抄録
With the increasing frequency of extreme natural disasters, equipment failures, and malicious attacks, the vulnerability of power systems has become increasingly prominent, making system restoration capability and operational resilience critical topics for ensuring energy security and enhancing system robustness. This paper provides a comprehensive review of recent research progress in power system restoration and resilience analysis, focusing on the evolution of key technical approaches and methodologies, and examining their interdisciplinary integration under the trend of intelligent power systems. First, the paper clarifies the fundamental concepts of resilience and restoration in power systems, analyzes mainstream quantitative indicators, assessment frameworks, and modeling methods, and distinguishes their intrinsic connections and essential differences from traditional performance metrics such as stability, reliability, and risk assessment. It then systematically summarizes current research achievements from perspectives such as restoration optimization scheduling, self-healing control strategies, and resilient network topology design, with particular emphasis on the critical roles of distributed energy resources, microgrid architectures, and multi-agent cooperative control technologies in enhancing power system resilience. Furthermore, the paper explores the frontier applications of emerging technologies—including artificial intelligence, digital twins, and power-communication coordinated defense—in building intelligent resilient grids, and identifies major challenges such as the high complexity of system modeling, the incompleteness of operational data, and the lack of standardized evaluation methods and frameworks. Finally, it outlines future research directions, advocating for the development of dynamic adaptive restoration mechanisms. This paper aims to provide systematic insights for resilience research and engineering practice in power systems, promoting the development of next-generation secure, adaptive, and intelligent power grids.
