Reduction of Wind Turbine Noise Annoyance: An Operational Approach

Abstract

This paper investigates the relationship between wind turbine noise annoyance, exposure indicators, operational characteristics and environmental variables. A six-month field experiment at an industrial site near a residential area includes regular on-line annoyance reports, continuous 1/3-octave band noise level registrations, periodic sound recordings, data on electricity production per minute and meteorological observations. Here the risk of high annoyance does not only depend on the angular blade velocity, but also on the wind turbines' nacelle position relative to the location of the dwellings, i.e. the wind direction. This directivity effect can be captured when noise parameters such as the background noise level caused by other sources and a so-called fluctuation-indicator are introduced, the latter calculated from the 1/3-octave band spectra to quantify the periodic part of wind turbine noise. In addition, the calculated turbine's specific emission levels are closely related to the angular blade velocity, and an important parameter to predict the risk of high annoyance. Finally, these results suggest that operational restrictions based on wind direction together with the angular blade velocity might help to reduce noise annoyance while preserving cost-effectiveness.

Short-term annoyance reactions to stationary and time-varying wind turbine and road traffic noise: A laboratory study

“…However, this might have been different if the participants had lived close to wind turbines, thus being accustomed to WTN and potentially recognizing random AM as unrealistic. The results suggest that annoyance reactions to WTN may be at least partially reduced if the occurrence of periodic AM can be ruled out or at least strongly reduced, e.g., by blade pitch control (Makarewicz and Gołe Rbiewski, 2015) or an operational approach (Bockstael et al, 2012).…”

“…Current literature, as recently reviewed by McCunney et al (2014) and Schmidt and Klokker (2014), suggests that the annoyance reactions to WTN may be explained by a range of factors, namely, by the visibility of wind turbines (Knopper and Ollson, 2011), shadow flicker (Voicescu et al, 2016), the living environment of residents (Pedersen and Larsman, 2008), identifying wind turbines as the noise source leading to window closing (Michaud et al, 2016b), and by individual attributes such as noise sensitivity (Miedema and Vos, 2003), attitude (Pedersen and Persson Waye, 2004), or economic benefit (Pedersen et al, 2009), in addition to acoustic characteristics. With respect to the latter, periodic amplitude modulation (AM), i.e., periodic temporal level variations sometimes observed for WTN, might be particularly important (van den Berg, 2009;Bockstael et al, 2012;RenewableUK, 2013). However, it is not known which acoustic characteristics alone, i.e., without the consideration of effect modifiers, are associated with (noise) annoyance.…”

Annoyance, detection and recognition of wind turbine noise

“…In case of a tie, the highest level is selected. A similar processing has been used in Bockstael et al (2012). Noise sensitivity in the tested group is considered to be rather high.…”

Auralization of Wind Turbine Noise: Emission Synthesis

“…Following other authors [19,20,18,21] initial attempts were made in the frequency domain by searching for local maxima in high resolution PSDs. However, it turned out that at ime domain based method with the autocorrelation function yielded more robust results.…”