Statistical characteristics of interacting wind turbine wakes from a 7-month LiDAR measurement campaign

Abstract

Abstract The present study focuses on the wakes of two wind turbines that, depending on the wind direction, experienced different degrees of interactions, by processing field wake observations made from a 7-month ground based scanning LiDAR measurement campaign. This duration ensures an acceptable statistical convergence of the ensemble-averaged flow fields obtained after a classification according to the wind speed at hub height and the wind direction, and limited to neutral atmospheric stability. The mean flow fields showed a well-defined wake evolution for all configurations. As expected, the wake centerlines are aligned with the wind direction, however when wakes are in intermediate interaction, wakes centerlines are skewed. This has been imputed to the wake center determination method, which is not appropriate to dissociate multiple wakes. For the lower degree of interactions, the mean wakes are aligned. However the standard deviation of the instantaneous wake centerlines shows the mutual influence that one wake has on the other. Obtained results showed an increase in the turbulence intensity within the wake, but an asymmetric distribution was observed. Listing the possible reasons, no plausible explanation has been found. The wake meandering had been quantified by the standard deviation of the instantaneous wake centerlines, showing that this phenomenon is amplified by the level of interactions. The velocity deficit recovery showed a good agreement with proposed models, as soon as there is no neighboring wakes. If that is the case, the velocity deficit is increased in function of the position of the neighboring rotor.