2 présentations au congrès Forum 2023
Des résultats obtenus dans le cadre de l'Axe 1 et 2 du projet seront présentés au prochain congrès international Forum Acusticum 2023 à Turin en Italie (11-15/09/2023) :
- Cotté, B., Mascarenhas, D., Ecotière, D.C., Guillaume, G., Gauvreau, B., Junker, F., 2023. Validation of a wind turbine noise propagation model against field measurements, in: Proc. Forum Acusticum. Presented at the Forum Acusticum, Torino.
Predicting the noise radiated by a wind farm needs to take into account many parameters such as wind turbine operational conditions, wind and temperature profiles, atmospheric turbulence, ground impedance and topography. In this study, we aim at validating a wind turbine noise prediction model that combines Amiet’s theory to calculate trailing edge noise and turbulence interaction noise with a wide-angle parabolic equation valid in moving media to account for long range acoustic propagation effects. The model considers the wind turbine as an extended and rotating noise source. The model predictions are compared to field measurements recorded during ten days around an eight-turbine single row wind farm. As the terrain is flatand the roughness is relatively homogeneous, the meteorological lidar and a mast data are supposed to be rangeindependent.
Using representative values for the ground parameters, the model gives the correct interference patterns in the third octave band spectrum. Accurate predictions of the third octave band spectra averaged over 10 minutes are obtained for propagation distances up to 1300 meters, although the influence of background noise becomes more significant as the distance increases.
- Bianchetti, S., Kayser, B., Guillaume, G., Gauvreau, B., Ecotière, D.C., 2023. Variability and uncertainty of wind farm noise: A comparison between numerical predictions and in-situ measurements, in: Proc. Forum Acusticum. Presented at the Forum Acusticum, Torino.
Wind farm noise depends on many environmental parameters that influence both sound emission and propagation. Poor knowledge of these parameters or their possible time and space fluctuations induce uncertainties leading to dispersion in SPL estimates. However, this dispersion is rarely taken into account, whereas it is not negligible realistic predictions. Thus, this paper presents a comparison between results of a model that estimates SPL dispersion of wind farm noise versus long-term experimental data. The uncertainty model is implemented in an open-access online tool (WindTUNE) developed within the French project PIBE. It is based on a metamodel embedded in a Shiny application, where noise emissions of each wind turbine of a wind farm are calculated using the Amiet’s theory, and sound propagation is calculated using a wide-angle Parabolic Equation (WAPE) modelling. Experimental data come from observations collected within the PIBE project near a wind farm for over 400 days. Comparisons are carried out for several scenarios encountered during the experimental campaign, with various values of influential parameters. Finally, the paper provides information on the reliability of our modelling approach for the estimation of variability and uncertainty of wind farm noise.