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A review on wind turbine noise mechanism and de-noising techniques

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  • Liu, W.Y.

Abstract

This paper reviews the wind turbine aerodynamic noise and mechanical noise mechanism and the de-noising methods in healthy condition monitoring (HCM). Fast development of the wind farm brings the problem of noise pollution, which can influence both the environment and the safety running of the turbine. To maintain the healthy running of the wind turbine, vibration-based signal analysis methods are introduced into wind turbine research. However, the noise interruption makes the feature extraction difficult in HCM. In order to suppress the noise, aerodynamic noise mechanism and mechanical noise mechanism are first analyzed separately. More and more wind turbine de-noising methods are proposed in recent years. Aerodynamic noise can be suppressed by structure optimization of the blade or the whole coupling system, or other similar numerical simulation and optimal methods. Mechanical noise can be de-noised by effective signal processing methods. Some ideal technologies are still needed according to the special characteristics of the wind turbine.

Suggested Citation

  • Liu, W.Y., 2017. "A review on wind turbine noise mechanism and de-noising techniques," Renewable Energy, Elsevier, vol. 108(C), pages 311-320.
    • Handle: RePEc:eee:renene:v:108:y:2017:i:c:p:311-320
    DOI: 10.1016/j.renene.2017.02.034
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    as
    1. Ryi, Jaeha & Choi, Jong-Soo & Lee, Seunghoon & Lee, Soogab, 2014. "A full-scale prediction method for wind turbine rotor noise by using wind tunnel test data," Renewable Energy, Elsevier, vol. 65(C), pages 257-264.
    2. Chen, Jinglong & Pan, Jun & Li, Zipeng & Zi, Yanyang & Chen, Xuefeng, 2016. "Generator bearing fault diagnosis for wind turbine via empirical wavelet transform using measured vibration signals," Renewable Energy, Elsevier, vol. 89(C), pages 80-92.
    3. Tabassum-Abbasi, & Premalatha, M. & Abbasi, Tasneem & Abbasi, S.A., 2014. "Wind energy: Increasing deployment, rising environmental concerns," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 270-288.
    4. Wang, Rong-Jie & Gerber, Stiaan, 2014. "Magnetically geared wind generator technologies: Opportunities and challenges," Applied Energy, Elsevier, vol. 136(C), pages 817-826.
    5. Kaldellis, J.K. & Apostolou, D. & Kapsali, M. & Kondili, E., 2016. "Environmental and social footprint of offshore wind energy. Comparison with onshore counterpart," Renewable Energy, Elsevier, vol. 92(C), pages 543-556.
    6. 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.
    7. Groth, Theresa M. & Vogt, Christine, 2014. "Residents' perceptions of wind turbines: An analysis of two townships in Michigan," Energy Policy, Elsevier, vol. 65(C), pages 251-260.
    8. Rahman, Mahmudur & Ong, Zhi Chao & Chong, Wen Tong & Julai, Sabariah & Khoo, Shin Yee, 2015. "Performance enhancement of wind turbine systems with vibration control: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 43-54.
    9. Yang, Dong & Li, Hui & Hu, Yaogang & Zhao, Jie & Xiao, Hongwei & Lan, Yongsen, 2016. "Vibration condition monitoring system for wind turbine bearings based on noise suppression with multi-point data fusion," Renewable Energy, Elsevier, vol. 92(C), pages 104-116.
    10. Tang, Baoping & Liu, Wenyi & Song, Tao, 2010. "Wind turbine fault diagnosis based on Morlet wavelet transformation and Wigner-Ville distribution," Renewable Energy, Elsevier, vol. 35(12), pages 2862-2866.
    11. de Almeida, L.A.L. & Filho, A.J. Sguarezi & Capovilla, C.E. & Casella, I.R.S. & Costa, F.F., 2016. "An impulsive noise filter applied in wireless control of wind turbines," Renewable Energy, Elsevier, vol. 86(C), pages 347-353.
    12. Liu, W.Y. & Zhang, W.H. & Han, J.G. & Wang, G.F., 2012. "A new wind turbine fault diagnosis method based on the local mean decomposition," Renewable Energy, Elsevier, vol. 48(C), pages 411-415.
    13. Katinas, Vladislovas & Marčiukaitis, Mantas & Tamašauskienė, Marijona, 2016. "Analysis of the wind turbine noise emissions and impact on the environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 825-831.
