Optimal Scheduling of Extreme Operating Conditions in Islanded Microgrid Based on Model Predictive Control

Abstract

To address the optimal scheduling of islanded microgrids under extreme operating conditions, this paper proposes a demand response (DR) economic optimization scheduling strategy based on model predictive control (MPC). The strategy improves the utilization of photovoltaic (PV) and energy storage systems while ensuring stable power supply to critical loads through a dynamic load shedding approach based on load priority and power system constraints. By incorporating time-of-use electricity pricing and load importance assessment, an innovative demand response incentive policy is designed to optimize consumer behavior and reduce grid load pressure. Experimental results demonstrate that the DR-MPC-based method reduces operating costs and increases renewable energy utilization compared to traditional methods. This approach is broadly applicable to pre-emptive load shedding and energy storage optimization in islanded microgrids during emergencies and is expected to be extended to the optimal scheduling of microgrid clusters in the future.