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Airfoil optimization to improve power performance of a high-solidity vertical axis wind turbine at a moderate tip speed ratio

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  • Ma, Ning
  • Lei, Hang
  • Han, Zhaolong
  • Zhou, Dai
  • Bao, Yan
  • Zhang, Kai
  • Zhou, Lei
  • Chen, Caiyong

Abstract

The relatively low power coefficient restricts the wide application of vertical axis wind turbines (VAWTs). An effective solution to this problem is to design specific airfoil profiles which directly influence the capture ratio of wind power. The main aim of the present study is to develop an automatic airfoil profile optimization system to improve the power performance of a VAWT. A three-bladed high-solidity VAWT is adopted as the research object with its chord length, blade span and rotor diameter being 0.2 m, 0.8 m and 0.8 m, respectively. The optimization is conducted at a moderate tip speed ratio (TSR) with a value of 1.0 and the method of coupled CFD simulations with genetic algorithms is employed. The following points make this paper different from previous studies: (a) introducing Multi-Island Genetic Algorithm to optimize airfoils for VAWTs; (b) investigating the airfoil as part of the VAWT rather than as a single isolated body with 3D simulations. The results show that the power coefficient of the VAWT equipped with the optimized blades sensibly improves at all TSRs from 0.4 to 1.5 and the maximum growth rate of it occurs at TSR = 0.9 with a value of 26.82%. The integrated optimization system used in this paper provides an effective way to generate suitable airfoil profiles for given VAWTs with the goal to achieve higher power efficiency.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:150:y:2018:i:c:p:236-252
    DOI: 10.1016/j.energy.2018.02.115
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    19. Zhang, Yanfeng & Guo, Zhiping & Zhu, Xinyu & Li, Yuan & Song, Xiaowen & Cai, Chang & Kamada, Yasunari & Maeda, Takao & Li, Qing’an, 2022. "Investigation of aerodynamic forces and flow field of an H-type vertical axis wind turbine based on bionic airfoil," Energy, Elsevier, vol. 242(C).
    20. Liu, Qingsong & Miao, Weipao & Li, Chun & Hao, Winxing & Zhu, Haitian & Deng, Yunhe, 2019. "Effects of trailing-edge movable flap on aerodynamic performance and noise characteristics of VAWT," Energy, Elsevier, vol. 189(C).
    21. Chen, Yaoran & Su, Jie & Han, Zhaolong & Zhao, Yongsheng & Zhou, Dai & Yang, He & Bao, Yan & Lei, Hang, 2020. "A shape optimization of ϕ-shape Darrieus wind turbine under a given range of inlet wind speed," Renewable Energy, Elsevier, vol. 159(C), pages 286-299.
    22. Liang Li & Inderjit Chopra & Weidong Zhu & Meilin Yu, 2021. "Performance Analysis and Optimization of a Vertical-Axis Wind Turbine with a High Tip-Speed Ratio," Energies, MDPI, vol. 14(4), pages 1-30, February.
    23. Wang, Longyan & Xu, Jian & Wang, Zilu & Zhang, Bowen & Luo, Zhaohui & Yuan, Jianping & Tan, Andy C.C., 2023. "A novel cost-efficient deep learning framework for static fluid–structure interaction analysis of hydrofoil in tidal turbine morphing blade," Renewable Energy, Elsevier, vol. 208(C), pages 367-384.

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