基于灰色关联度的配电网故障区段定位与类型识别方法
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摘要
为了更全面准确地对配电网故障进行识别,提出了一种基于灰色关联度的配电网故障区段定位和故障类型识别方法。针对三相电流采用卡伦鲍厄相模变换得到0模、α模、β模,选择变化较为明显的模量,构造反映区段故障的综合模电流作为特征序列,再计算各区段的特征序列与参考正常区段之间的灰色关联度,与门限值比较从而确定故障区段。利用0模、α模、β模分量在故障前后的幅值畸变度,将故障初步分为单相接地、两相接地、相间短路故障三类。根据相模变换关系和不同类型故障的边界条件,选择不同的特征量进行灰色关联度计算,对计算结果分类处理,确定故障类型。IEEE 33节点配电网模型仿真实验结果验证了所提方法能够可靠准确地进行故障区段定位和故障类型识别,不受故障类型、接地电阻和故障相角的影响。
In order to identify the faults of distribution network more comprehensively and accurately,a method of fault location and fault type identification based on grey relational degree is proposed.Three-phase currents can be transformed to 0,αandβmodulus by Karrenbauer transformation.The module with more obvious change is selected,and the comprehensive module current that reflects the fault section is constructed as the feature sequence.Then,the grey correlation degree between the feature sequence of each section and the reference normal section is calculated,and the fault section is determined by comparing with the threshold value.The magnitude distortion of 0,αandβmodulus before and after faults is used to classify the faults into three categories:single-phase grounding,two-phase grounding and inter-phase short-circuit faults.According to the phase-mode transformation relationships and the boundary conditions of different types of faults,different characteristic variables are selected to calculate the grey relational degree,and the calculation results are classified to determine the type of faults.The simulation results of the IEEE 33-bus distribution network model verify that the proposed method can reliably and accurately locate the fault section and identify the fault type,and is not affected by the fault type,grounding resistance and fault phase angle.
In order to identify the faults of distribution network more comprehensively and accurately,a method of fault location and fault type identification based on grey relational degree is proposed.Three-phase currents can be transformed to 0,αandβmodulus by Karrenbauer transformation.The module with more obvious change is selected,and the comprehensive module current that reflects the fault section is constructed as the feature sequence.Then,the grey correlation degree between the feature sequence of each section and the reference normal section is calculated,and the fault section is determined by comparing with the threshold value.The magnitude distortion of 0,αandβmodulus before and after faults is used to classify the faults into three categories:single-phase grounding,two-phase grounding and inter-phase short-circuit faults.According to the phase-mode transformation relationships and the boundary conditions of different types of faults,different characteristic variables are selected to calculate the grey relational degree,and the calculation results are classified to determine the type of faults.The simulation results of the IEEE 33-bus distribution network model verify that the proposed method can reliably and accurately locate the fault section and identify the fault type,and is not affected by the fault type,grounding resistance and fault phase angle.
引文
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[17]孔令号,焦彦军,戴志辉.基于灰色关联度的站域保护原理[J].电网技术,2014,38(8):2274-2279.KONG Linghao,JIAO Yanjun,DAI Zhihui.A new substation area protection principle based on gray correlation degree[J].Power System Technology,2014,38(8):2274-2279.
[18]宋国兵,李森,康小宁,等.一种新相模变换矩阵[J].电力系统自动化,2007,31(14):57-60.SONG Guobing,LI Sen,KANG Xiaoning,et al.A novel phase-mode transformation matrix[J].Automation of Electric Power Systems,2007,31(14):57-60.
[19]崔艳,刘志刚,戴晨曦.HF-EMD频率选取原则及在暂态扰动检测中的应用[J].电力系统保护与控制,2014,42(21):47-53.CUI Yan,LIU Zhigang,DAI Chenxi.Frequency selection principle of HF-EMD and its application in transient disturbance detection[J].Power System Protection and Control,2014,42(21):47-53.
[2]徐垦.配电网接地故障点定位的编码S注入法[J].电气自动化,2014,36(6):61-63.XU Ken.Encoded S-injection scheme for locating ground fault in the distribution network[J].Electrical Automation,2014,36(6):61-63.
[3]齐郑,庄舒仪,刘自发,等.基于并联电阻扰动信号的配电网故障定位方法分析[J].电力系统自动化,2018,42(9):195-200.DOI:71110.7500/AEPS20170817005.QI Zheng,ZHUANG Shuyi,LIU Zifa,et al.Analysis on distribution network fault location method based on parallel resistance distribution signal injection[J]. Automation of Electric Power Systems,2018,42(9):195-200.DOI:10.7500/AEPS20170817005.
[4]常仲学,宋国兵,王晓卫.基于零序电压幅值差的配电网断线识别与隔离[J].电力系统自动化,2018,42(6):135-139.DOI:10.7500/AEPS20170626001.CHANG Zhongxue, SONG Guobing, WANG Xiaowei.Identification and isolation of line breakage fault in distribution network based on zero sequence voltage amplitude differential principle[J].Automation of Electric Power Systems,2018,42(6):135-139.DOI:10.7500/AEPS20170626001.
