt & Neill, Simon & Masters, Ian, 2017. "Comparison of ADCP observations and 3D model simulations of turbulence at a tidal energy site," Renewable Energy, Elsevier, vol. 114(PA), pages 273-282.
    2. Neary, Vincent S. & Gunawan, Budi & Hill, Craig & Chamorro, Leonardo P., 2013. "Near and far field flow disturbances induced by model hydrokinetic turbine: ADV and ADP comparison," Renewable Energy, Elsevier, vol. 60(C), pages 1-6.
    3. Yu-Ting Wu & Fernando Porté-Agel, 2012. "Atmospheric Turbulence Effects on Wind-Turbine Wakes: An LES Study," Energies, MDPI, vol. 5(12), pages 1-23, December.
    4. Gao, Xiaoxia & Yang, Hongxing & Lu, Lin, 2016. "Optimization of wind turbine layout position in a wind farm using a newly-developed two-dimensional wake model," Applied Energy, Elsevier, vol. 174(C), pages 192-200.
    5. Li, Binghui & de Queiroz, Anderson Rodrigo & DeCarolis, Joseph F. & Bane, John & He, Ruoying & Keeler, Andrew G. & Neary, Vincent S., 2017. "The economics of electricity generation from Gulf Stream currents," Energy, Elsevier, vol. 134(C), pages 649-658.
    6. Bastankhah, Majid & Porté-Agel, Fernando, 2014. "A new analytical model for wind-turbine wakes," Renewable Energy, Elsevier, vol. 70(C), pages 116-123.
    7. 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.
    8. Amin Niayifar & Fernando Porté-Agel, 2016. "Analytical Modeling of Wind Farms: A New Approach for Power Prediction," Energies, MDPI, vol. 9(9), pages 1-13, September.
    9. Baheri, Ali & Ramaprabhu, Praveen & Vermillion, Christopher, 2018. "Iterative 3D layout optimization and parametric trade study for a reconfigurable ocean current turbine array using Bayesian Optimization," Renewable Energy, Elsevier, vol. 127(C), pages 1052-1063.
    10. Mycek, Paul & Gaurier, Benoît & Germain, Grégory & Pinon, Grégory & Rivoalen, Elie, 2014. "Experimental study of the turbulence intensity effects on marine current turbines behaviour. Part II: Two interacting turbines," Renewable Energy, Elsevier, vol. 68(C), pages 876-892.
    11. Mycek, Paul & Gaurier, Benoît & Germain, Grégory & Pinon, Grégory & Rivoalen, Elie, 2014. "Experimental study of the turbulence intensity effects on marine current turbines behaviour. Part I: One single turbine," Renewable Energy, Elsevier, vol. 66(C), pages 729-746.
    12. Chowdhury, Souma & Zhang, Jie & Messac, Achille & Castillo, Luciano, 2012. "Unrestricted wind farm layout optimization (UWFLO): Investigating key factors influencing the maximum power generation," Renewable Energy, Elsevier, vol. 38(1), pages 16-30.
    13. Myers, L.E. & Bahaj, A.S., 2012. "An experimental investigation simulating flow effects in first generation marine current energy converter arrays," Renewable Energy, Elsevier, vol. 37(1), pages 28-36.
    14. Draycott, S. & Sellar, B. & Davey, T. & Noble, D.R. & Venugopal, V. & Ingram, D.M., 2019. "Capture and simulation of the ocean environment for offshore renewable energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 15-29.
    15. Vinod, Ashwin & Banerjee, Arindam, 2019. "Performance and near-wake characterization of a tidal current turbine in elevated levels of free stream turbulence," Applied Energy, Elsevier, vol. 254(C).
    16. Yang, Xiufeng & Haas, Kevin A. & Fritz, Hermann M., 2014. "Evaluating the potential for energy extraction from turbines in the gulf stream system," Renewable Energy, Elsevier, vol. 72(C), pages 12-21.
    17. Vinod, Ashwin & Han, Cong & Banerjee, Arindam, 2021. "Tidal turbine performance and near-wake characteristics in a sheared turbulent inflow," Renewable Energy, Elsevier, vol. 175(C), pages 840-852.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cao, Lichao & Ge, Mingwei & Gao, Xiaoxia & Du, Bowen & Li, Baoliang & Huang, Zhi & Liu, Yongqian, 2022. "Wind farm layout optimization to minimize the wake induced turbulence effect on wind turbines," Applied Energy, Elsevier, vol. 323(C).
