Spatial prediction of wind farm outputs using the Augmented Kriging-based Model

Wind generating resources have been increasing more rapidly than any other renewable generating resources. Wind farm output prediction is an important issue for deploying higher wind power penetrations on power grids. The existing work on wind farm output prediction has focused on the temporal issues. As wind farm outputs depend on natural wind resources that vary over space and time, spatial analysis and modeling is also needed. Predictions about suitability for locating new wind generating resources can be performed by optimal spatial modeling. In this paper, a new approach to spatial prediction of wind farm outputs is proposed using the Augmented Kriging-based Model (AKM).