LAUSR

This work shows the development of a tool for wind farm layout optimization based on computational fluid dynamics (CFD) simulations of the atmospheric wind flow and inter-turbine interference. Due to the high computational power required to simulate a whole wind farm using the complete geometry of the wind turbines, simplified models were developed to represent the turbine behavior, and the most commonly used model is the actuator disk model and its variations. The procedure for wind turbine behavior evaluation using a CFD model was implemented in the OpenFOAM software, and this model was coupled with the Dakota optimization toolkit. A genetic algorithm was selected for the optimization task due to its robustness and the characteristics of the problem solved. With this new tool in hand, three different terrain cases, with growing complexity, were tested considering different numbers of turbines on a cylindrical domain in order to achieve the best wind farm layout in terms of annual energy production that respects the imposed physical restrictions. As expected, the layout efficiency decreased as turbines were added to the domain, meaning that wake losses are introduced in this process. For the simpler domains, we observed that this efficiency decrease was approximately linear with respect to the number of turbines. Complex phenomena were captured during the optimization, such as wake deflection, different wake recoveries depending on the wind speed and interaction between the disturbances in the flow field caused by the terrain and by the turbines. These phenomena are not observed when using the tools available in the wind market and are seen as an improvement in the field of wind farm layout optimization, yielding more accurate results, and should decrease the level of uncertainty in the design of a wind farm.