Analysis of wind turbine power and aerodynamic loads under the influence of four-dimensional spatiotemporal non-uniform wake

The aerodynamic characteristics of wind turbines operating in the wake region exhibit significant differences compared to those in free-flow conditions. In order to quantify the influence of wake on the aerodynamic characteristics of wind turbines, this paper proposes a method for calculating the aerodynamic characteristics of wind turbines based on a three-dimensional time-varying wake model (3DJGF-T) with a coupling-improved blade element momentum (BEM) model. Firstly, using sinusoidal and free-stream wind conditions as upstream turbine inputs, the 3DJGF-T wake model is employed to obtain the spatiotemporal characteristics of the wind field within the wake, and the external field experiments are conducted for validation. Secondly, utilizing the unevenly distributed flow field within the wake as the boundary condition in terms of spatial location points and time, the spatiotemporal variations of wind turbine rotor and single-blade power, torque, and axial force are investigated at different downstream longitudinal positions (X=5D, X=6D, X=7D, X=8D) and horizontal positions (full wake, 1/2 wake, 3/4 wake, and full-half wake) with the comparative analyses are performed. Results indicate that the rotor power increases by approximately 10% with a longitudinal distance increase of 1D. However, changes in the downstream longitudinal position will simultaneously alter the temporal and spatial characteristics of the wake. The time when the wake reaches the downstream wind turbine changes, which also leads to changes in the position of the wind turbine blades in the non-uniform flow field, resulting in more complex fluctuations in load and power. Changes in the horizontal position only affect the spatial characteristics of the wake. The power loss of the wind turbine gradually increases as it approaches the center of the wake. The relative average power losses of 1/2 wake, 3/4 wake, and full wake are 23.7%, 44.3%, and 61.2%, respectively. The findings of this study provide important reference value for wake regulation and micro-siting in wind farms.