With the increasing size and scale of wind turbines, the ripple caused by wind shear may have negative effects on wind turbines, such as decreasing grid-connected power quality and increasing mechanical loss. To address this issue, a virtual dual-ripple suppression strategy is proposed to suppress the ripple caused by wind shear without additional cost and sacrificing system efficiency. First, in this paper, a three-bladed double-fed wind turbine is taken as the research object with the analysis of its transmission mechanism and form of ripple. Second, an online artificial neural network (ANN) ripple detection method is proposed to detect the time-varying low-frequency ripple with high accuracy. In addition, a virtual dual-ripple suppression strategy composed of two ANN-based filters is utilized to suppress electromagnetic torque ripple and grid-connected power ripple simultaneously. Finally, the accuracy of the presented ANN ripple detection method and suppression strategy are verified by matlab simulation. The results show that the virtual dual-ripple suppression strategy can effectively suppress the transmission of ripple while increasing the conversion efficiency of wind energy without additional hardware circuits and equipment.