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A Feasibility Study to Reduce Infrasound Emissions from Existing Wind Turbine Blades Using a Biomimetic Technique

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  • Jinlei Lv

    (School of Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
    China Aerodynamics Research and Development Center, Facility Design and Instrumentation Institute, Mianyang 621000, China
    State Key Laboratory of Aerodynamics, China Aerodynamics Research and Development Center, Mianyang 621000, China)

  • Wenxian Yang

    (School of Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU, UK)

  • Haiyang Zhang

    (China Aerodynamics Research and Development Center, Facility Design and Instrumentation Institute, Mianyang 621000, China
    State Key Laboratory of Aerodynamics, China Aerodynamics Research and Development Center, Mianyang 621000, China)

  • Daxiong Liao

    (China Aerodynamics Research and Development Center, Facility Design and Instrumentation Institute, Mianyang 621000, China
    State Key Laboratory of Aerodynamics, China Aerodynamics Research and Development Center, Mianyang 621000, China)

  • Zebin Ren

    (China Aerodynamics Research and Development Center, Facility Design and Instrumentation Institute, Mianyang 621000, China
    State Key Laboratory of Aerodynamics, China Aerodynamics Research and Development Center, Mianyang 621000, China)

  • Qin Chen

    (China Aerodynamics Research and Development Center, Facility Design and Instrumentation Institute, Mianyang 621000, China
    State Key Laboratory of Aerodynamics, China Aerodynamics Research and Development Center, Mianyang 621000, China)

Abstract

Infrasound, i.e., low-frequency noise in the frequency range of 10–200 Hz, produced by rotating wind turbine blades has become a matter of concern because it is harmful to human health. Today, with the rapid increase of wind turbine size, this kind of noise is more worrying than ever. Although much effort has been made to design quiet wind turbine blades, today there is still a lack of effective techniques to reduce infrasound emissions from existing blades. To fill this gap in technology, a biomimetic technique that can be readily applied to reduce infrasound emissions of existing wind turbine blades is studied in this paper using both numerical simulation and experimental testing approaches. The numerical study of the technique is based on the analysis of the sound field distribution near the blade, which is derived by performing both aerodynamic and acoustic simulations of the blade. The experimental study of the technique is based on laboratory tests of two scale models of the blade. Both numerical and experimental studies have shown that the shedding vortices behind the blade can be successfully suppressed by semi-cylindrical rings wrapped on the blade. Consequently, both infrasound and the overall sound pressure level of the noise produced by the blade are significantly reduced. Although the rings fail to show good performance in reducing high-frequency noise, it is not a problem for human health because high-frequency noise is weak and moreover it attenuates rapidly as distance increases. The research also showed that the proposed technique can, not only reduce the infrasound produced by the blade, but can also improve the power coefficient of wind turbines.

Suggested Citation

  • Jinlei Lv & Wenxian Yang & Haiyang Zhang & Daxiong Liao & Zebin Ren & Qin Chen, 2021. "A Feasibility Study to Reduce Infrasound Emissions from Existing Wind Turbine Blades Using a Biomimetic Technique," Energies, MDPI, vol. 14(16), pages 1-18, August.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:16:p:4923-:d:612614
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    References listed on IDEAS

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    1. Luo, Kun & Zhang, Sanxia & Gao, Zhiying & Wang, Jianwen & Zhang, Liru & Yuan, Renyu & Fan, Jianren & Cen, Kefa, 2015. "Large-eddy simulation and wind-tunnel measurement of aerodynamics and aeroacoustics of a horizontal-axis wind turbine," Renewable Energy, Elsevier, vol. 77(C), pages 351-362.
    2. 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.
    3. Ghasemian, Masoud & Nejat, Amir, 2015. "Aero-acoustics prediction of a vertical axis wind turbine using Large Eddy Simulation and acoustic analogy," Energy, Elsevier, vol. 88(C), pages 711-717.
    4. Tadamasa, A. & Zangeneh, M., 2011. "Numerical prediction of wind turbine noise," Renewable Energy, Elsevier, vol. 36(7), pages 1902-1912.
    5. Wenxian Yang & Theodoros Alexandridis & Wenye Tian, 2018. "Numerical Research of the Effect of Surface Biomimetic Features on the Efficiency of Tidal Turbine Blades," Energies, MDPI, vol. 11(4), pages 1-15, April.
    6. Abbasi, S.A. & Tabassum-Abbasi, & Abbasi, Tasneem, 2016. "Impact of wind-energy generation on climate: A rising spectre," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1591-1598.
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    1. Tomasz Malec & Tomasz Boczar & Daria Wotzka & Michał Kozioł, 2021. "Measurement and Analysis of Infrasound Signals Generated by Operation of High-Power Wind Turbines," Energies, MDPI, vol. 14(20), pages 1-21, October.

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