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arxiveess.SY2026-07-09

A graph theoretic view on small signal stability of inverter-based power grids

Iva Bačić, Jakob Niehues, Philipp C. Böttcher, Cai Dieball, Leonardo Rydin Gorjão, Andrea Benigni, Frank Hellmann, Dirk Witthaut

Dynamic grid stability is traditionally ensured with synchronous generators. Modern grids rely substantially more on inverter-based resources, which require grid-forming control to guarantee adequate system-wide synchronization and stability. Small-signal stability has granted various centralized and decentralized stability certificates - but these have primarily been limited to sufficient criteria only. In this work, we construct a necessary and sufficient small-signal stability criterion for lossless inverter-based power grids with arbitrary topology. We show that asymptotic stability is equivalent to the positive definiteness of a single matrix that combines network topology, operating point, and effective droop gains. We derive graph-theoretic stability criteria based on an augmented cone graph and show that the contribution of graph cycles is typically small, as illustrated for three IEEE test cases. The resulting framework yields decentralized stability criteria, quantifies the conservatism introduced by decentralization, and may support the development of future grid codes.

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arxiveess.SY2026-07-08

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arxiveess.SY2026-06-30

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arxiveess.SY2026-06-26

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arxiveess.SY2026-07-18

Cluster-Based Distributed Small-Signal Stability Certificates for Grid-Forming Inverter Networks

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Large-scale power networks are often organized by geography, ownership, or control authority, making stability certificates that require a fully assembled global model challenging. This paper develops a time-domain small-signal stability certification framework for grid-forming i…

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arxiveess.SY2026-07-07

Network Interdependency-Informed Power System Dynamic Trajectory Prediction Utilizing Black-Box Modeling of Multiple Inverter-Based Resources

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Black-box modeling of inverter-based resources (IBRs) has attracted growing interest for real-time grid operation and control in the presence of proprietary electronic control architectures. Existing machine learning (ML)-based online dynamic trajectory prediction approaches usin…

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arxiveess.SY2026-07-15

Transformer is All You Need: Attention-Based Anomaly Detection and Classification in Inverter-Rich Power Systems

Emad Abukhousa, Saman Zonouz, A. P. Sakis Meliopoulos

Inverter-based resources and IEC 61850 process-bus measurements introduce new protection challenges, including nontraditional fault behavior and measurement-domain cyber-physical attacks. This paper evaluates DL-Xformer, an attention-based Transformer classifier for multi-class f…

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