It is crucial to maximize the power output of wind farms to enhance the efficiency of utilizing wind energy. Turbine operational parameters have a significant impact on this. Nine Taguchi experiments are conducted, with each parameter having three levels: downstream spacing (3D, 5D, and 7D), yaw angle (10°, 20°, and 30°), and hub height difference (−0.2D, 0D, and 0.2D), where D is the turbine diameter. The total power output (Ptotal) under different combinations is measured. Range analysis and analysis of variance (ANOVA) are employed to rank the sensitivities of the parameters and identify the optimal configuration. Additionally, the velocity contour visualization helps reveal the underlying wake mechanisms that affect variations in power output. The results obtained show that downstream spacing (L) has the most significant influence on power output, accounting for 77.8% of the variance in the ANOVA. The yaw angle (β) follows, with a contribution of 16.0%, and then the hub height difference (Δh) with a contribution of 5.9%. Thus, the order of parameter importance is determined as L β Δh. The optimal parameter configuration is found to be L = 7D and β = 10°, which has been proven to result in a relatively high total power output. The velocity contour analysis verifies that this configuration reduces wake interference, optimizes redirection, and separates the wake from the downstream turbine's rotor plane, thereby enhancing performance. These findings provide valuable guidance for optimizing wind farm layout, emphasizing L as the primary control parameter, and suggest that adjustments to β and Δh can enhance the wake management and the energy capture efficiency.
Mi et al. (Thu,) studied this question.