Abstract
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.
Highlights
The increasing penetration of wind power generation into the power system is becoming an important trend [1,2]
The doubly fed induction generator (DFIG)-based wind turbine is decoupled from power grid by back-to-back power converter, so that there exists no inherent response from wind turbine in the presence of grid frequency event [3,4]
In [9], the authors provide the calculation method of the equivalent virtual inertia time constant reflecting the effective energy storage of the DFIG and put forward the variable parameter virtual inertia emulation method based on DFIG effective energy storage, so as to improve the ability of DFIG to participate in system frequency regulation
Summary
The increasing penetration of wind power generation into the power system is becoming an important trend [1,2]. In [13], the relationship among virtual inertia, rotor speed, and grid frequency change are analyzed, and a new virtual inertia emulation method is developed, where the MPPT curve can be switched to virtual inertia control curve according to frequency deviation so as to release kinetic energy and provide inertia support for the power grid This method tends to increase the computational burdens of the control system. In [15], an approximate dynamic programming method is proposed for online parameters tuning of traditional PD virtual inertia controller, where the knowledge of system model is not necessary This method can realize the online optimal parameter tuning, which enhances the control performance of DFIG for frequency regulation, these data-driven inertia control methods may address effectively transient frequency fluctuation.
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