Explicit formulas for the asymptotic variance of a linearized model of a Gaussian disturbance driven power system with a uniform damping-inertia ratio

Xian Wu, Kaihua Xi*, Aijie Cheng, Hai Xiang Lin, Jan H. van Schuppen, Chenghui Zhang

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

Serious fluctuations caused by disturbances may lead to instability of power systems. With the disturbance modeled by a Brownian motion process, the fluctuations are often described by the asymptotic variance at the invariant probability distribution of an associated Gaussian stochastic process. Here, we derive the explicit formula of the variance matrix for the system with a uniform damping-inertia ratio at all the nodes, which enables us to analyze the influences of the system parameters on the fluctuations and investigate the fluctuation propagation in the network. With application to systems with complete graphs and star graphs, it is found that the variance of the frequency at the disturbed node is significantly bigger than those at all the other nodes. It is also shown that adding new nodes may prevent the propagation of fluctuations from the disturbed node to all the others. Finally, it is proven theoretically that larger line capacities accelerate the propagation of the frequency fluctuation and larger inertia of synchronous machines help suppress the fluctuations of the phase differences, however, these acceleration and suppression are quite limited.

Original languageEnglish
Article number115511
Number of pages13
JournalChaos, Solitons and Fractals
Volume188
DOIs
Publication statusPublished - 2024

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • Fluctuation propagation
  • Invariant probability distribution
  • Lyapunov equation
  • Power systems
  • Stochastic Gaussian system
  • Synchronization stability

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