Towards real-time optimal control of wind farms using large-eddy simulations

Abstract

Large-eddy simulations (LESs) are commonly considered too slow to serve as a practical wind farm control model. Using coarser grid resolutions, this study examines the feasibility of LES for real-time, receding-horizon control to optimize the overall energy extraction in wind farms. By varying the receding-horizon parameters (i.e. the optimization horizon and control update time) and spatiotemporal resolution of the LES control models, we investigate the trade-off between computational speed and controller performance. The methodology is validated on the TotalControl Reference Wind Power Plant using a fine-grid LES model as a wind farm emulator. Analysis of the resulting power gains reveals that the performance of the controllers is primarily determined by the receding-horizon parameters, whereas the grid resolution has minor impact on the overall power extraction. By leveraging these insights, we achieve near-parity between our LES-based controller and real-time computational speed, while still maintaining competitive power gains up to 40 %.