AI & ML
Stability Analysis in IBR-Dominated Grids: Model-Based and Data-Driven Methodologies
arXiv cs.SY0 views
arXiv:2610.22227v1 Announce Type: new Abstract: Stability issues in converter-dominated grids have a multifold nature, where static, small-signal and large-signal phenomena can influence each other. Capturing the interplay among these different stability aspects requires a rethinking of conventional modeling and analysis tools for power systems. As a further complication, Intellectual Property protection among manufacturers and system operators makes detailed converters and grid models unattainable. This motivates the use of data-driven approaches for stability analysis and control, nevertheless achieving an insightful representation of static, small-signal and large-signal phenomena from data still leaves many open questions. This paper discusses model-based and data-driven methodologies for stability analysis of converter-dominated grids. The instability mechanisms of static, small-signal and large-signal phenomena are conceptually explained, and the capability of different modeling and analysis tools to investigate them is examined. The effectiveness of data-driven methodologies to analyze instability phenomena in their multifold nature is debated, and the challenges on data completeness, model generalization under untrained conditions, physical interpretability, and uncertainty awareness are discussed.
Source:https://arxiv.org/abs/2610.22227PreviousRobust Multi-Agent Pursuit with Preemptive Communication via Reachability-Based Control Barrier FunctionsNextCo-designing a Layered Control Architecture
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