Aiming at the problem of complex substation equipment faults and defects,low identification accuracy,a substation equipment fault and defect identification method is studied by considering equivalent load density.This paper intelligently se-lects the wiring mode according to the different boundary conditions,feedbacks the results to the basic parameter setting part,matchs the basic parameters,builds the equivalent load density model,analyzes the feeder power loss and voltage drop of the e-quipment operation of the distribution station under different load conditions,and inputs the obtained feeder power loss and voltage drop as the fault characteristic information of the substation equipment into the deep learning network.The fault and defect identification of substation equipment is completed through secondary learning and training.Simulation results show that this method can accurately calculate the active line loss and voltage drop of load,and effectively identify and locate the fault de-fects of substation equipment.
关键词
等效负荷密度/变电站设备/故障缺陷识别/功率损失
Key words
equivalent load density/substation equipment/fault and defect identification/power loss
维普
万方数据