Power system fault diagnosis based on Bayesian network
Dan Su · Dianli zidonghua shebei · 2007
According to the internal logic relationships among element fault,protective relay action and circuit breaker trip,the general fault diagnosis models of transmission lines,busbars and transformers are respectively established to solve the information uncertainty problem in power system fault diagnosis,which organizes a special Bayesian network composed of Noisy-Or and Noisy-And nodes,and uses back propagation algorithm in parameter learning.The Bayesian network for each element diagnosis is generated automatically according to the relationships among element,protective relays and circuit breakers.By element diagnosis network reasoning,the element fault probability is obtained.Instance simulations show the feasibility and effectiveness of the proposed fault diagnosis method for both simple and complex faults,even when there is malfunction of protective relays or circuit breakers.