IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i13p4045-d588689.html
   My bibliography  Save this article

Surrogate-Based Optimization of Horizontal Axis Hydrokinetic Turbine Rotor Blades

Author

Listed:
  • David Menéndez Arán

    (Laboratorio de Modelación Matemática, Departamento de Hidráulica, Facultad de Ingeniería, Universidad de Buenos Aires, Paseo Colón 850, Ciudad Autónoma de Buenos Aires C1063ACV, Argentina)

  • Ángel Menéndez

    (Laboratorio de Modelación Matemática, Departamento de Hidráulica, Facultad de Ingeniería, Universidad de Buenos Aires, Paseo Colón 850, Ciudad Autónoma de Buenos Aires C1063ACV, Argentina)

Abstract

A design method was developed for automated, systematic design of hydrokinetic turbine rotor blades. The method coupled a Computational Fluid Dynamics (CFD) solver to estimate the power output of a given turbine with a surrogate-based constrained optimization method. This allowed the characterization of the design space while minimizing the number of analyzed blade geometries and the associated computational effort. An initial blade geometry developed using a lifting line optimization method was selected as the base geometry to generate a turbine blade family by multiplying a series of geometric parameters with corresponding linear functions. A performance database was constructed for the turbine blade family with the CFD solver and used to build the surrogate function. The linear functions were then incorporated into a constrained nonlinear optimization algorithm to solve for the blade geometry with the highest efficiency. A constraint on the minimum pressure on the blade could be set to prevent cavitation inception.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:13:p:4045-:d:588689
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/13/4045/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/14/13/4045/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Lee, Ju Hyun & Park, Sunho & Kim, Dong Hwan & Rhee, Shin Hyung & Kim, Moon-Chan, 2012. "Computational methods for performance analysis of horizontal axis tidal stream turbines," Applied Energy, Elsevier, vol. 98(C), pages 512-523.
    3. Walker, Jessica M. & Flack, Karen A. & Lust, Ethan E. & Schultz, Michael P. & Luznik, Luksa, 2014. "Experimental and numerical studies of blade roughness and fouling on marine current turbine performance," Renewable Energy, Elsevier, vol. 66(C), pages 257-267.
    4. Laws, Nicholas D. & Epps, Brenden P., 2016. "Hydrokinetic energy conversion: Technology, research, and outlook," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1245-1259.
    5. Yang, Xiaolei & Khosronejad, Ali & Sotiropoulos, Fotis, 2017. "Large-eddy simulation of a hydrokinetic turbine mounted on an erodible bed," Renewable Energy, Elsevier, vol. 113(C), pages 1419-1433.
    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. Segura, E. & Morales, R. & Somolinos, J.A., 2018. "A strategic analysis of tidal current energy conversion systems in the European Union," Applied Energy, Elsevier, vol. 212(C), pages 527-551.
    2. 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.
    3. 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.
    4. Fontaine, A.A. & Straka, W.A. & Meyer, R.S. & Jonson, M.L. & Young, S.D. & Neary, V.S., 2020. "Performance and wake flow characterization of a 1:8.7-scale reference USDOE MHKF1 hydrokinetic turbine to establish a verification and validation test database," Renewable Energy, Elsevier, vol. 159(C), pages 451-467.
    5. 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.
    6. Li, Wei & Zhou, Hongbin & Liu, Hongwei & Lin, Yonggang & Xu, Quankun, 2016. "Review on the blade design technologies of tidal current turbine," Renewable and Sustainable Energy Reviews, Elsevier, vol. 63(C), pages 414-422.
    7. Rahimian, Masoud & Walker, Jessica & Penesis, Irene, 2018. "Performance of a horizontal axis marine current turbine– A comprehensive evaluation using experimental, numerical, and theoretical approaches," Energy, Elsevier, vol. 148(C), pages 965-976.
    8. Musa, Mirko & Hill, Craig & Guala, Michele, 2019. "Interaction between hydrokinetic turbine wakes and sediment dynamics: array performance and geomorphic effects under different siting strategies and sediment transport conditions," Renewable Energy, Elsevier, vol. 138(C), pages 738-753.
    9. 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.
    10. Moreau, Martin & Germain, Grégory & Maurice, Guillaume, 2023. "Experimental performance and wake study of a ducted twin vertical axis turbine in ebb and flood tide currents at a 1/20th scale," Renewable Energy, Elsevier, vol. 214(C), pages 318-333.
    11. Goundar, Jai N. & Ahmed, M. Rafiuddin, 2013. "Design of a horizontal axis tidal current turbine," Applied Energy, Elsevier, vol. 111(C), pages 161-174.
    12. Brown, Eloise J. & King, Amanda L. & Duvoy, Paul X. & Trochim, Erin & Kasper, Jeremy L. & Wilson, Melany L. & Ravens, Thomas M., 2023. "Site suitability analysis of hydrokinetic river energy resources at community microgrids on the Kuskokwim River, Alaska," Renewable Energy, Elsevier, vol. 217(C).
    13. 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.
    14. Mansoor Ahmed Zaib & Arbaz Waqar & Shoukat Abbas & Saeed Badshah & Sajjad Ahmad & Muhammad Amjad & Seyed Saeid Rahimian Koloor & Mohamed Eldessouki, 2022. "Effect of Blade Diameter on the Performance of Horizontal-Axis Ocean Current Turbine," Energies, MDPI, vol. 15(15), pages 1-13, July.
    15. Wu, Chutian & Yang, Xiaolei & Zhu, Yaxin, 2021. "On the design of potential turbine positions for physics-informed optimization of wind farm layout," Renewable Energy, Elsevier, vol. 164(C), pages 1108-1120.
    16. del Horno, L. & Segura, E. & Morales, R. & Somolinos, J.A., 2020. "Exhaustive closed loop behavior of an one degree of freedom first-generation device for harnessing energy from marine currents," Applied Energy, Elsevier, vol. 276(C).
    17. Okulov, V.L. & Naumov, I.V. & Kabardin, I.K. & Litvinov, I.V. & Markovich, D.M. & Mikkelsen, R.F. & Sørensen, J.N. & Alekseenko, S.V. & Wood, D.H., 2021. "Experiments on line arrays of horizontal-axis hydroturbines," Renewable Energy, Elsevier, vol. 163(C), pages 15-21.
    18. Song, Cuihong & Gardner, Kevin H. & Klein, Sharon J.W. & Souza, Simone Pereira & Mo, Weiwei, 2018. "Cradle-to-grave greenhouse gas emissions from dams in the United States of America," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 945-956.
    19. Deng, Xu & Zhang, Jisheng & Lin, Xiangfeng, 2024. "Proposal of actuator line-immersed boundary coupling model for tidal stream turbine modeling with hydrodynamics upon scouring morphology," Energy, Elsevier, vol. 292(C).
    20. Ifaei, Pouya & Tayerani Charmchi, Amir Saman & Loy-Benitez, Jorge & Yang, Rebecca Jing & Yoo, ChangKyoo, 2022. "A data-driven analytical roadmap to a sustainable 2030 in South Korea based on optimal renewable microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).

    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:gam:jeners:v:14:y:2021:i:13:p:4045-:d:588689. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.