A novel dynamic wake model for prediction of wind speed and power production considering wake propagation velocity and deflection

In this study, a novel dynamic wake model is proposed to predict real-time wind speed and power production by incorporating a new wake propagation velocity model and a new wake deflection model and is validated by numerical simulations and wind tunnel tests. Firstly, the unsteady Reynolds-Averaging Navier-Stokes (URANS) model is used to evaluate the dynamic wake model and validated by phase-averaged LES results. The wake propagation velocity model is proposed based on the results of URANS simulations considering various operational and inflow conditions. It is found that the propagation velocity of the wind turbine wake is smaller than half of the ambient wind speed in the near wake region and asymptotically approaches approximately 0.65 times the ambient wind speed in the far wake region. The new wake deflection model for a yawed wind turbine is then derived from the momentum conservation equation and the double-Gaussian wake model and is validated by experimental results and numerical simulations. The new wake deflection model shows a significant improvement in prediction accuracy of wind speed and power production in both near and far wake regions. Finally, the proposed wake deflection and propagation velocity models are incorporated into the dynamic wake model and validated by numerical simulations with time-varying yaw angle and wind speed. The normalized root mean square error (NRMSE) of power production of downstream wind turbine at x=7D predicted by the proposed dynamic wake model is reduced from 15.05 % to 1.89 % for the simulation of time-varying yaw angle and from 16.30 % to 7.35 % for the simulation of time-varying wind speed compared to that using the conventional dynamic wake models.