首页> 外文会议>2011 International Symposium on Computer Science and Society >Prediction for Magnitude of Short Circuit Current in Power Distribution System Based on ANN
【24h】

Prediction for Magnitude of Short Circuit Current in Power Distribution System Based on ANN

机译:基于人工神经网络的配电系统短路电流幅度预测

获取原文

摘要

With the growth seen by power systems lately, short circuits have become some of the most common and damaging power system failures. Accurate forecasting of short circuit faults and predicting for magnitude of short circuit current are becoming increasingly important. Power system short circuit fault research is a basic technological problem, but at the same time a rather difficult one, which has played an important role in the design of smart grids. The introduction of ANN prediction has led to improved results over prior art fault diagnosis technologies. Although it has been employed with good results in various fields, reports of its application in power distribution short-circuit current prediction are rather limited. This article introduces the ANN theory in the sphere of short-circuit current prediction in power distribution systems. The prediction model formulated shall serve as theoretical foundation for the design of intelligent switching equipment, with global and selective protection, very likely to be found in future smart grids.
机译:随着近来电力系统的增长,短路已成为一些最常见的破坏性电力系统故障。准确预测短路故障和预测短路电流的大小变得越来越重要。电力系统短路故障的研究是一个基本的技术问题,但同时也是一个相当困难的问题,在智能电网的设计中发挥了重要作用。与现有技术的故障诊断技术相比,人工神经网络预测的引入已带来了改进的结果。尽管已经在各个领域中采用了良好的结果,但是其在配电短路电流预测中的应用的报道却非常有限。本文在配电系统的短路电流预测领域中介绍了ANN理论。所建立的预测模型将为具有全局和选择性保护的智能开关设备的设计提供理论基础,这很可能会在未来的智能电网中找到。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号