Finite‐time H∞${{H}_\infty }$ fault detection for large‐scale power system via Markov jumping mechanism

Abstract This paper investigates the finite‐time fault detection problem for large‐scale power systems via the Markov jumping mechanism subject to unknown disturbances. The novel power system is described by a large‐scale system model, and the residual dynamic properties of unknown input signals and fault signals, including unknown disturbances and modelling errors, are obtained by reconstructing the system. Then, the energy norm indicators of the residual disturbance signal and fault signal are, respectively, selected to reflect their suppression effect on disturbance and sensitivity to faults. Moreover, the design of a fault detection observer is formulated as an optimisation problem. Based on Lyapunov theory and linear matrix inequalities (LMI), sufficient conditions for the designed fault detection observer solutions are given, and an optimisation design method is provided. Finally, the simulation results show that the optimised observer can detect the fault signal effectively and can contain the effect of unknown disturbances on the residuals within a given range when a fault occurs.

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Publication Details

Journal
IET Control Theory and Applications
Published
2024-09-05
DOI
https://doi.org/10.1049/cth2.12732
Citations
3
Primary Topic
Islanding Detection in Power Systems
Type
article
Field-Weighted Citation Impact
0.63

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article

Finite‐time H∞${{H}_\infty }$ fault detection for large‐scale power system via Markov jumping mechanism

Chengcheng Ren, Xunting Wang, Jinjin Ding, Qian Zhang et al.
3 citations
IET Control Theory and Applications
Islanding Detection in Power Systems
0.63
article

Finite‐time H∞${{H}_\infty }$ fault detection for large‐scale power system via Markov jumping mechanism

Chengcheng Ren, Xunting Wang, Jinjin Ding, Qian Zhang, Bin Xu
article en
3 citations

Abstract

Abstract This paper investigates the finite‐time fault detection problem for large‐scale power systems via the Markov jumping mechanism subject to unknown disturbances. The novel power system is described by a large‐scale system model, and the residual dynamic properties of unknown input signals and fault signals, including unknown disturbances and modelling errors, are obtained by reconstructing the system. Then, the energy norm indicators of the residual disturbance signal and fault signal are, respectively, selected to reflect their suppression effect on disturbance and sensitivity to faults. Moreover, the design of a fault detection observer is formulated as an optimisation problem. Based on Lyapunov theory and linear matrix inequalities (LMI), sufficient conditions for the designed fault detection observer solutions are given, and an optimisation design method is provided. Finally, the simulation results show that the optimised observer can detect the fault signal effectively and can contain the effect of unknown disturbances on the residuals within a given range when a fault occurs.

IET Control Theory and ApplicationsVol. 18(18)
Anhui University (CN), State Grid Corporation of China (China) (CN)
China Postdoctoral Science Foundation
Openalex Percentile: Top 32%
Islanding Detection in Power Systems
0.63
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