Abstract

Utility scale wind turbines produce a significant amount of noise which has been identified as one of the most critical challenges to the widespread use of wind energy. Aerodynamic noise caused primarily by the interaction of the boundary layer and (or) the upstream atmospheric turbulence with the trailing edge of the blade has been identified as the most dominant source of noise in wind turbines. The authors here propose an active noise control system based on the FxLMS algorithm which can achieve suppression of noise from a modern wind turbine. Two types of noise sources have been simulated: monopole and dipole. The results of the active noise control algorithm are validated with simulations in MATLAB. The agreement between the results shows the far impact of active noise control techniques will have in future wind turbines.

Highlights

  • Over the past few decades, wind energy has come up to becoming one of the most popular sources of clean energy

  • The agreement between the results shows the far impact of active noise control techniques will have in future wind turbines

  • This article is aimed at modeling a wind turbine noise source for different directivity patterns and thereafter showing how real-time noise reduction can be achieved for the different acoustic models by employing the FxLMS adaptation algorithm

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Summary

Introduction

Over the past few decades, wind energy has come up to becoming one of the most popular sources of clean energy. Besides being a clean fuel source, it is cost-effective when compared to the conventional sources of power generation. The choice of wind energy has often been criticized owing to the constant noise being generated from wind turbines and farms. Various research studies have shown that constant exposure to noise generated from. Low frequency noise, may cause sleep disturbances, fatigue and other various physiological effects [2]. Significant research effort in modern wind turbine technology has been to achieve reduction of wind turbine noise [3] [4] [5] [6]

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