Wind turbines within a wind farm are highly coupled through wake effects, presenting significant potential for improving overall wind energy utilization through wake distribution optimization. Considering the combined impact of active yaw control and axial induction control on inter-turbine wakes, as well as differences in their regulation cycles and response times, we propose a nested optimization method integrating both controls. Combined with an initial solution localization strategy, this approach enhances wind farm power generation while significantly reducing optimization time. Wake distribution modeling incorporates dual-parameter Weibull-distributed inflow and a 3D Gaussian wake model to improve accuracy and reflect the effects of turbine yaw and vertical height variations on wake estimation. Finally, simulation studies conducted for an offshore wind farm in Southeast China’s sea area demonstrate that the proposed nested optimization strategy achieves better overall power enhancement.