Adaptive inertia and damping of grid‐connected inverter with improved VSG control

Abstract

AbstractThe control technology of virtual synchronization generator (VSG) based on energy storage system is proposed to compensate for the inertia and damping loss caused by the grid connection of distributed generators. However, with the addition of virtual inertia and damping, VSG is prone to generate frequency and power oscillation, and the regulating ability is weakened. For the above problems, this paper analyzes the inertia and damping characteristics of the synchronous motor in the rotation of synchronous motors, and applies artificial neural network control to VSG. In intelligent control strategy, a multi‐input‐output radial basis function (RBF) neural network is first proposed to adaptively adjust virtual inertia and damping. Finally, an experimental platform with a rated power of 1 kW and a variable load of 1 kW was built to validate the proposed control strategy. The experimental results show that the artificial neural network control strategy has a better regulation ability.