Fault Diagnosis Based on Bayesian Petri Nets

This paper provides a kind of Bayesian Petri net model and presents a fault diagnosis method for power grid based on this model. Firstly, the BPN models for each component are established in power cut area separately, according to the fault spread directions. Secondly, the failed component is determined by the application of Petri net reasoning and Bayesian probability calculation. At last, the result is given by fusing all parties’ results using mean method. Diagnosis analysis showed that this method had better fault tolerance under the condition of incomplete information and had better adaptability after the change of network topology structure. In the BPN reasoning, calculating the fault probability of component is based on the prior probability from statistics, so the subjectivity of setting related parameters can be avoided. Copyright © 2014 IFSA Publishing, S. L.