An Effective PQ-Decoupling Control Scheme Using Adaptive Dynamic Programming Approach to Reducing Oscillations of Virtual Synchronous Generators for Grid Connection With Different Impedance Types

The power coupling of the virtual synchronous generator (VSG) in the grid-connected mode may aggravate power oscillation because of a resistance-inductive line. In order to deal with this issue, this research study proposes an adaptive and optimal approach to controlling VSG via reinforcement learning and adaptive dynamic programming (ADP). It derives the linear and nonlinear hybrid equations of the VSG power considering the case where the line impedance is uncertain. The nonlinear part is a disturbance, and the linear ADP solves the optimal feedback control and compensation controller, eliminating the interaction between the active power and reactive power. Also, the proposed method utilizes value iteration and is data-driven. Thus, it does not rely on an initial stability control gain and an accurate dynamic model during the learning process. Comparative experiments reveal the effectiveness of the proposed method and validate the practicability of the methodology introduced; in addition, comparative simulations present the superiority of the proposed method in power systems based on synchronous generators.