Enhancing Multimicrogrid Resilience: A State-of-the-Art Survey on Model Predictive Control-Based Energy Management Strategies

The growing frequency of extreme natural and human-induced events underscores the critical need to enhance the resilience of power systems. Multimicro grids (MMGs), integrating distributed energy resources (DERs), such as renewable generation and energy storage systems (ESSs), offer a promising solution by enabling power exchange both among interconnected microgrids (MGs) and with the main grid. This survey presents a comprehensive review of the application of model predictive control (MPC) for energy management in MMG systems, emphasizing its potential to improve system resilience under high-impact events. The paper proposes a structured taxonomy of existing MMG energy management strategies, categorized into three principal groups: (i) economic-based strategies, (ii) optimal energy management, and (iii) operational recovery strategies. Each category has unique goals, implementation methods, and timescales, which require separate examinations. Key research gaps are identified, including the coordination of normal and resilient operations, the development and quantification of resilience metrics, and the integration of real-time data to enhance MPC performance in MMGs. In addition, this paper provides a foundational understanding of resilience in power systems by defining core concepts, presenting evaluation methods, and examining the roles of MMGs and MPC in enhancing system resilience. These insights form a comprehensive framework for understanding the challenges and opportunities in this evolving field. Finally, the paper outlines future research directions, emphasizing the potential of MPC for scalable, real-time control in modern power systems, thereby supporting the development of a more adaptive and resilient energy infrastructure.