Accurate and effective prediction of wind turbine wakes and their interferences with surrounding atmospheric environment in the wind farm is critical for optimizing the layout design of the wind farm, which can maximize wind energy production and minimize fatigue loads for turbines. The purpose of this paper is to develop a lattice Boltzmann method (LBM)-based computational framework with the actuator disk model with rotation (ADMR) for wind turbine aerodynamics. Such a framework aims at achieving reasonable accuracy and affordable computational effort while being able to investigate the characteristics of wind turbine wakes and interferences within a large-scale wind farm. The LBM–ADMR framework was first validated using three benchmark cases, including a single-turbine model wind tunnel experiment (BT1), two in-line placed turbine models wind tunnel experiment (BT2), and a full-size wind turbine of National Renewable Energy Laboratory (NREL) 5 MW. Results from wind tunnel model experiments demonstrate that the established LBM–ADMR computational framework exhibits high simulation accuracy in the far-wake region, while low accuracy is observed in the near wake due to the simplification for the rotor model. Based on the studies of the NREL 5 MW reference wind turbine, it is found that the LBM–ADMR achieves higher simulation accuracy at lower tip–speed ratios (TSR), while higher TSR can lead to flow instability at the rotor location, resulting in low simulation accuracy. Subsequently, the LBM–ADMR is applied to investigate wake effects and wake interference in a 3 × 4 wind farm. The study findings indicate that wake effects significantly reduce the power output of rear-row turbines in the wind farm, particularly for the second-row turbines fully immersed in the wake of the first-row turbines, with output power decreasing to the 22.49% of rated power, consistent with BT2 wind tunnel experimental conclusions. However, wake interference can substantially accelerate wake recovery with a notable increase in the averaged inflow velocity for rear-row turbines, and significantly enhance output power with the fourth-row turbines rising to approximately 60% of rated power. Nevertheless, wake interference also leads to a significant increase in inflow turbulence intensity, exacerbating fluctuations of power and structural vibration of wind turbines, imposing considerable pressure on wind farm grid integration and daily maintenance.
Zhuang et al. (Fri,) studied this question.