计及等效负荷密度的变电站设备故障缺陷识别仿真  

Simulation of Fault and Defect Identification of Substation Equipment by Considering Equivalent Load Density

作　　者：李明轩 李峰 颜培培 叶波 LI Mingxuan;LI Feng;YAN Peipei;YE Bo(Electric Power Research Institute of State Grid Xinjiang Electric Power Co.,Ltd.,Urumqi 830011,China)

机构地区：[1]国网新疆电力有限公司电力科学研究院,新疆乌鲁木齐830011

出　　处：《微型电脑应用》2024年第5期120-123,共4页Microcomputer Applications

摘　　要：针对变电站设备故障缺陷复杂,识别精度较低的问题,研究了计及等效负荷密度的变电站设备故障缺陷识别方法。依照有所差异的边界条件智能选取接线方式,并将结果反馈至基础参数设置部分,匹配基础参数,构建等效负荷密度模型,分析不同负荷条件下配电站设备运行的馈线功率损失与电压降落情况,将所得馈线功率损失与电压降落情况作为变电站设备故障特征信息输入深度学习网络,通过二次学习与训练完成变电站设备故障缺陷识别。仿真结果显示该方法能够准确计算负荷的有功线损与电压降落情况,有效识别并定位变电站设备故障缺陷。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 selects 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 equipment 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 defects 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 

分 类 号：TM721[电气工程—电力系统及自动化]