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Variability of wind turbine noise over a diurnal cycle

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  • Barlas, Emre
  • Wu, Ka Ling
  • Zhu, Wei Jun
  • Porté-Agel, Fernando
  • Shen, Wen Zhong

Abstract

The diurnal variation of atmospheric conditions over land has a significant effect on the wind and temperature distributions which greatly influence the generation and propagation of wind turbine aerodynamic sound. In this paper, a fully consistent unsteady approach is used to study wind turbine noise such that large eddy simulation with a rotational actuator disk wind turbine model is used to model the wind and temperature around a mega-watt scale wind turbine over a diurnal cycle, and time dependent flow and temperature fields are used as input to the coupled wind turbine noise generation-propagation model. Computations are carried out for four different 10 min datasets selected at certain periods of a day for a same hub height wind speed. It is observed that the time dependent as well as the time averaged sound pressure levels in near field do not show large variations during the day. However, as we move away from the turbine, the propagation effects take over and downwind of the turbine the night time levels exceed the day time levels (at 3600 m the averaged difference reaches 6.5 dBA).

Suggested Citation

  • Barlas, Emre & Wu, Ka Ling & Zhu, Wei Jun & Porté-Agel, Fernando & Shen, Wen Zhong, 2018. "Variability of wind turbine noise over a diurnal cycle," Renewable Energy, Elsevier, vol. 126(C), pages 791-800.
  • Handle: RePEc:eee:renene:v:126:y:2018:i:c:p:791-800
    DOI: 10.1016/j.renene.2018.03.086
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    References listed on IDEAS

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    1. Zhong, Hongmin & Du, Pingan & Tang, Fangning & Wang, Li, 2015. "Lagrangian dynamic large-eddy simulation of wind turbine near wakes combined with an actuator line method," Applied Energy, Elsevier, vol. 144(C), pages 224-233.
    2. Veisi, Amin Allah & Shafiei Mayam, Mohammad Hossein, 2017. "Effects of blade rotation direction in the wake region of two in-line turbines using Large Eddy Simulation," Applied Energy, Elsevier, vol. 197(C), pages 375-392.
    3. 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.
    4. Mahdi Abkar & Fernando Porté-Agel, 2013. "The Effect of Free-Atmosphere Stratification on Boundary-Layer Flow and Power Output from Very Large Wind Farms," Energies, MDPI, vol. 6(5), pages 1-24, April.
    5. Betakova, Vendula & Vojar, Jiri & Sklenicka, Petr, 2015. "Wind turbines location: How many and how far?," Applied Energy, Elsevier, vol. 151(C), pages 23-31.
    6. Bastankhah, Majid & Porté-Agel, Fernando, 2014. "A new analytical model for wind-turbine wakes," Renewable Energy, Elsevier, vol. 70(C), pages 116-123.
    7. Castellani, Francesco & Vignaroli, Andrea, 2013. "An application of the actuator disc model for wind turbine wakes calculations," Applied Energy, Elsevier, vol. 101(C), pages 432-440.
    8. Molnarova, Kristina & Sklenicka, Petr & Stiborek, Jiri & Svobodova, Kamila & Salek, Miroslav & Brabec, Elizabeth, 2012. "Visual preferences for wind turbines: Location, numbers and respondent characteristics," Applied Energy, Elsevier, vol. 92(C), pages 269-278.
    9. Tsoutsos, Theocharis & Tsouchlaraki, Androniki & Tsiropoulos, Manolis & Serpetsidakis, Michalis, 2009. "Visual impact evaluation of a wind park in a Greek island," Applied Energy, Elsevier, vol. 86(4), pages 546-553, April.
    10. 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.
    11. Fernando Porté-Agel & Yu-Ting Wu & Chang-Hung Chen, 2013. "A Numerical Study of the Effects of Wind Direction on Turbine Wakes and Power Losses in a Large Wind Farm," Energies, MDPI, vol. 6(10), pages 1-17, October.
    12. Barthelmie, R.J. & Pryor, S.C., 2013. "An overview of data for wake model evaluation in the Virtual Wakes Laboratory," Applied Energy, Elsevier, vol. 104(C), pages 834-844.
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    Cited by:

    1. Li, Jian & Liu, Ranhui & Yuan, Peng & Pei, Yanli & Cao, Renjing & Wang, Gang, 2020. "Numerical simulation and application of noise for high-power wind turbines with double blades based on large eddy simulation model," Renewable Energy, Elsevier, vol. 146(C), pages 1682-1690.
    2. Cao, Jiufa & Nyborg, Camilla Marie & Feng, Ju & Hansen, Kurt S. & Bertagnolio, Franck & Fischer, Andreas & Sørensen, Thomas & Shen, Wen Zhong, 2022. "A new multi-fidelity flow-acoustics simulation framework for wind farm application," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).

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