Wind Potential/Power Estimation Based on Unsteady OpenFOAM Solutions Coupled with WRF
Current wind power prediction tools mostly employ Computational Fluid Dynamics (CFD) models which are based on statistical observation data obtained from wind-masts. CFD models first simulate sectoral wind fields over a region of interest. The dominant wind field is then reconstructed by correlating the statistical wind mast data at a single point to the sectoral wind fields simulated. The reconstructed wind field may be used for micro-siting of wind turbines, and for the annual energy production estimation of a wind farm. In the current study, unsteady atmospheric flows in complex terrains are simulated by the open source flow solver OpenFOAM coupled with the mesoscale weather prediction software, WRF. The low resolution, unsteady WRF solution provides the spatially varying unsteady boundary conditions for the OpenFOAM solution on high resolution terrain fitted viscous grids. The unsteady wind fields integrated in time provide accurate wind energy production estimations and may be used for micro-siting of wind turbines. The coupled unsteady flow solutions are validated and it is shown that the predictions compare well with the wind mast data.