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- W4382118601 abstract "This chapter introduces a novel framework to construct the region of attraction (ROA) of a power system centered around a stable equilibrium by using stable state trajectories of system dynamics. Most existing works on estimating ROA rely on analytical Lyapunov functions, which are subject to two limitations: the analytic Lyapunov functions may not be always readily available, and the resulting ROA may be overly conservative. This work overcomes these two limitations by leveraging the converse Lyapunov theorem in control theory to eliminate the need for an analytic Lyapunov function and learning the unknown Lyapunov function with the Gaussian Process (GP) approach. In addition, a Gaussian Process Upper Confidence Bound (GP-UCB) based sampling algorithm is designed to reconcile the trade-off between the exploitation for enlarging the ROA and the exploration for reducing the uncertainty of sampling region. Within the constructed ROA, it is guaranteed in the probability that the system state will converge to the stable equilibrium with a confidence level. Numerical simulations are also conducted to validate the assessment approach for the ROA of the single-machine infinite bus system and the New England 39-bus system. Numerical results demonstrate that our approach can significantly enlarge the estimated ROA compared to that of the analytic Lyapunov counterpart." @default.
- W4382118601 created "2023-06-27" @default.
- W4382118601 creator A5043288516 @default.
- W4382118601 date "2023-01-01" @default.
- W4382118601 modified "2023-09-24" @default.
- W4382118601 title "Security Monitoring Using Converse Lyapunov Function" @default.
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- W4382118601 doi "https://doi.org/10.1007/978-981-99-3053-1_4" @default.
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