    2. Nicolas Kirchner-Bossi & Fernando Porté-Agel, 2018. "Realistic Wind Farm Layout Optimization through Genetic Algorithms Using a Gaussian Wake Model," Energies, MDPI, vol. 11(12), pages 1-26, November.
    3. Nicolas Kirchner-Bossi & Fernando Porté-Agel, 2021. "Wind Farm Area Shape Optimization Using Newly Developed Multi-Objective Evolutionary Algorithms," Energies, MDPI, vol. 14(14), pages 1-25, July.
    4. Song, Jeonghwan & Kim, Taewan & You, Donghyun, 2023. "Particle swarm optimization of a wind farm layout with active control of turbine yaws," Renewable Energy, Elsevier, vol. 206(C), pages 738-747.
    5. 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.
    6. 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.
    7. Ebdon, Tim & Allmark, Matthew J. & O’Doherty, Daphne M. & Mason-Jones, Allan & O’Doherty, Tim & Germain, Gregory & Gaurier, Benoit, 2021. "The impact of turbulence and turbine operating condition on the wakes of tidal turbines," Renewable Energy, Elsevier, vol. 165(P2), pages 96-116.
    8. Ziyu Zhang & Peng Huang & Haocheng Sun, 2020. "A Novel Analytical Wake Model with a Cosine-Shaped Velocity Deficit," Energies, MDPI, vol. 13(13), pages 1-20, June.
    9. Lo Brutto, Ottavio A. & Nguyen, Van Thinh & Guillou, Sylvain S. & Thiébot, Jérôme & Gualous, Hamid, 2016. "Tidal farm analysis using an analytical model for the flow velocity prediction in the wake of a tidal turbine with small diameter to depth ratio," Renewable Energy, Elsevier, vol. 99(C), pages 347-359.
    10. Maduka, Maduka & Li, Chi Wai, 2022. "Experimental evaluation of power performance and wake characteristics of twin flanged duct turbines in tandem under bi-directional tidal flows," Renewable Energy, Elsevier, vol. 199(C), pages 1543-1567.
    11. Lam, Wei-Haur & Chen, Long & Hashim, Roslan, 2015. "Analytical wake model of tidal current turbine," Energy, Elsevier, vol. 79(C), pages 512-521.
    12. Modali, Pranav K. & Vinod, Ashwin & Banerjee, Arindam, 2021. "Towards a better understanding of yawed turbine wake for efficient wake steering in tidal arrays," Renewable Energy, Elsevier, vol. 177(C), pages 482-494.
    13. Aghsaee, Payam & Markfort, Corey D., 2018. "Effects of flow depth variations on the wake recovery behind a horizontal-axis hydrokinetic in-stream turbine," Renewable Energy, Elsevier, vol. 125(C), pages 620-629.
    14. Pyakurel, Parakram & VanZwieten, James H. & Sultan, Cornel & Dhanak, Manhar & Xiros, Nikolaos I., 2017. "Numerical simulation and dynamical response of a moored hydrokinetic turbine operating in the wake of an upstream turbine for control design," Renewable Energy, Elsevier, vol. 114(PB), pages 1134-1145.
    15. Chen, Yaling & Lin, Binliang & Lin, Jie & Wang, Shujie, 2017. "Experimental study of wake structure behind a horizontal axis tidal stream turbine," Applied Energy, Elsevier, vol. 196(C), pages 82-96.
    16. Lo Brutto, Ottavio A. & Thiébot, Jérôme & Guillou, Sylvain S. & Gualous, Hamid, 2016. "A semi-analytic method to optimize tidal farm layouts – Application to the Alderney Race (Raz Blanchard), France," Applied Energy, Elsevier, vol. 183(C), pages 1168-1180.
    17. Niebuhr, C.M. & Schmidt, S. & van Dijk, M. & Smith, L. & Neary, V.S., 2022. "A review of commercial numerical modelling approaches for axial hydrokinetic turbine wake analysis in channel flow," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    18. Ti, Zilong & Deng, Xiao Wei & Yang, Hongxing, 2020. "Wake modeling of wind turbines using machine learning," Applied Energy, Elsevier, vol. 257(C).
    19. Mingqiu Liu & Zhichang Liang & Haixiao Liu, 2022. "Numerical Investigations of Wake Expansion in the Offshore Wind Farm Using a Large Eddy Simulation," Energies, MDPI, vol. 15(6), pages 1-19, March.
    20. Ti, Zilong & Deng, Xiao Wei & Zhang, Mingming, 2021. "Artificial Neural Networks based wake model for power prediction of wind farm," Renewable Energy, Elsevier, vol. 172(C), pages 618-631.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:200:y:2022:i:c:p:1602-1617. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.