Classified Fault Diagnosis of Power Grid Based on Probabilistic Petri Net

According to the fault alarm information, the power grid faults are classified into three categories: simple fault, complex single fault and complex multiple fault, and the corresponding diagnosis models will be established to reduce the redundant operation in diagnosis. For the complex multiple faults, the existing probabilistic Petri nets are improved as follows: (1) Introduced the "non-logic" relation in the probabilistic Petri net; (2) the transition ignition function of the probabilistic Petri net is improved; (3) The input arc weights are analyzed to find more suitable for improving the probability Petri net. Three typical fault examples of Siping power grid in Jilin province are used to simulate and test the diagnosis method in this paper. The simulation results show that this method reduces the unnecessary modeling process and diagnosis time for simple fault diagnosis, gives correct diagnosis results under incomplete information, and improves the diagnosis efficiency and accuracy of complex multiple faults.