IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v147y2020ip1p2128-2140.html
   My bibliography  Save this article

Performance improvement of horizontal axis wind turbines by aerodynamic shape optimization including aeroealstic deformation

Author

Listed:
  • Lee, Hak Min
  • Kwon, Oh Joon

Abstract

Aerodynamic shape optimization of horizontal axis wind turbines was performed to minimize the cost of energy. The optimum blade was obtained by modifying the blade section contours at selected blade radial stations. For the optimization, the design variables were defined as the coordinates of the blade section contours perpendicular to the chord. An aerodynamic performance database was constructed for those blade configurations defined by random combinations of design variables selected within a given range by Latin-Hypercube sampling. An artificial neural network was applied to derive the approximate functions between the design variables and the aerodynamic performance of the database. By utilizing the approximate functions, a genetic algorithm was adopted to search for an optimized blade. To construct the database, a CFD flow solver based on unstructured meshes was utilized. To consider the effects of aeroelastic deformation of the structurally flexible blades, a coupled CFD-CSD method was also adopted. The applications were made for the NREL phase VI and NREL 5 MW reference wind turbine rotor blades. After optimization, the cost of energy was reduced by 0.82% for the NREL phase VI rotor blade and one percent for the NREL 5 MW reference wind turbine blade, respectively.

Suggested Citation

  • Lee, Hak Min & Kwon, Oh Joon, 2020. "Performance improvement of horizontal axis wind turbines by aerodynamic shape optimization including aeroealstic deformation," Renewable Energy, Elsevier, vol. 147(P1), pages 2128-2140.
    • Handle: RePEc:eee:renene:v:147:y:2020:i:p1:p:2128-2140
    DOI: 10.1016/j.renene.2019.09.125
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148119314673
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2019.09.125?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.

    Citations

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


    Cited by:

    1. Win Naung, Shine & Nakhchi, Mahdi Erfanian & Rahmati, Mohammad, 2021. "High-fidelity CFD simulations of two wind turbines in arrays using nonlinear frequency domain solution method," Renewable Energy, Elsevier, vol. 174(C), pages 984-1005.
    2. Rasool, Safdar & Muttaqi, Kashem M. & Sutanto, Danny & Hemer, Mark, 2022. "Quantifying the reduction in power variability of co-located offshore wind-wave farms," Renewable Energy, Elsevier, vol. 185(C), pages 1018-1033.
    3. Win Naung, Shine & Rahmati, Mohammad & Farokhi, Hamed, 2021. "Nonlinear frequency domain solution method for aerodynamic and aeromechanical analysis of wind turbines," Renewable Energy, Elsevier, vol. 167(C), pages 66-81.
    4. Du, Qiuwan & Li, Yunzhu & Yang, Like & Liu, Tianyuan & Zhang, Di & Xie, Yonghui, 2022. "Performance prediction and design optimization of turbine blade profile with deep learning method," Energy, Elsevier, vol. 254(PA).
    5. Zhang, Dongqin & Liu, Zhenqing & Li, Weipeng & Hu, Gang, 2023. "LES simulation study of wind turbine aerodynamic characteristics with fluid-structure interaction analysis considering blade and tower flexibility," Energy, Elsevier, vol. 282(C).
    6. Nakhchi, M.E. & Naung, S. Win & Dala, L. & Rahmati, M., 2022. "Direct numerical simulations of aerodynamic performance of wind turbine aerofoil by considering the blades active vibrations," Renewable Energy, Elsevier, vol. 191(C), pages 669-684.

    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:147:y:2020:i:p1:p:2128-2140. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.