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Surrogate-Based Optimization of Horizontal Axis Hydrokinetic Turbine Rotor Blades

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  • 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
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    References listed on IDEAS

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    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.
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