Stochastic dynamic stability assessment with high penetration of uncertain sources: Uncertainty modeling, solutions and applications

The growing penetration of inverter-based resources (IBRs) in modern power systems has introduced new challenges for dynamic stability assessment due to increased uncertainty and reduced system inertia. Traditional deterministic methods often fall short in capturing the stochastic nature of renewable generation and load fluctuations. In this context, stochastic dynamic security assessment (SDSA) has emerged as a vital framework for quantifying stability risks under uncertainty. This paper presents a comprehensive review of SDSA methods, categorizing them into Type I and Type II based on the treatment of stochastic inputs. Key components such as stochastic modeling and solution techniques are systematically analyzed. In addition, representative application scenarios are discussed, including parametric design and stochastic security-constrained optimization. Finally, this paper highlights several critical challenges and outlines future research directions aimed at enhancing the efficiency, adaptability, and real-world applicability of SDSA in supporting secure and resilient power system operations and control.