A Novel Distributed Iterative Learning Secondary Control for AC Microgrids

This paper proposes a novel distributed iterative learning control strategy for regulation of AC microgrids with external disturbances. By introducing the recursive control part into the conventional consensus algorithm for microgrid control, the designed controller acquires the capability to compensate disturbances and continuously improve the control performance by exploiting previous errors like the convectional iterative learning control approach. Furthermore, the corresponding stability criterion of the proposed secondary control strategy is derived by using the direct Lyapunov method in both iteration and time domains. Finally, simulation results of the microgrid test system demonstrate the effectiveness and robustness of the proposed control strategy.