IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v116y2016ip1p202-213.html
   My bibliography  Save this article

A new optimization approach to improve the overall performance of thick wind turbine airfoils

Author

Listed:
  • Li, Xingxing
  • Yang, Ke
  • Bai, Jingyan
  • Xu, Jianzhong

Abstract

A crucial problem of designing thick airfoils is balancing structural and aerodynamic requirements. This paper documented a new idea to deal with the thick airfoil's design. Firstly, the relative thickness of the original airfoil was increased to enhance its structural property. Then the overall aerodynamic performance was improved by the optimization design method. Specifically, this paper put forward a mathematical model of the overall optimization employing airfoil's performance evaluation indicators which represent modern rotor blades' aerodynamic requirements of “high efficiency, low extreme load, wide range of operating angle of attack and stability with varying operating conditions”. Based on this model, an integrated optimization platform for thick airfoils' overall design was established. Through an optimization experiment, a new 35-percent relative thickness airfoil was obtained. The new airfoil was predicted with high design lift coefficient, acceptable maximum lift to drag ratio, moderate stall parameter, and desirable stability parameters. These characteristics contribute to a high overall performance which could be competent with commonly used thick DU airfoils. Lift characteristics of the new airfoil have been validated by tests. These results confirmed the proposed method has effectively balanced airfoil's complicated requirements and successfully improved the new airfoil's overall performance.

Suggested Citation

  • Li, Xingxing & Yang, Ke & Bai, Jingyan & Xu, Jianzhong, 2016. "A new optimization approach to improve the overall performance of thick wind turbine airfoils," Energy, Elsevier, vol. 116(P1), pages 202-213.
  • Handle: RePEc:eee:energy:v:116:y:2016:i:p1:p:202-213
    DOI: 10.1016/j.energy.2016.09.108
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544216313809
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2016.09.108?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. Peter J. Schubel & Richard J. Crossley, 2012. "Wind Turbine Blade Design," Energies, MDPI, vol. 5(9), pages 1-25, September.
    2. Abdallah, I. & Natarajan, A. & Sørensen, J.D., 2015. "Impact of uncertainty in airfoil characteristics on wind turbine extreme loads," Renewable Energy, Elsevier, vol. 75(C), pages 283-300.
    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. Zhou, Teng & Cao, Huijing & Zhang, Mingming & Liao, Caicai, 2022. "Performance simulation of wind turbine with optimal designed trailing-edge serrations," Energy, Elsevier, vol. 243(C).
    2. Ma, Ning & Lei, Hang & Han, Zhaolong & Zhou, Dai & Bao, Yan & Zhang, Kai & Zhou, Lei & Chen, Caiyong, 2018. "Airfoil optimization to improve power performance of a high-solidity vertical axis wind turbine at a moderate tip speed ratio," Energy, Elsevier, vol. 150(C), pages 236-252.
    3. Vianna Neto, Júlio Xavier & Guerra Junior, Elci José & Moreno, Sinvaldo Rodrigues & Hultmann Ayala, Helon Vicente & Mariani, Viviana Cocco & Coelho, Leandro dos Santos, 2018. "Wind turbine blade geometry design based on multi-objective optimization using metaheuristics," Energy, Elsevier, vol. 162(C), pages 645-658.

