A resilience driven robust predictive control for optimal microgrid scheduling.

This paper presents a novel approach to enhance microgrid resilience through the application of robust Model Predictive Control (RMPC). The primary objective is to minimize overall cost during prolonged main grid outages by optimizing resource allocation. The proposed methodology encompasses two essential phases: grid connected operation and resilient operation. In the former, optimal unit commitments, energy storage schedules, and adjustable loads are determined to inform the subsequent resilient operation phase. During resilient operation, the microgrid's capacity to fulfill local load demands amidst main grid disruptions is evaluated. A crucial element of this approach is the mitigation of uncertainties through robust optimization techniques, thereby guaranteeing the solution's resilience in the face of variations in load, non-dispatchable generation, and the timing of main grid interruptions. The resulting refined solution strikes a delicate equilibrium between economic efficiency and resilience, thereby facilitating seamless islanding with minimal disruptions. Through numerical simulations conducted within a test microgrid, this approach's effectiveness is validated, highlighting its potential to bolster microgrid resilience by strategically optimizing resource allocation, particularly in critical scenarios. [ABSTRACT FROM AUTHOR]