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With rising levels of wind power penetration in global electricity production, the relevance of wind power prediction is growing. More accurate forecasts reduce the required total amount of energy reserve capacity needed to ensure grid reliability and the risk of penalty for wind farm operators. This study analyzes the Computational Fluid Dynamics (CFD) software WindSim regarding its ability to perform accurate wind power predictions in complex terrain. Simulations of the wind field and wind farm power output in the Swiss Jura Mountains at the location of the Juvent Wind Farm during winter were performed. The study site features the combined presence of three complexities: topography, heterogeneous vegetation including forest, and interactions between wind turbine wakes. Hence, it allows a comprehensive evaluation of the software. Various turbulence models, forest models, and wake models, as well as the effects of domain size and grid resolution were evaluated against wind and power observations from nine Vestas V90’s 2.0-MW turbines. The results show that, with a proper combination of modeling options, WindSim is able to predict the performance of the wind farm with sufficient accuracy.
Fernando Porté Agel, Peter Andreas Brugger, Corey Dean Markfort
Michael Lehning, Wolf Hendrik Huwald, Jérôme François Sylvain Dujardin, Franziska Gerber, Fanny Kristianti, Sebastian Wilhelm Hoch