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To enhance the accuracy and fault tolerance of fault diagnosis, an intelligent distributed fault automatic diagnosis algorithm for distribution networks based on weighted queues is proposed. After the feeder terminal unit collects the fault current information of each switch, the fault current is scheduled and transmitted to the dispatching center server according to the weighted fair queue algorithm. By designing an improved weighted fair queue algorithm based on bandwidth allocation, a distribution network intelligent distributed fault diagnosis evaluation function is constructed. The quantum particle swarm optimization algorithm is introduced to automatically optimize the solution process of the evaluation function, ultimately achieving the automatic diagnosis of intelligent distributed faults in distribution networks. The test results show that when the learning coefficient is 4, the quantum particle swarm optimization algorithm has the best performance. The proposed algorithm can diagnose multiple faults in the distribution network and determine the fault section. The algorithm has good fault diagnosis fault tolerance, and the diagnosis effect is only affected when the fault information of multiple switches near the fault location is lost. At the same time, the algorithm has good information scheduling capability and short delay time.
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Basic Information:
China Classification Code:TP277;TM73
Citation Information:
[1]XI Jiawei,HU Jing,JIANG Hao ,et al.Design of Intelligent Distributed Fault Automation Diagnosis Algorithm for Distribution Networks[J].Journal of Dalian Jiaotong University().
2026-04-11
2026-04-11
2026-04-11