Wind Power Forecasting - Physical Approach To Wind Power Forecasting

Physical Approach To Wind Power Forecasting

Meteorological forecasts are given at specific nodes of a grid covering an area. Since wind farms are not situated on these nodes, it is then needed to extrapolate these forecasts at the desired location and at turbine hub height. Physical-based forecasting methods consist of several sub-models which altogether deliver the translation from the wind forecast at a certain grid point and model level, to power forecast at the site considered. Every sub-model contains the mathematical description of the physical processes relevant to the translation. Knowledge of all relevant processes is therefore crucial when developing a purely physical prediction method (such as the early versions of the Danish Prediktor). The core idea of physical approaches is to refine the NWPs by using physical considerations about the terrain such as the roughness, orography and obstacles, and by modeling the local wind profile possibly accounting for atmospheric stability. The two main alternatives to do so are: (i) to combine the modeling of the wind profile (with a logarithmic assumption in most of the cases) and the geostrophic drag law for obtaining surface winds; (ii) to use a CFD (Computational Fluid Dynamics) code that allows one to accurately compute the wind field that the farm will see, considering a full description of the terrain.

When the wind at the level of the wind farm and at hub height is known, the second step consists in converting wind speed to power. Usually, that task is carried out with theoretical power curves. However, since several studies have shown the interest of using empirically derived power curve instead of theoretical ones, theoretical power curves are less and less considered. When applying a physical methodology, the modeling of the function which gives the wind generation from NWPs at given locations around the wind farm is done once for all. Then, the estimated transfer function is consequently applied to the available weather predictions at a given moment. In order to account for systematic forecasting errors that may be due to the NWP model or to their modeling approach, physical modelers often integrate Model Output Statistics (MOS) for post-processing power forecasts.