Adaptive neuro-fuzzy methodology for noise assessment of wind turbine.

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ID: 41683
2014
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Abstract
Wind turbine noise is one of the major obstacles for the widespread use of wind energy. Noise tone can greatly increase the annoyance factor and the negative impact on human health. Noise annoyance caused by wind turbines has become an emerging problem in recent years, due to the rapid increase in number of wind turbines, triggered by sustainable energy goals set forward at the national and international level. Up to now, not all aspects of the generation, propagation and perception of wind turbine noise are well understood. For a modern large wind turbine, aerodynamic noise from the blades is generally considered to be the dominant noise source, provided that mechanical noise is adequately eliminated. The sources of aerodynamic noise can be divided into tonal noise, inflow turbulence noise, and airfoil self-noise. Many analytical and experimental acoustical studies performed the wind turbines. Since the wind turbine noise level analyzing by numerical methods or computational fluid dynamics (CFD) could be very challenging and time consuming, soft computing techniques are preferred. To estimate noise level of wind turbine, this paper constructed a process which simulates the wind turbine noise levels in regard to wind speed and sound frequency with adaptive neuro-fuzzy inference system (ANFIS). This intelligent estimator is implemented using Matlab/Simulink and the performances are investigated. The simulation results presented in this paper show the effectiveness of the developed method.
Reference Key
shamshirband2014adaptiveplos Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Shamshirband, Shahaboddin;Petković, Dalibor;Hashim, Roslan;Motamedi, Shervin;
Journal PloS one
Year 2014
DOI
10.1371/journal.pone.0103414
URL
Keywords Keywords not found

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