At the moment of electric locomotive passing the neutral-section, the voltage and current of traction network may have low-frequency oscillation (LFO), which will seriously affect the safe operation of the railway. Aiming at eliminating LFO, a modeling method of vehicle-grid coupling system based on flux-current theory is presented in this paper. In the model of electric locomotive, the transient current control strategy and magnetic saturation of on-board transformer are considered, and the equivalent model of excitation inductance of on-board transformer is established based on the flux-current theory. Using this model, based on the Middlebrook impedance ratio criterion, the stability region of vehicle-grid coupling system is analyzed under the influence of average saturation of on-board transformer and control parameters of electric locomotive. Simulation results and analysis are established to evaluate and verify the proposed modeling method of LFO. This work has the benefits of defining the opening and closing phase angle region of system stability as well as providing guidance to adaptively modify the control parameters to suppress the LFO.

With the increasing size and scale of wind turbines, the ripple caused by wind shear may have negative effects for 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. Firstly, 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. Secondly, 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 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 circuit and equipment.