Fault Diagnosis for Distribution Networks Based on Fuzzy Information Fusion

In allusion to realize the fault pattern recognition in distribution network with a low degree of automation, a fault diagnosis method based on the fusion of fuzzy information is presented. For the purpose of improving the efficiency of fault diagnosis on important branch lines, based on the hierarchical model of feeder, the membership function through fusion of equipment alarm information in important branch lines and telephones complain information is improved. Besides, in order to reduce the adverse effects caused by manually setting the threshold too high or too low, the threshold value is partitioned by random sampling on the historical data, then we gets the statistical probability in different sections of threshold. Moreover, the evaluation parameter is defined to revise the fault diagnosis results to make the algorithm owe the ability to diagnosis multiple faults, thus solving the problem that multiple nodes fault is misjudged into fault in their public upstream node. Finally, a distribution line is taken as an example to verify the validity and permissibility of the algorithm in the case of both single failure and multiple failures.