IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v99y2016icp347-359.html
   My bibliography  Save this article

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

Author

Listed:
  • Lo Brutto, Ottavio A.
  • Nguyen, Van Thinh
  • Guillou, Sylvain S.
  • Thiébot, Jérôme
  • Gualous, Hamid

Abstract

A tidal turbine is a device converting hydrodynamic power into electrical power. Lately, more and more projects have been developed in order to optimize the productivity of this kind of energy. In such research with industrial interest, under the impact of the wake effect on the output power, the analysis of a tidal farm layout is regarded as the first priority. Simple approaches such as those developed for wind farms could be used in tidal turbine arrangement optimization. These methodologies can be improved by taking into account the turbulence in tidal farms and tidal turbines' mechanical characteristics. The goal of this work is to propose a predictive analytical model to estimate the tidal speed in the far wake of tidal turbines with small diameter to depth ratio (20% here). It is a first step prior to integrate the wake model in a tidal farm layout optimization algorithm. The wake model development is achieved reanalyzing the far wake's equations used in wind farm applications. A turbine represented by an Actuator Disc (AD) in conjunction with a Computational Fluid Dynamics (CFD) numerical model is used as a reference for this purpose. The CFD-AD model has been validated with experimental results from literature. The novelty of the present work consists in expressing the far wake's radius expansion as a function of the ambient turbulence and the thrust coefficient. The proposed equation is used in conjunction with the Jensen's model in a manner that the velocities downstream a tidal turbine can be estimated. The velocity distribution in the far wake of a single turbine obtained by the proposed model is in good agreement with the CFD numerical model. As a matter of fact, the model provides satisfactory accuracy in the cases of two parks: one with five aligned turbines and one with ten staggered turbines.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:renene:v:99:y:2016:i:c:p:347-359
    DOI: 10.1016/j.renene.2016.07.020
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148116306164
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2016.07.020?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. Malki, Rami & Masters, Ian & Williams, Alison J. & Nick Croft, T., 2014. "Planning tidal stream turbine array layouts using a coupled blade element momentum – computational fluid dynamics model," Renewable Energy, Elsevier, vol. 63(C), pages 46-54.
    2. 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.
    3. 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.
    4. Emami, Alireza & Noghreh, Pirooz, 2010. "New approach on optimization in placement of wind turbines within wind farm by genetic algorithms," Renewable Energy, Elsevier, vol. 35(7), pages 1559-1564.
    5. Myers, L. & Bahaj, A.S., 2005. "Simulated electrical power potential harnessed by marine current turbine arrays in the Alderney Race," Renewable Energy, Elsevier, vol. 30(11), pages 1713-1731.
    6. 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.
    7. Pookpunt, Sittichoke & Ongsakul, Weerakorn, 2013. "Optimal placement of wind turbines within wind farm using binary particle swarm optimization with time-varying acceleration coefficients," Renewable Energy, Elsevier, vol. 55(C), pages 266-276.
    8. Jo, Chul-Hee & Lee, Jun-Ho & Rho, Yu-Ho & Lee, Kang-Hee, 2014. "Performance analysis of a HAT tidal current turbine and wake flow characteristics," Renewable Energy, Elsevier, vol. 65(C), pages 175-182.
    9. 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.
    10. 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.
