Psychoacoustic model for predicting wind turbine noise annoyance

Conference paper (2022)

Authors

R. Merino Martinez Aircraft Noise and Climate Effects - Aerospace Engineering
Reto Pieren Swiss Federal Laboratories for Materials Science and Technology (Empa)
Beat Schäffer Swiss Federal Laboratories for Materials Science and Technology (Empa)
D.G. Simons Aircraft Noise and Climate Effects - Aerospace Engineering
Research Group
Aircraft Noise and Climate Effects (Aerospace Engineering) (TU Delft)
Copyright: © 2022 R. Merino Martinez, Reto Pieren, Beat Schäffer, D.G. Simons
Wind turbine noise Noise annoyance Psychoacoustics
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Published Date

2022

Language

English

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Faculty

Aerospace Engineering

Department

Control & Operations

Research Group

Aircraft Noise and Climate Effects

Abstract

Noise annoyance caused by wind turbines is a critical issue for the societal acceptance of wind energy. Wind turbine noise exposure is typically assessed using conventional time–averaged metrics, however, the literature suggests that these metrics do not fully capture the sound properties responsible for the perceived noise annoyance. Therefore, it is questionable to assess wind turbine noise and its abatement strategies using only such metrics. This paper presents a novel psychoacoustic model for predicting wind turbine noise annoyance that combines perception–based sound quality metrics. To establish the psychoacoustic model, the synthetic sound signals of two different wind turbines equipped with four state–of–the–art noise reduction add–ons (two types of trailing–edge serrations and two types of trailing–edge permeable materials inserts) were studied. Using a parametric wind turbine noise generator, the simulated sound signals were auralized at different observer positions and their noise annoyance was evaluated in two laboratory listening experiments with 16 and 10 subjects, respectively. The psychoacoustic annoyance model proposed here provides a very close agreement with the results of the listening experiment and improved accuracy compared to conventional sound metrics.