This paper presents a data-driven virtual inertia control method for doubly fed induction generator (DFIG)-based wind turbine to provide inertia support in the presence of frequency events. The Markov parameters of the system are first obtained by monitoring the grid frequency and system operation state. Then, a data-driven state observer is developed to evaluate the state vector of the optimal controller. Furthermore, the optimal controller of the inertia emulation system is developed through the closed solution of the differential Riccati equation. Moreover, a differential Riccati equation with self-correction capability is developed to enhance the anti-noise ability to reject noise interference in frequency measurement process. Finally, the simulation verification was performed in Matlab/Simulink to validate the effectiveness of the proposed control strategy. Simulation results showed that the proposed virtual inertia controller can adaptively tune control parameters online to provide transient inertia supports for the power grid by releasing the kinetic energy, so as to improve the robustness and anti-interference ability of the control system of the wind power system.

This paper presents an advanced virtual inertia control strategy for wind farms to provide transient power support in the presence of frequency events, where a fuzzy active disturbance rejection controller is developed to enable the operation of an energy storage system (ESS) so as to provide support for frequency regulation of the power grid. To effectively estimate the system frequency under uncertain noises, fuzzy rules are presented to adaptively tune the parameters of the extended state observer and to realize the power-sharing, to improve the anti-interference ability of the wind power system. Finally, simulation analysis in MATLAB/Simulink is provided to validate the effectiveness of the proposed control strategy. Simulation results show that the developed virtual inertia control strategy based on fuzzy active disturbance rejection control has a good inertia support capability. In addition, the proposed method is able to improve the anti-noise capability of the wind power system.