Initializing idealized Large-Eddy Simulations (LES) for wind energy applications presents a persistent control problem, typically characterized by slow convergence due to inertial oscillations and the difficulty of matching target height wind targets. To address this, we present Dynamic Geostrophic Nudging (DGN), a method that couples physical fidelity with computational efficiency. Unlike standard velocity nudging, DGN acts on the forcing terms: it dynamically adjusts the geostrophic wind components based on the flow tendency and the error between the mean velocity and the target value. This mechanism allows the controller to efficiently steer the mean wind toward the target while actively damping inertial oscillations in the boundary layer. We employ a one-dimensional model to perform a parameter sweep and investigate the sensitivity of the control parameters before applying the method to a full three-dimensional LES. The results demonstrate that DGN reduces the spin-up time from the standard 12–24 hours to approximately two hours while maintaining the target wind vector with high accuracy. Furthermore, by arresting the unphysical transient growth of the boundary layer, the method allows for the use of vertically optimized domains, representing a significant advancement in the operational efficiency of precursor generation for wind farm simulations.