A Review of Resilience Assessment of Smart Grids via Wide-Area Measurement Systems: Intelligent Modeling, Electronics Integration, and Real-World Applications

Abstract

The increasing complexity and interconnectivity of modern power systems have elevated the importance of resilience assessment in smart grids, particularly under conditions of cyber-physical disturbances and large-scale uncertainties. Wide-Area Measurement Systems (WAMS), enabled by Phasor Measurement Units (PMUs), have emerged as a cornerstone technology for real-time monitoring, situational awareness, and resilience evaluation. This paper presents a comprehensive review of resilience assessment methodologies for smart grids leveraging WAMS, integrating perspectives from intelligent modeling, advanced electronics, and real-world deployment scenarios. The study explores the convergence of data-driven techniques, including machine learning and generative artificial intelligence, with traditional analytical frameworks. Additionally, it draws conceptual parallels with cryptographic systems and chaotic modeling for secure and adaptive grid operations. Key findings highlight the transition from static reliability metrics to dynamic resilience indicators, the role of AI in predictive analytics, and the challenges of integrating heterogeneous data sources. The contributions of this paper include a structured synthesis of recent advancements, identification of research gaps, and the proposal of future research directions focusing on secure, scalable, and intelligent grid infrastructures.