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 proposes a wind power virtual inertia control strategy based on the intelligent bee colony active disturbance rejection controller (ABC-ADRC). The proposed control method aims to improve the anti-interference capability of the virtual inertia control system and solve the challenge of tuning the parameters of the active disturbance rejection control (ADRC).The control strategy is developed based on the system frequency dynamic response equation. An active disturbance rejection controller is designed using a nonlinear feedback control law and an extended state observer. This controller aims to enhance the system's ability to reject disturbances. However, tuning the parameters of the ADRC can be difficult. To address this issue, an ABC algorithm based on nectar collection behavior is proposed to iteratively optimize the ADRC parameters. The proposed control method is verified through simulations using Matlab/Simulink. The results demonstrate that the ABC-ADRC control strategy is more effective compared to traditional algorithms. It successfully controls the rotor speed to adjust the frequency of the power grid system, achieves power sharing, and eliminates adaptive noise. Furthermore, this method reduces the complexity of parameter settings, improves anti-interference ability, and enhances the robustness of the system.