    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. Nallapaneni Manoj Kumar & Aneesh A. Chand & Maria Malvoni & Kushal A. Prasad & Kabir A. Mamun & F.R. Islam & Shauhrat S. Chopra, 2020. "Distributed Energy Resources and the Application of AI, IoT, and Blockchain in Smart Grids," Energies, MDPI, vol. 13(21), pages 1-42, November.
    2. Michał Pacholczyk & Dariusz Karkosiński, 2020. "Parametric Study on a Performance of a Small Counter-Rotating Wind Turbine," Energies, MDPI, vol. 13(15), pages 1-17, July.
    3. Wiroon Monatrakul & Kritsadang Senawong & Piyawat Sritram & Ratchaphon Suntivarakorn, 2023. "A Comparison Study of Hydro-Compact Generators with Horizontal Spiral Turbines (HSTs) and a Three-Blade Turbine Used in Irrigation Canals," Energies, MDPI, vol. 16(5), pages 1-15, February.
    4. Sessarego, Matias & Feng, Ju & Ramos-García, Néstor & Horcas, Sergio González, 2020. "Design optimization of a curved wind turbine blade using neural networks and an aero-elastic vortex method under turbulent inflow," Renewable Energy, Elsevier, vol. 146(C), pages 1524-1535.
    5. Ali, Qazi Shahzad & Kim, Man-Hoe, 2021. "Design and performance analysis of an airborne wind turbine for high-altitude energy harvesting," Energy, Elsevier, vol. 230(C).
    6. Didane, Djamal Hissein & Rosly, Nurhayati & Zulkafli, Mohd Fadhli & Shamsudin, Syariful Syafiq, 2018. "Performance evaluation of a novel vertical axis wind turbine with coaxial contra-rotating concept," Renewable Energy, Elsevier, vol. 115(C), pages 353-361.
    7. Avri Eitan & Gillad Rosen & Lior Herman & Itay Fishhendler, 2020. "Renewable Energy Entrepreneurs: A Conceptual Framework," Energies, MDPI, vol. 13(10), pages 1-23, May.
    8. Golnary, Farshad & Moradi, Hamed, 2022. "Identification of the dynamics of the drivetrain and estimating its unknown parts in a large scale wind turbine," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 192(C), pages 50-69.
    9. Fiammetta Rita Bianchi & Barbara Bosio, 2021. "Operating Principles, Performance and Technology Readiness Level of Reversible Solid Oxide Cells," Sustainability, MDPI, vol. 13(9), pages 1-23, April.
    10. Yao, Shulong & Griffith, D. Todd & Chetan, Mayank & Bay, Christopher J. & Damiani, Rick & Kaminski, Meghan & Loth, Eric, 2020. "A gravo-aeroelastically scaled wind turbine rotor at field-prototype scale with strict structural requirements," Renewable Energy, Elsevier, vol. 156(C), pages 535-547.
    11. Li, Yingjue & Wei, Kexiang & Yang, Wenxian & Wang, Qiong, 2020. "Improving wind turbine blade based on multi-objective particle swarm optimization," Renewable Energy, Elsevier, vol. 161(C), pages 525-542.
    12. Toft, Henrik Stensgaard & Svenningsen, Lasse & Sørensen, John Dalsgaard & Moser, Wolfgang & Thøgersen, Morten Lybech, 2016. "Uncertainty in wind climate parameters and their influence on wind turbine fatigue loads," Renewable Energy, Elsevier, vol. 90(C), pages 352-361.
    13. Tuka N Fattal, 2018. "Increasing Wind Turbine Efficiency," International Journal of Technology and Engineering Studies, PROF.IR.DR.Mohid Jailani Mohd Nor, vol. 4(4), pages 120-131.
    14. Tjiu, Willy & Marnoto, Tjukup & Mat, Sohif & Ruslan, Mohd Hafidz & Sopian, Kamaruzzaman, 2015. "Darrieus vertical axis wind turbine for power generation II: Challenges in HAWT and the opportunity of multi-megawatt Darrieus VAWT development," Renewable Energy, Elsevier, vol. 75(C), pages 560-571.
    15. Zhiyu Jiang & Weifei Hu & Wenbin Dong & Zhen Gao & Zhengru Ren, 2017. "Structural Reliability Analysis of Wind Turbines: A Review," Energies, MDPI, vol. 10(12), pages 1-25, December.
    16. Tang, Xinzi & Yuan, Keren & Gu, Nengwei & Li, Pengcheng & Peng, Ruitao, 2022. "An interval quantification-based optimization approach for wind turbine airfoil under uncertainties," Energy, Elsevier, vol. 244(PA).
    17. Sudhakar Gantasala & Narges Tabatabaei & Michel Cervantes & Jan-Olov Aidanpää, 2019. "Numerical Investigation of the Aeroelastic Behavior of a Wind Turbine with Iced Blades," Energies, MDPI, vol. 12(12), pages 1-24, June.
    18. Sedaghatizadeh, Nima & Arjomandi, Maziar & Cazzolato, Benjamin & Kelso, Richard, 2017. "Wind farm noises: Mechanisms and evidence for their dependency on wind direction," Renewable Energy, Elsevier, vol. 109(C), pages 311-322.
    19. Abdul Ghani Olabi & Tabbi Wilberforce & Khaled Elsaid & Enas Taha Sayed & Tareq Salameh & Mohammad Ali Abdelkareem & Ahmad Baroutaji, 2021. "A Review on Failure Modes of Wind Turbine Components," Energies, MDPI, vol. 14(17), pages 1-44, August.
    20. Elena Sosnina & Andrey Dar’enkov & Andrey Kurkin & Ivan Lipuzhin & Andrey Mamonov, 2022. "Review of Efficiency Improvement Technologies of Wind Diesel Hybrid Systems for Decreasing Fuel Consumption," Energies, MDPI, vol. 16(1), pages 1-38, December.

    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:energy:v:116:y:2016:i:p1:p:202-213. 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/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.