首页 | 本学科首页   官方微博 | 高级检索  
     

基于VMD双狼群算法的电网单相接地故障选线优化
引用本文:付华,孟繁东. 基于VMD双狼群算法的电网单相接地故障选线优化[J]. 计算机应用与软件, 2019, 36(2): 269-273
作者姓名:付华  孟繁东
作者单位:辽宁工程技术大学电气与控制工程学院 辽宁葫芦岛125105;辽宁工程技术大学电气与控制工程学院 辽宁葫芦岛125105
基金项目:国家自然科学基金;辽宁省重点实验室项目
摘    要:针对电网单相接地故障选线的问题,对传统小波分解线路故障选线法进行改进,提出一种VMD(Variational Mode Decomposition)双狼群算法对故障选线进行优化。利用变分模态分解VMD提高信号的分解精度,对各条线路故障前后的能量特征进行提取,并形成故障的特征向量作为神经网络的输入。同时为了提高传统狼群算法的寻优精度,引入双狼群算法,建立一种VMD-DLWCA-NN模型,并由该模型的输出来判定故障线路。仿真实验验证了该方法的准确性。通过与小波算法法及传统算法对比,表明优化后的系统选线效果更好。

关 键 词:单相接地  双狼群算法  变分模态分解

SINGLE-PHASE GROUNDING FAULT LINE SELECTION OPTIMIZATION FOR POWER GRID BASED ON VMD DOUBLE WOLVES COLONY ALGORITHM
Fu Hua,Meng Fandong. SINGLE-PHASE GROUNDING FAULT LINE SELECTION OPTIMIZATION FOR POWER GRID BASED ON VMD DOUBLE WOLVES COLONY ALGORITHM[J]. Computer Applications and Software, 2019, 36(2): 269-273
Authors:Fu Hua  Meng Fandong
Affiliation:(School of Electrical and Control Engineering, Liaoning Technology University, Huludao 125105, Liaoning, China)
Abstract:Aiming at the problem of single-phase grounding fault line selection in power network, we improved the traditional wavelet decomposition fault line selection method and proposed a VMD dual-wolf colony algorithm to optimize the fault line selection. The variational mode decomposition (VMD) was used to improve the signal decomposition accuracy. The energy features of each line before and after the fault were extracted and the fault eigenvector was formed as the input of the neural network. To improve the searching accuracy of traditional wolves algorithm, we introduced the double wolves colony algorithm, and established a VMD-DLWCA-NN model. The fault line was determined by the output of the model. The simulation experiment proves the accuracy of the method. Compared with wavelet algorithm and traditional algorithm, the optimized system is more effective in line selection.
Keywords:Single-phase grounding  Double wolves colony algorithm  Variational mode decomposition
本文献已被 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号