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.

Wind turbines represent an encouraging option for sustainable energy but their noise emissions can be an issue for their public acceptance. Noise reduction measures, such as trailing-edge serrations or permeable inserts, seem to offer promising results in reducing wind turbine noise levels. This manuscript presents a novel holistic approach for perception-based evaluation of wind turbine noise and the performance of reduction measures using synthetic sound auralization. To demonstrate its feasibility, a case study featuring four state-of-the-art noise reduction trailing-edge add-ons synthetically applied to two full-scale wind turbines at nominal power is presented. The synthetic sound signals were auralized and propagated to three observer locations. The expected annoyance in each case was estimated by employing a combination of psychoacoustic sound quality metrics and a listening experiment featuring 16 participants. A close relation was found between the results of the psychoacoustic metrics and the listening experiment. In general, this holistic approach provides valuable information for the design of optimal noise reduction measures and wind turbines.