| Title |
Neural Network Application for Fault Location Identifying in Substation |
| Authors |
Kyung-Min Lee ; Chul-Won Park |
| DOI |
http://dx.doi.org/10.5207/JIEIE.2018.32.11.016 |
| Keywords |
CB ; Dev C++ ; Fault location ; IED ; Learning Pattern Matrix ; Neural Network ; Substation |
| Abstract |
Because substation is complexly composed of transmission lines, generators, breakers, buses, and auxiliary transformers etc, it seems really difficult to find out where the fault occurred. Recently, there is an increasing interest in research for fault location and fault restoration using neural networks. This paper proposes a neural networks application for fault location identifying in substation. First, event information such as the operation status of CB(Circuit Breaker) and IED(Intelligent Electronic Device) etc are collected from the substation operating devices. A learning pattern matrix is constructed by using the faults types that can occur in transmission line, generator, breaker, bus, and auxiliary transformer in substation. We design the neural network to find the fault point in the substation using Dev C++ software and learn the learning pattern matrix. Finally, we use the test pattern matrix to evaluate the performance to find the fault location in the proposed neural network. |