Cyber-physical security for microgrids through Digital Twin technologies: A review and research outlook

Digital Twins (DTs) are emerging as a transformative approach for enhancing the monitoring, control, and resilience in Cyber-Physical systems (CPSs), particularly in the context of microgrids (MGs). Due to their complexity and inter-connectivity, MGs are increasingly vulnerable to a range of cyber-attacks that can compromise system stability, reliability, and safety. This paper presents an overview of Microgrid Digital Twins (MGDTs) with a special focus on their security applications, including modeling and communication protocols. The study outlines key aspects of MGDT development and provides a classification of existing approaches based on their primary security functions. The integration of Artificial Intelligence (AI) is also examined in order to enhance detection and response capabilities. The findings highlight substantial opportunities for future research toward the development of intelligent, resilient, and secure MGDT frameworks to support the evolving needs for smart energy systems. • Security-focused Microgrid Digital Twin (MGDT) frameworks are reviewed. • Key facets of MGDT development are described. • MGDTs are classified by resilience, assessment, detection, and mitigation roles. • Early use of AI in MGDTs for automated security capabilities is explored. • Gaps in MGDT research for security are identified.