Presentation au congrès WTN 2023

 

Noise in the vicinity of a wind farm is influenced by many environmental parameters such as wind, ground or atmospheric properties for example. The values of these parameters are associated with uncertainties due to poor knowledge of parameters or to possible time and  space fluctuations during the period for which the noise estimate is required. Those uncertainties induce dispersion in the SPL estimation that are rarely taken into account. However they are not negligible and they influence the quality of the prediction.

The paper presents a web tool developed within the French project PIBE, which aims at quantifying the SPL uncertainty of wind farm noise predictions. The tool uses a metamodel based on the calculation of the noise emission of each wind turbine of a wind farm using the Amiet’s theory, and of its propagation using a wide-angle parabolic equation modelling. Sound pressure level distributions and uncertainties are estimated thanks to a quasi Monte-Carlo technique which considers the propagation of distributions of the main influent environmental parameters (e.g. wind speed, wind direction, ground absorption…). The tool will be freely available online at the end of the PIBE project. It will help to better evaluate uncertainties and thus to take into account the risk of noise pollution of local population regarding regulatory requirements.

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L'outil WindTUNE sera librement accessible via une interface web fin 2023.

Cet outil permettra d'évaluer la distribution statistique du niveau sonore au voisinage d'un parc éolien, en fonction des incertitudes de différents paramètres de l'environnement (vent, sol, etc).