【24h】

A NEW APPROACH FOR DISTANCE PROTECTION USING ARTIFICIAL NEURAL NETWORK

机译:基于人工神经网络的远程保护新方法

获取原文
获取原文并翻译 | 示例

摘要

This paper presents an artificial neural network (ANN) based approach for three-zone distance protection of transmission lines. The proposed neural network-based distance relay has multilayer feedforward architecture with two inputs and three trip/(no trip) output signals. The first output is responsible for main protection of the transmission line section, whereas the other two outputs provide back-up protection for the adjacent line sections. The input features of the neural network are the fundamental frequency voltage and current magnitudes extracted by discrete-Fourier transform. In this paper, the back propagation training technique has been used for off-line training of the proposed ANN distance relay. The Input-output patterns were simulated for faults covering the three zones of protection at different locations, operating conditions, and fault inception angles. The simulation results presented in this paper show that the proposed ANN distance relay is very effective in detection and classification of line faults and therefore can be considered as a good tool for main and backup digital distance protection.
机译:本文提出了一种基于人工神经网络(ANN)的传输线三区域距离保护方法。所提出的基于神经网络的距离继电器具有多层前馈架构,具有两个输入和三个跳闸/(无跳闸)输出信号。第一个输出负责传输线路部分的主保护,而其他两个输出为相邻线路部分提供备用保护。神经网络的输入特征是通过离散傅立叶变换提取的基频电压和电流幅度。在本文中,反向传播训练技术已用于所提出的ANN距离继电器的离线训练。针对覆盖不同位置,操作条件和故障起始角度的三个保护区域的故障,模拟了输入-输出模式。本文给出的仿真结果表明,所提出的人工神经网络距离继电器在线路故障的检测和分类中非常有效,因此可以作为主,备用数字距离保护的良好工具。

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