[5]李泽文,周卿松,曾祥君,等.基于行波模量传输时差的配电网接地故障定位新方法[J].中国电力,2015,48(9):67-72.LI Zewen,ZHOU Qingsong,ZENG Xiangjun,et al.New fault location method based on time difference of traveling wave mode-component in distribution network[J].Electric Power,2015,48(9):67-72.
[6]马士聪,徐丙垠,高厚磊,等.检测暂态零模电流相关性的小电流接地故障定位方法[J].电力系统自动化,2008,32(7):48-52.MA Shicong,XU Bingyin,GAO Houlei,et al.An earth fault locating method in feeder automation system by examining correlation of transient zero mode currents[J].Automation of Electric Power Systems,2008,32(7):48-52.
[7]田书,王晓卫,王娟娟.基于相关分析的暂态零模电流与功率故障定位方法比较[J].电网技术,2011,35(4):206-211.TIAN Shu,WANG Xiaowei,WANG Juanjuan.Comparative research on fault location by transient zero-module current and transient zero-module power based on correlation analysis[J].Power System Technology,2011,35(4):206-211.
[8]付家才,陆青松.基于蝙蝠算法的配电网故障区间定位[J].电力系统保护与控制,2015,43(16):100-105.FU Jiacai,LU Qingsong.Fault sections location of distribution network based on bat algorithm[J].Power System Protection and Control,2015,43(16):100-105.
[9]李超文,何正友,张海平,等.基于二进制粒子群算法的辐射状配电网故障定位[J].电力系统保护与控制,2009,37(7):35-39.LI Chaowen,HE Zhengyou,ZHANG Haiping,et al.Fault location for radialized distribution networks based on BPSO algorithm[J].Power System Protection and Control,2009,37(7):35-39.
[10]梅念,石东源,杨增力,等.一种实用的复杂配电网故障定位的矩阵算法[J].电力系统自动化,2007,31(10):66-70.MEI Nian,SHI Dongyuan,YANG Zengli,et al.A practical matrix-based fault location algorithm for complex distribution network[J].Automation of Electric Power Systems,2007,31(10):66-70.
[11]李林,陆鼎堃,郭晋楠.基于相模变换的互相关故障定位方法[J].广东电力,2014,27(10):68-73.LI Lin,LU Dingkun,GUO Jinnan.Cross-correlation fault positioningbasedonphase-modetransformation[J].Guangdong Electric Power,2014,27(10):68-73.
[12]邵文权,吉玥,张志华.利用单一电流模量波形互相关系数的故障选相方案[J].电力系统保护与控制,2017,45(7):90-96.SHAO Wenquan,JI Yue,ZHANG Zhihua.A faulted phase selection scheme using waveform cross-correlation coefficient of single-mode current[J].Power System Protection and Control,2017,45(7):90-96.
[13]胡伟,李勇,曹一家,等.基于LOF和SVM的智能配电网故障辨识方法[J].电力自动化设备,2016,36(6):7-12.HU Wei,LI Yong,CAO Yijia,et al.Fault identification based on LOF and SVM for smart distribution network[J].Electric Power Automation Equipment,2016,36(6):7-12.
[14]刘健,张志华,张小庆,等.基于配电自动化系统的单相接地定位[J].电力系统自动化,2017,41(1):145-149.DOI:10.7500/AEPS20160118005.LIU Jian,ZHANG Zhihua,ZHANG Xiaoqing,et al.Single phase to ground fault location based on distribution automation systems[J].Automation of Electric Power Systems,2017,41(1):145-149.DOI:10.7500/AEPS20160118005.
[15]周秀文.灰色关联度的研究与应用[D].长春:吉林大学,2007:5-14.ZHOU Xiuwen.Research and application of grey relevance degree[D].Changchun:Jilin University,2007:5-14.
[16]韩迎春,童晓阳.利用时空电气量基于灰色关联度的电网故障诊断[J].电网技术,2017,41(2):581-588.HAN Yingchun,TONG Xiaoyang.The power system fault diagnosis method based on gray relational degree using spacetime electric quantity[J].Power System Technology,2017,41(2):581-588.
[17]孔令号,焦彦军,戴志辉.基于灰色关联度的站域保护原理[J].电网技术,2014,38(8):2274-2279.KONG Linghao,JIAO Yanjun,DAI Zhihui.A new substation area protection principle based on gray correlation degree[J].Power System Technology,2014,38(8):2274-2279.
[18]宋国兵,李森,康小宁,等.一种新相模变换矩阵[J].电力系统自动化,2007,31(14):57-60.SONG Guobing,LI Sen,KANG Xiaoning,et al.A novel phase-mode transformation matrix[J].Automation of Electric Power Systems,2007,31(14):57-60.
[19]崔艳,刘志刚,戴晨曦.HF-EMD频率选取原则及在暂态扰动检测中的应用[J].电力系统保护与控制,2014,42(21):47-53.CUI Yan,LIU Zhigang,DAI Chenxi.Frequency selection principle of HF-EMD and its application in transient disturbance detection[J].Power System Protection and Control,2014,42(21):47-53.
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