Fault location technique of 154 kV substation using neural network

作     者：Ahn, Jong-Bok Kang, Tae-Won Park, Chul-Won 안종복;강태원;박철원

作者机构：Dept. of Electrical Engineering Gangneung-Wonju National University Korea Republic of Dept. of Biomedical Convergence Engineering Gangneung-Wonju National University Korea Republic of Dept. of Computer Science and Engineering Gangneung-Wonju National University Korea Republic of 

出 版 物：《Transactions of the Korean Institute of Electrical Engineers》 (Trans. Korean Inst. Electr. Eng.)

年 卷 期：2018年第67卷第9期

页      面：1146-1151页

核心收录：

主　　题：Location 

摘      要：Recently, researches on the intelligence of electric power facilities have been trying to apply artificial intelligence techniques as computer platforms have improved. In particular, faults occurring in substation should be able to quickly identify possible faults and minimize power fault recovery time. This paper presents fault location technique for 154kV substation using neural network. We constructed a training matrix based on the operating conditions of the circuit breaker and IED to identify the fault location of each component of the target 154kV substation, such as line, bus, and transformer. After performing the training to identify the fault location by the neural network using Weka software, the performance of fault location discrimination of the designed neural network was confirmed. Copyright © The Korean Institute of Electrical Engineers.