Improving the small-signal stability of a stochastic power system

Algorithms and mathematical analysis

Journal Article (2025)
Author(s)

Zhen Wang (Shandong University)

Kaihua Xi (Shandong University)

Aijie Cheng (Shandong University)

Hai Xiang Lin (TU Delft - Mathematical Physics, Universiteit Leiden)

J.H. van Schuppen (TU Delft - Mathematical Physics)

Research Group
Mathematical Physics
DOI related publication
https://doi.org/10.1016/j.chaos.2025.116616
More Info
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Publication Year
2025
Language
English
Research Group
Mathematical Physics
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.@en
Volume number
199
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Abstract

Tools and analysis for improving the small-signal stability of a stochastic power system by optimal power dispatch in each short time horizon, such as five-minute intervals, are provided in this paper. An objective function which characterizes the maximal exit probability from the static stability region (−π/2,π/2) across the phase-angle differences of all power lines is formulated. This objective function is proven to be Lipschitz continuous, nondifferentiable, and nonconvex, with a finite minimum defined over the region of power supply vectors. The formulas of the generalized subgradient and directional derivative of the objective function are provided, and based on these formulas, a two-step algorithm is designed to approximate a minimizer accompanied by the convergence proof: (1) using a projected generalized subgradient method to compute an effective initial vector, and (2) applying the steepest descent method to approximate a local minimizer. The algorithms have been verified using a synthesized power network, demonstrating computational validity and effectiveness in minimizing the maximal exit probability of all power lines.

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