    11. Yazicioglu, Hasan & Tunc, K.M. Murat & Ozbek, Muammer & Kara, Tolga, 2016. "Simulation of electricity generation by marine current turbines at Istanbul Bosphorus Strait," Energy, Elsevier, vol. 95(C), pages 41-50.
    12. Grady, S.A. & Hussaini, M.Y. & Abdullah, M.M., 2005. "Placement of wind turbines using genetic algorithms," Renewable Energy, Elsevier, vol. 30(2), pages 259-270.
    13. Feng, Ju & Shen, Wen Zhong, 2015. "Solving the wind farm layout optimization problem using random search algorithm," Renewable Energy, Elsevier, vol. 78(C), pages 182-192.
    14. Shakoor, Rabia & Hassan, Mohammad Yusri & Raheem, Abdur & Rasheed, Nadia, 2016. "Wind farm layout optimization using area dimensions and definite point selection techniques," Renewable Energy, Elsevier, vol. 88(C), pages 154-163.
    15. Yamani Douzi Sorkhabi, Sami & Romero, David A. & Yan, Gary Kai & Gu, Michelle Dao & Moran, Joaquin & Morgenroth, Michael & Amon, Cristina H., 2016. "The impact of land use constraints in multi-objective energy-noise wind farm layout optimization," Renewable Energy, Elsevier, vol. 85(C), pages 359-370.
    16. Song, Zhe & Zhang, Zijun & Chen, Xingying, 2016. "The decision model of 3-dimensional wind farm layout design," Renewable Energy, Elsevier, vol. 85(C), pages 248-258.
    17. Nguyen, Van Thinh & Guillou, Sylvain S. & Thiébot, Jérôme & Santa Cruz, Alina, 2016. "Modelling turbulence with an Actuator Disk representing a tidal turbine," Renewable Energy, Elsevier, vol. 97(C), pages 625-635.
    18. Stansby, Peter & Stallard, Tim, 2016. "Fast optimisation of tidal stream turbine positions for power generation in small arrays with low blockage based on superposition of self-similar far-wake velocity deficit profiles," Renewable Energy, Elsevier, vol. 92(C), pages 366-375.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dou, Bingzheng & Guala, Michele & Lei, Liping & Zeng, Pan, 2019. "Wake model for horizontal-axis wind and hydrokinetic turbines in yawed conditions," Applied Energy, Elsevier, vol. 242(C), pages 1383-1395.
    2. Chen, Yaling & Lin, Binliang & Liang, Dongfang, 2023. "Interactions between approaching flow and hydrokinetic turbines in a staggered layout," Renewable Energy, Elsevier, vol. 218(C).
    3. Ziyao Wang & Erhu Hou & He Wu, 2024. "Semi-Empirical Model Based on the Influence of Turbulence Intensity on the Wake of Vertical Axis Turbines," Energies, MDPI, vol. 17(18), pages 1-17, September.
    4. Kabir Bashir Shariff & Sylvain S. Guillou, 2024. "A Generalized Empirical Model for Velocity Deficit and Turbulent Intensity in Tidal Turbine Wake Accounting for the Effect of Rotor-Diameter-to-Depth Ratio," Energies, MDPI, vol. 17(9), pages 1-20, April.
    5. Chen, Long & Yao, Yu & Wang, Zhi-liang, 2020. "Development and validation of a prediction model for the multi-wake of tidal stream turbines," Renewable Energy, Elsevier, vol. 155(C), pages 800-809.
    6. Chen, Yaling & Lin, Binliang & Sun, Jian & Guo, Jinxi & Wu, Wenlong, 2019. "Hydrodynamic effects of the ratio of rotor diameter to water depth: An experimental study," Renewable Energy, Elsevier, vol. 136(C), pages 331-341.
    7. 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.
    8. Aguayo, Maichel M. & Fierro, Pablo E. & De la Fuente, Rodrigo A. & Sepúlveda, Ignacio A. & Figueroa, Dante M., 2021. "A mixed-integer programming methodology to design tidal current farms integrating both cost and benefits: A case study in the Chacao Channel, Chile," Applied Energy, Elsevier, vol. 294(C).
    9. Nasteho Djama Dirieh & Jérôme Thiébot & Sylvain Guillou & Nicolas Guillou, 2022. "Blockage Corrections for Tidal Turbines—Application to an Array of Turbines in the Alderney Race," Energies, MDPI, vol. 15(10), pages 1-18, May.
    10. 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.
    11. Lo Brutto, Ottavio A. & Guillou, Sylvain S. & Thiébot, Jérôme & Gualous, Hamid, 2017. "Assessing the effectiveness of a global optimum strategy within a tidal farm for power maximization," Applied Energy, Elsevier, vol. 204(C), pages 653-666.

