Abstract
The prediction of a wind farm near the wind turbines has a significant effect on the safety as well as economy of wind power generation. To assess the wind resource distribution within a complex terrain, a computational fluid dynamics (CFD) based wind farm forecast microscale model is developed. The model uses the Reynolds Averaged Navier-Stokes (RANS) model to characterize the turbulence. By using the results of Weather Research and Forecasting (WRF) mesoscale weather forecast model as the input of the CFD model, a coupled model of CFD-WRF is established. A special method is used for the treatment of the information interchange on the lateral boundary between two models. This established coupled model is applied in predicting the wind farm near a wind turbine in Hong Gang-zi, Jilin, China. The results from this simulation are compared to real measured data. On this basis, the accuracy and efficiency of turbulence characterization schemes are discussed. It indicates that this coupling system is easy to implement and can make these two separate models work in parallel. The CFD model coupled with WRF has the advantage of high accuracy and fast speed, which makes it valid for the wind power generation.
Highlights
Energy is one of the most valuable consumables of human society
Weather Research and Forecasting (WRF) model uses the dynamics equations built in the p-σ coordinates, the output results will be transformed into spherical coordinates of the earth
Because the WRF model is the only input of the computational fluid dynamics (CFD) model, the wind velocity of two models increases or decreases with the inflection point appearing in different positions
Summary
Energy is one of the most valuable consumables of human society. With energy shortage becoming obvious, the demand for renewable energy is rapidly increasing. The demand for a more precise prediction of atmospheric processes calls for the improvement of the resolution of model and grid. It will cause extreme increase of computation and time expense if the fine mesh model is used with higher resolution in the whole prediction area and making the model unable to meet the requirements of fast prediction. The solution is applying the microscale model in the concerned local region on the background of mesoscale meteorological model. This method is called the coupling model method. Several meteorological CFD models have been founded, such as WindSim of Norway and Meteodyn WT of France [3][4]
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