Data-Driven Distributed Stability Certification for Power Systems via Input-State Trajectories
Abstract
This article proposes a data-driven framework to verify the distributed conditions that guarantee the system-wide stability for interconnected power systems. To guarantee system wide stability, the dynamics of each bus are required to satisfy an output differential passivity (ODP) condition with a sufficient index. These ODP indices uniformly quantify the impacts on the system-wide stability of individual bus dynamics and the coupling strength from the power network. To obtain these indices without explicit physical models, we derive a data-driven linear matrix inequality (LMI) criterion based exclusively on measured input-state trajectories. Furthermore, extracting the optimal ODP index is formulated as a convex semi-definite programming (SDP) problem. Simulations verify the effectiveness of the proposed method under both single-device offline evaluation and system-wide online certification scenarios.
Cite
@article{arxiv.2604.16212,
title = {Data-Driven Distributed Stability Certification for Power Systems via Input-State Trajectories},
author = {Xiaohui Zhang and Liaoyuan Yang and Peng Yang},
journal= {arXiv preprint arXiv:2604.16212},
year = {2026}
}
Comments
6 pages, 2 figures. Submitted to ASCC 2026