    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. 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.
    2. Azlan, F. & Kurnia, J.C. & Tan, B.T. & Ismadi, M.-Z., 2021. "Review on optimisation methods of wind farm array under three classical wind condition problems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    3. Van Thinh Nguyen & Alina Santa Cruz & Sylvain S. Guillou & Mohamad N. Shiekh Elsouk & Jérôme Thiébot, 2019. "Effects of the Current Direction on the Energy Production of a Tidal Farm: The Case of Raz Blanchard (France)," Energies, MDPI, vol. 12(13), pages 1-20, June.
    4. Lo Brutto, Ottavio A. & Guillou, Sylvain S. & Thiébot, Jérôme & Gualous, Hamid, 2017. "Assessing the effectiveness of a global optimum strategy within a tidal farm for power maximization," Applied Energy, Elsevier, vol. 204(C), pages 653-666.
    5. Yang, Kyoungboo & Kwak, Gyeongil & Cho, Kyungho & Huh, Jongchul, 2019. "Wind farm layout optimization for wake effect uniformity," Energy, Elsevier, vol. 183(C), pages 983-995.
    6. Dinçer, A.E. & Demir, A. & Yılmaz, K., 2024. "Multi-objective turbine allocation on a wind farm site," Applied Energy, Elsevier, vol. 355(C).
    7. Antonini, Enrico G.A. & Romero, David A. & Amon, Cristina H., 2018. "Continuous adjoint formulation for wind farm layout optimization: A 2D implementation," Applied Energy, Elsevier, vol. 228(C), pages 2333-2345.
    8. Kyoungboo Yang & Kyungho Cho, 2019. "Simulated Annealing Algorithm for Wind Farm Layout Optimization: A Benchmark Study," Energies, MDPI, vol. 12(23), pages 1-15, November.
    9. Antonini, Enrico G.A. & Romero, David A. & Amon, Cristina H., 2020. "Optimal design of wind farms in complex terrains using computational fluid dynamics and adjoint methods," Applied Energy, Elsevier, vol. 261(C).
    10. Yang, Zhixue & Ren, Zhouyang & Li, Hui & Pan, Zhen & Xia, Weiyi, 2024. "A review of tidal current power generation farm planning: Methodologies, characteristics and challenges," Renewable Energy, Elsevier, vol. 220(C).
    11. Riglin, Jacob & Daskiran, Cosan & Jonas, Joseph & Schleicher, W. Chris & Oztekin, Alparslan, 2016. "Hydrokinetic turbine array characteristics for river applications and spatially restricted flows," Renewable Energy, Elsevier, vol. 97(C), pages 274-283.
    12. Guirguis, David & Romero, David A. & Amon, Cristina H., 2016. "Toward efficient optimization of wind farm layouts: Utilizing exact gradient information," Applied Energy, Elsevier, vol. 179(C), pages 110-123.
    13. 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.
    14. 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.
    15. Muhammad Nabeel Hussain & Nadeem Shaukat & Ammar Ahmad & Muhammad Abid & Abrar Hashmi & Zohreh Rajabi & Muhammad Atiq Ur Rehman Tariq, 2022. "Effective Realization of Multi-Objective Elitist Teaching–Learning Based Optimization Technique for the Micro-Siting of Wind Turbines," Sustainability, MDPI, vol. 14(14), pages 1-24, July.
    16. 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.
    17. Chen, Yaling & Lin, Binliang & Sun, Jian & Guo, Jinxi & Wu, Wenlong, 2019. "Hydrodynamic effects of the ratio of rotor diameter to water depth: An experimental study," Renewable Energy, Elsevier, vol. 136(C), pages 331-341.
    18. 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).
    19. 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.
    20. Yin, Peng-Yeng & Wu, Tsai-Hung & Hsu, Ping-Yi, 2017. "Simulation based risk management for multi-objective optimal wind turbine placement using MOEA/D," Energy, Elsevier, vol. 141(C), pages 579-597.

    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:99:y:2016:i:c:p:347-359. 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.