Fault Diagnosis Method Of Distribution Network Based On Time Sequence Hierarchical Fuzzy Petri Nets

A large number of alarm information will be generated after the distribution network fails, these information can be used to identify fault components quickly. Since the existing fault diagnosis methods of Petri nets do not fully utilize the time sequence attribute of alarm information, and the time sequence reasoning and fuzzy reasoning are complicated, besides, there are few methods applied to distribution network. A novel fault diagnosis method based on time sequence hierarchical fuzzy Petri nets (TSHFPNs) is proposed for distribution network in this paper. A time interval is assigned for each proposition and rule of the TSHFPNs model to describe the timing constraint of alarm information. The matrix reasoning algorithm can be applied to different system structures, the model has good adaptability. The fuzzy reasoning and time sequence reasoning are implemented at the same time, therefore, the time point constraint and the confidence probability of fault component can be obtained at the same time. At the end of the reasoning process, Gaussian function is introduced to optimize the fault probability and improve the accuracy of fault diagnosis results. Through the comparison and analysis of the distribution system examples, the correctness and rationality of the proposed method are verified.