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Angle Stability Analysis of Power System With Multiple Operating Conditions Considering Cascading Failure

A method to analyze the angle stability of power system with multiple operating conditions considering cascading failure is proposed in this paper. First, considering stochastic events such as uncertain operation of protection/breaker and system hardware failure, the system operating condition set i...

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Bibliographic Details
Published in:IEEE transactions on power systems 2017-03, Vol.32 (2), p.873-882
Main Authors: Jing Ma, Shangxing Wang, Yang Qiu, Yinan Li, Zengping Wang, Thorp, James S.
Format: Article
Language:English
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Summary:A method to analyze the angle stability of power system with multiple operating conditions considering cascading failure is proposed in this paper. First, considering stochastic events such as uncertain operation of protection/breaker and system hardware failure, the system operating condition set is determined based on the flow transfer theory and the matrix of transfer probability between different operating conditions is calculated. On this basis, the discrete Markov power system model with multiple operating conditions considering cascading failure is established. And then, construct the Lyapunov functional containing the Markov model, and derive the robust stochastic stability criterion which satisfies the disturbance attenuation degree γ by iteration and the angle stability of power system could be identified according to the criterion using linear matrix inequality tools. Finally, stability index μ is defined to establish the relationship between transfer probability and system stability. Time-domain simulation tests on the IEEE 16-machine 68-bus system verify that, the proposed method could identify the stability of power system with multiple operating conditions effectively, with no need to obtain the operating trajectory of the system. Compared with traditional time-domain simulation method, the computation amount is reduced. Besides, it is simple and easy to implement.
ISSN:0885-8950
1558-0679
DOI:10.1109/TPWRS.2016.2566672