Assessing the Reliability and Optimizing Input Parameters of the NWP-CFD Downscaling Method for Generating Onshore Wind Energy Resource Maps of South Korea

Abstract

The numerical weather prediction (NWP) method is one of the popular wind resource forecasting methods, but it has the limitation that it does not consider the influence of local topography. The NWP-CFD downscaling considers topographic features and surface roughness by performing computational fluid dynamics (CFD) with the meteorological data obtained by the NWP method as a boundary condition. The NWP-CFD downscaling is expected to be suitable for wind resource forecasting in Korea, but it lacks a quantitative evaluation of its reliability. In this study, we compare the actual measured data, the NWP-based data, and the NWP-CFD-based data quantitatively and analyze the three main input parameters used for the calculation of NWP-CFD (minimum vertical grid size Δzmin, the difference angle Δdir, and the forest model activation reference length l0). Compared to the actual measurement data, the NWP-based data overestimate wind resources by more than 35%, while the NWP-CFD-based data show an error of about 8.5%. The Δzmin and Δdir have little effect on the results, but the l0 has a large effect on the simulation results, and it is necessary to adjust the values appropriately corresponding to the characteristics of an area.