基于ICEEMDAN-GWO-SVM的煤矿井下单相接地故障选线  

Single-phase ground fault line selection of coal mine power supply system based on ICEEMDAN-GWO-SVM

作　　者：谢子殿 赵欣荣 刘帅 XIE Zidian;ZHAO Xinrong;LIU Shuai(School of Electrical and Control Engineering,Heilongjiang University of Science and Technology,Harbin 150022,China)

机构地区：[1]黑龙江科技大学电气与控制工程学院,哈尔滨150022

出　　处：《黑龙江电力》2024年第1期70-76,共7页Heilongjiang Electric Power

基　　金：黑龙江省重点研发计划指导类项目(项目编号:GZ20220122);黑龙江省省属高等学校基本科研业务费项目(项目编号:2021-KYYWF-1480)。

摘　　要：为解决煤矿配电网发生单相接地故障时,难以对故障线路准确识别的问题,提出一种基于改进的自适应噪声完备集合经验模态分解(ICEEMDAN)的灰狼算法优化支持向量机(GWO-SVM)配电网单相接地故障选线方法。采用ICEEMDAN对不同工况下的每一条线路的零序电流进行分解,对各线路分解后的第一个模态分量IMF1求裕度因子、残差量相对能量系数和综合相关系数,然后将求解出的3种特征值组合形成特征向量,最后输入GWO-SVM中进行模式识别。通过Matlab/Simulink搭建包含4条馈线的10 kV配电网仿真模型进行验证。仿真结果表明,该方法不受故障位置、故障初始角、过渡电阻的影响,具有较高的选线准确率。In order to solve the problem that it is difficult to accurately identify the fault line when single phase grounding faults occur in coal mine distribution networks,a method of single phase grounding fault line selection based on improved adaptive noise complete set Empirical Mode decomposition(ICEEMDAN)based on grey Wolf algorithm optimization support vector machine(GWO-SVM)is proposed.ICEEMDAN was used to decompose the zero-sequence current of each line under different working conditions.The first modal component IMF 1 after decomposition of each line was determined to obtain the margin factor,and the residual was determined to obtain the relative energy coefficient and comprehensive correlation coefficient.Then the three eigenvalues were combined to form the feature vector,which was finally input into GWO-SVM for pattern recognition.A 10 kV distribution network simulation model containing four feeders was built by Matlab/Simulink for verification.The simulation results show that the proposed method is not affected by the fault location,initial fault Angle and transition resistance,and has a high line selection accuracy.

关 键 词：单相接地故障 GWO-SVM 特征向量 故障选线 

分 类 号：TD611[矿业工程—矿山机电]