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- W2379352309 abstract "A novel method for on-line transient stability prediction considering uncertainties was presented, which was based on Monte Carlo and Naive Bayesian classifier. The method took the uncertainties into account such as loads, injection power of nodes, fault clear time, fault line and position. It sampled the parameters using Monte Carlo, clustered the sample with the purpose of saving simulation time, regenerated and rearranged the discrete variable of original sample after getting the stability of clustered sample. Then minimum risk Naive Bayesian classifier was constructed based on Bayesian theory and risk theory, which was used for on-line transient stability prediction. Simulation was carried out based on New England test system and the results showed that the method had the merits of high precision and concept clear. The method presents a new way to transient stability on-line prediction considering uncertainties." @default.
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- W2379352309 date "2009-01-01" @default.
- W2379352309 modified "2023-09-23" @default.
- W2379352309 title "On-line Transient Stability Prediction Considering Uncertainties" @default.
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