Transient Synchronization Stability in Grid-Following Converters: Mechanistic Insights and Technological Prospects—A Review

This paper investigates the transient synchronization stability mechanisms and technological advancements associated with grid-following (GFL) converters, providing a systematic review of the current research landscape and future directions in this field. The current literature lacks a comprehensive understanding of how outer-loop control dynamics and grid-converter interactions critically influence transient stability mechanisms. This oversight often leads to incomplete or overly simplistic stability assessments, particularly under high penetration of renewable energy sources. Furthermore, existing stability criteria and analytical methodologies do not adequately address the compounded challenges arising from multi-control-loop coupling effects and systems with multiple parallel converters. These limitations underscore the inability of conventional methodologies to holistically model the transient synchronization behavior of GFL converters in modern power-electronics-dominated grids. To address these gaps, this work synthesizes a comprehensive review of modeling frameworks, analytical methodologies, transient stability mechanisms, and influence factors specific to GFL converters. First, based on the fundamental differences between synchronous generators and GFL, this paper summarizes the second-order equivalent model derived from phase-locked loop (PLL) dynamic. It conducts a comparative analysis of the applicability and limitations of conventional stability assessment methods, such as the equal-area criterion, phase portrait method, and Lyapunov functions, within power-electronics-dominated systems. It highlights potential mechanistic misinterpretations arising from neglecting outer-loop control and grid interactions. Second, the paper delineates the principal challenges inherent in the transient synchronization stability analysis of GFL converters. These challenges encompass the dynamic influences of multi-control-loop coupling effects and the imperative for advancing stability criterion research in systems with multiple parallel converters. Building on existing studies, the paper further explores innovative applications of artificial intelligence (AI) in transient stability assessment, including stability prediction based on deep learning, data-physics hybrid modeling, and human–machine collaborative optimization strategies. It emphasizes that enhancing model interpretability and dynamic generalization capabilities will be critical future directions. Finally, by addressing these gaps, this work provides theoretical foundations and technical references for transient synchronization stability analysis and control in high-penetration inverter-based resources (IBRs) grids.