Fault line selection method for resonant grounded system Based on the BP neural network

摘要：

One-phase ground fault is the most common faults in distribution network, but the existing methods of fault line selection is greatly effected by fault close Angle, arc grounding and other factors, so, the accuracy of fault line selection is not very satisfactory. In this paper, through the introduction of artificial neural network, We use BP neural network to train the morphological filtered fault data, and select fault line on the basic of training of the zero sequence current when one-phase ground fault occurs on resonant grounded system with the help of trained BP neural network. We prove that the method is feasible and effective after the simulation of result.

关键词： resonant grounded system. Transient zero sequence current neural network BP fault line selection

作者: Yanbo Li Yanjun Li Lili Wang

作者单位: Sanmenxia Power Supply Company Sanmenxia,China Lingbao Electricity Power Bureau Lingbao,China Zhijiang college of Zhejiang University of Technology Hangzhou,China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer and Network Technology(ICCNT 2011)(2011第三届IEEE计算机与网络技术国际会议)

会议地点: 太原

会议语种:英文

页码: 505-509

在线出版日期: 2011-02-26（万方平台首次上网日期，不代表论文的发表时间）