Improved Design of Finite-Set Sliding Mode Predictive Control for AC Microgrids With Multiple Distributed Generators

Abstract

Microgrids offer a reliable way to integrate renewable energy sources into the main power grid. Connecting distributed generators (DGs) to the grid requires robust control strategies to manage power flow without disruption. This study presents a novel finite-set sliding mode predictive control (FS-SMPC) framework that supports microgrid operation in both grid-connected and islanded modes. Each DG operates with its own FS-SMPC and inverse droop controller, enabling decentralized control. The control goals change based on the current mode. In grid-connected operation, each DG regulates its power output, while voltage and frequency are maintained by the main grid. In islanded mode, the FS-SMPC takes over to stabilize voltage and frequency within the microgrid. The proposed FS-SMPC design is validated using MATLAB/Simulink® simulations. Its performance is further confirmed through a real-time Hardware-in-the-Loop (HiL) test setup, using the OPAL-RT OP5600 digital simulator. Results show effective power tracking and dynamic load management.