On Information Transfer Based Characterization of Power System Stability
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Abstract (arXiv)
In this paper, we present a novel approach to identify the generators and states responsible for the small-signal stability of power networks. To this end, the newly developed notion of information transfer between the states of a dynamical system is used. In particular, using the concept of information transfer, which characterizes influence between the various states and a linear combination of states of a dynamical system, we identify the generators and states which are responsible for causing instability of the power network. While characterizing influence from state to state, information transfer can also describe influence from state to modes thereby generalizing the well-known notion of participation factor while at the same time overcoming some of the limitations of the participation factor. The developed framework is applied to study the three bus system identifying various cause of instabilities in the system. The simulation study is extended to IEEE 39 bus system.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Sep 2018.
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Citing papers per year: 2021: 1; 2022: 2.
3 papers.
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- 2022Online Real-time Learning of Dynamical Systems from Noisy Streaming Data: A Koopman Operator Approach10 Dec 2022
- 2022Data-driven Influence Based Clustering of Dynamical Systems5 Apr 2022
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