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An Aero-acoustic Noise Distribution Prediction Methodology for Offshore Wind Farms

Author

Listed:
  • Jiufa Cao

    (School of Hydraulic Energy and Power Engineering, Yangzhou University, Yangzhou 225127, China)

  • Weijun Zhu

    (School of Hydraulic Energy and Power Engineering, Yangzhou University, Yangzhou 225127, China)

  • Xinbo Wu

    (School of Hydraulic Energy and Power Engineering, Yangzhou University, Yangzhou 225127, China)

  • Tongguang Wang

    (Jiangsu Key Laboratory of Hi-Tech Research for Wind Turbine Design, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, China)

  • Haoran Xu

    (School of Hydraulic Energy and Power Engineering, Yangzhou University, Yangzhou 225127, China
    GCL Intelligent Energy Co., Ltd., Suzhou 215000, China)

Abstract

Recently attention has been paid to wind farm noise due to its negative health impact, not only on human beings, but also to marine and terrestrial organisms. The current work proposes a numerical methodology to generate a numerical noise map for a given wind farm. Noise generation from single wind turbines as well as wind farms has its basis in the nature of aerodynamics, caused by the interactions between the incoming turbulent flow and the wind turbine blades. Hence, understanding the mechanisms of airfoil noise generation, demands access to sophisticated numerical tools. The processes of modeling wind farm noise include three steps: (1) The whole wind farm velocity distributions are modelled with an improved Jensen’s wake model; (2) The individual wind turbine’s noise is simulated by a semi-empirical wind turbine noise source model; (3) Propagations of noise from all wind turbines are carried out by solving the parabolic wave equation. In the paper, the wind farm wake effect from the Horns Rev wind farm is studied. Based on the resulted wind speed distributions in the wind farm, the wind turbine noise source and its propagation are simulated for the whole wind farm.

Suggested Citation

  • Jiufa Cao & Weijun Zhu & Xinbo Wu & Tongguang Wang & Haoran Xu, 2018. "An Aero-acoustic Noise Distribution Prediction Methodology for Offshore Wind Farms," Energies, MDPI, vol. 12(1), pages 1-16, December.
    • Handle: RePEc:gam:jeners:v:12:y:2018:i:1:p:18-:d:192398
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    References listed on IDEAS

    as
    1. Wu, Yu-Ting & Porté-Agel, Fernando, 2015. "Modeling turbine wakes and power losses within a wind farm using LES: An application to the Horns Rev offshore wind farm," Renewable Energy, Elsevier, vol. 75(C), pages 945-955.
    2. Umberto Ciri & Giovandomenico Petrolo & Maria Vittoria Salvetti & Stefano Leonardi, 2017. "Large-Eddy Simulations of Two In-Line Turbines in a Wind Tunnel with Different Inflow Conditions," Energies, MDPI, vol. 10(6), pages 1-23, June.
    3. José F. Herbert-Acero & Oliver Probst & Pierre-Elouan Réthoré & Gunner Chr. Larsen & Krystel K. Castillo-Villar, 2014. "A Review of Methodological Approaches for the Design and Optimization of Wind Farms," Energies, MDPI, vol. 7(11), pages 1-87, October.
    4. Tian, Linlin & Zhu, Weijun & Shen, Wenzhong & Song, Yilei & Zhao, Ning, 2017. "Prediction of multi-wake problems using an improved Jensen wake model," Renewable Energy, Elsevier, vol. 102(PB), pages 457-469.
    5. Göçmen, Tuhfe & Laan, Paul van der & Réthoré, Pierre-Elouan & Diaz, Alfredo Peña & Larsen, Gunner Chr. & Ott, Søren, 2016. "Wind turbine wake models developed at the technical university of Denmark: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 752-769.
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