CFD-based Methodology for Wind Farm Layout Optimization

Driven by concerns on climate change and global warming, increasing oil prices, government support and public receptiveness, wind energy harvesting is emerging as one of the fastest growing renewable energy technologies. Most wind energy is nowadays produced by wind farms, which consist of hundreds of turbines to take advantage of economies of scale. Wind farm performance is however affected by the wakes generated by the turbines which can significantly diminish their annual energy production. Accurate wake effect predictions and reliable wind farm layout design become therefore critical aspects to the economic success of a wind farm project. The present research project aims therefore to define an innovative design framework that integrates accurate wake effect predictions for the development of the next generation wind farms as part of the strategy for promoting the transition to a renewable energy generation. Computational fluid dynamics (CFD) provides a unique tool to simulate wind turbine wakes because of its capability to provide a complete solution for the flow field in complex configurations. Nevertheless, CFD simulations are strongly influenced by the choice of the turbulence model used to close the Reynolds-averaged Navier-Stokes (RANS) equations. We therefore conducted an analysis of different turbulence models and their influence on the results of CFD wind turbine simulations to suggest the most suitable for such applications. Even though proper turbulence modeling is adopted, several studies showed however that the effectiveness of RANS models in wind farm simulations has not always been consistent. We therefore hypothesized this limitation to arise from uncertainties generated by the wind direction variability and proposed a modeling framework that, by accounting for such uncertainties, consistently improved the agreement of the CFD predictions with the experimental observations. To integrate the CFD models in a design methodology, we developed an innovative continuous adjoint formulation for gradient calculations within the framework of a gradient-based wind farm layout optimization. By testing this optimization methodology under different wind farm configurations, wind resource distributions and terrain topography, we showed that this unique CFD-based design framework effectively improved the annual energy production of a proposed wind farm by optimally siting its turbines.Ph.D