    14. Lee, Seunghoon & Lee, Soogab, 2014. "Numerical and experimental study of aerodynamic noise by a small wind turbine," Renewable Energy, Elsevier, vol. 65(C), pages 108-112.
    15. Rogers, T. & Omer, S., 2012. "The effect of turbulence on noise emissions from a micro-scale horizontal axis wind turbine," Renewable Energy, Elsevier, vol. 41(C), pages 180-184.
    16. Hammar, Linus & Wikström, Andreas & Molander, Sverker, 2014. "Assessing ecological risks of offshore wind power on Kattegat cod," Renewable Energy, Elsevier, vol. 66(C), pages 414-424.
    17. Liu, Wenyi & Tang, Baoping & Jiang, Yonghua, 2010. "Status and problems of wind turbine structural health monitoring techniques in China," Renewable Energy, Elsevier, vol. 35(7), pages 1414-1418.
    18. Hooper, Tara & Austen, Melanie, 2014. "The co-location of offshore windfarms and decapod fisheries in the UK: Constraints and opportunities," Marine Policy, Elsevier, vol. 43(C), pages 295-300.
    19. Ahmed, Noor A. & Cameron, Michael, 2014. "The challenges and possible solutions of horizontal axis wind turbines as a clean energy solution for the future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 439-460.
    20. Ruiz de la Hermosa González-Carrato, Raúl & García Márquez, Fausto Pedro & Dimlaye, Vichaar, 2015. "Maintenance management of wind turbines structures via MFCs and wavelet transforms," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 472-482.
    21. Yamani Douzi Sorkhabi, Sami & Romero, David A. & Yan, Gary Kai & Gu, Michelle Dao & Moran, Joaquin & Morgenroth, Michael & Amon, Cristina H., 2016. "The impact of land use constraints in multi-objective energy-noise wind farm layout optimization," Renewable Energy, Elsevier, vol. 85(C), pages 359-370.
    22. Mohamed, M.H., 2014. "Aero-acoustics noise evaluation of H-rotor Darrieus wind turbines," Energy, Elsevier, vol. 65(C), pages 596-604.
    23. 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.
    24. Wenyi, Liu & Zhenfeng, Wang & Jiguang, Han & Guangfeng, Wang, 2013. "Wind turbine fault diagnosis method based on diagonal spectrum and clustering binary tree SVM," Renewable Energy, Elsevier, vol. 50(C), pages 1-6.
    25. Auld, Trisha & McHenry, Mark P. & Whale, Jonathan, 2014. "Options to mitigate utility-scale wind turbine impacts on defence capability, air supremacy, and missile detection," Renewable Energy, Elsevier, vol. 63(C), pages 255-262.
    26. Nabe-Nielsen, Jacob & Sibly, Richard M. & Tougaard, Jakob & Teilmann, Jonas & Sveegaard, Signe, 2014. "Effects of noise and by-catch on a Danish harbour porpoise population," Ecological Modelling, Elsevier, vol. 272(C), pages 242-251.
    27. Kim, Taehyung & Jeon, Minu & Lee, Soogab & Shin, Hyungki, 2014. "Numerical simulation of flatback airfoil aerodynamic noise," Renewable Energy, Elsevier, vol. 65(C), pages 192-201.
    28. Kim, Sanghyeon & Cheong, Cheolung, 2015. "Development of low-noise drag-type vertical wind turbines," Renewable Energy, Elsevier, vol. 79(C), pages 199-208.
    29. McKenna, R. & Ostman v.d. Leye, P. & Fichtner, W., 2016. "Key challenges and prospects for large wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 1212-1221.
    30. Mohamed, M.H., 2016. "Reduction of the generated aero-acoustics noise of a vertical axis wind turbine using CFD (Computational Fluid Dynamics) techniques," Energy, Elsevier, vol. 96(C), pages 531-544.
    31. Mittal, Prateek & Kulkarni, Kedar & Mitra, Kishalay, 2016. "A novel hybrid optimization methodology to optimize the total number and placement of wind turbines," Renewable Energy, Elsevier, vol. 86(C), pages 133-147.
    32. Ying, Pei & Chen, Yong Kang & Xu, Yi Geng, 2015. "An aerodynamic analysis of a novel small wind turbine based on impulse turbine principles," Renewable Energy, Elsevier, vol. 75(C), pages 37-43.
    33. Liu, W.Y. & Tang, B.P. & Han, J.G. & Lu, X.N. & Hu, N.N. & He, Z.Z., 2015. "The structure healthy condition monitoring and fault diagnosis methods in wind turbines: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 466-472.
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