基于人工智能的电力电子变流器并网系统稳定性分析与控制研究综述OA

With the increasing penetration of renewable energy sources such as wind and solar power in AC power grids,power electronic converters have become key devices affecting the safe and stable operation of the system.The grid-connected control performance is critical to power quality,system stability,and efficient integration of renewables.In recent years,artificial intelligence(AI)algorithms have demonstrated significant potential in stability analysis and control of power electronic systems,owing to their superiorities in feature extraction,self-learning,and nonlinear modeling.This paper first reviews the instability mechanisms and control theories of converter-based grid-connected systems and summarizes the limitations of existing methods in modeling accuracy,stability analysis,and control performance.It then systematically reviews recent advances in AI-based small-signal modeling,stability analysis,and high-performance control of converter systems,as well as AI applications in large-signal transient modeling and control.Finally,future research directions are discussed,highlighting the role of AI in enhancing stability control for next-generation power systems.