scholarly journals Machine Learning Based on Bayes Networks to Predict the Cascading Failure Propagation

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 44815-44823 ◽  
Author(s):  
Renjian Pi ◽  
Ye Cai ◽  
Yong Li ◽  
Yijia Cao
2008 ◽  
Vol 372 (36) ◽  
pp. 5778-5782 ◽  
Author(s):  
Z.J. Bao ◽  
Y.J. Cao ◽  
L.J. Ding ◽  
Z.X. Han ◽  
G.Z. Wang

2005 ◽  
Vol 19 (4) ◽  
pp. 475-488 ◽  
Author(s):  
Ian Dobson ◽  
Benjamin A. Carreras ◽  
Vickie E. Lynch ◽  
Bertrand Nkei ◽  
David E. Newman

We compare and test statistical estimates of failure propagation in data from versions of a probabilistic model of loading-dependent cascading failure and a power system blackout model of cascading transmission line overloads. The comparisons suggest mechanisms affecting failure propagation and are an initial step toward monitoring failure propagation from practical system data. Approximations to the probabilistic model describe the forms of probability distribution of cascade sizes.


2009 ◽  
Vol 42 (5) ◽  
pp. 209-214 ◽  
Author(s):  
A. Bobbio ◽  
D. Codetta-Raiteri ◽  
S. Montani ◽  
L. Portinale

2008 ◽  
Vol 387 (23) ◽  
pp. 5922-5929 ◽  
Author(s):  
Z.J. Bao ◽  
Y.J. Cao ◽  
L.J. Ding ◽  
G.Z. Wang ◽  
Z.X. Han

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