Parameterization of Wind Evolution using Lidar

Abstract. Wind evolution refers to the change of the turbulence structure of the eddies over time while the eddies are advected by the main flow over space. With the development of the lidar-assisted wind turbine control, modelling of the wind evolution becomes an interesting topic, because the control system should only react to the changes in the wind field which can be predicted accurately over the distance to avoid harmful and unnecessary control action. This paper aims to achieve a parameterization model for the wind evolution model to predict the wind evolution model parameters according to the wind field conditions. For this purpose, a two-parameter wind evolution model suggested in literature was applied to model the wind evolution and the wind evolution was estimated using lidar data. A statistical analysis was done to reveal the characteristics of wind evolution model parameters. Gaussian process regression was applied to achieve the parameterization model. The results have proven the applicability of Gaussian process regression model to predict the wind evolution model parameters with sufficient accuracy.