Data-Driven Virtual Inertia Control Method of Doubly Fed Wind Turbine

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