Stochastic calibration of the actuator line model parameters

Since the numerical representation of wind turbine blades leads to simulations beyond the present computational resources, simplified models are usually employed. We focus on the Actuator Line Model (ALM), in which the blade is replaced by a rotating line divided into finite segments with representative aerodynamic coefficients. The Lift and Drag forces are distributed among the nearest grid points by using a Gaussian kernel. The standard deviation of this kernel and the reference velocity are two fundamental parameters that strongly affect the characteristics of the wind turbine wake. The sensitivity of the ALM predictions to these parameters is here investigated by comparing the wake features obtained in Large Eddy Simulations of the flow around a 2D airfoil (NACA 0009) with the results of simulations in which the body is modeled by ALM. We adopt a stochastic approach to the sensitivity analysis to obtain a continuous response surfaces of the quantities of interest in the parameter space, starting from a few simulations. Attention is focused on the influence of these parameters on the prediction of the mean velocity field and of the turbulent kinetic energy in the wake. This also permits to identify the values of the model parameters providing the best agreement with LES.