摘要
为减少线路参数不确定性对配电网线路故障定位结果的影响,提出一种考虑预设偏移值的多分支配电网故障定位方法。通过分析配电网线路中故障行波的传输特性,考虑预设故障点与真实故障点位置关系,定义线路端点的预设偏移值,建立了以预设故障点与行波波速为变量,总预设偏移值最小为目标的优化模型。利用灰狼优化算法下最小预设偏移值的求解原理,提出了预设故障位置与行波波速的选择方法,减少行波波速不确定性对配电网故障定位的影响,实现精确的故障定位。仿真结果表明,所提方法能够有效辨识故障支路和精确定位故障点,定位结果不易受线路参数不确定性的影响,有效提高了配电网故障定位的精度。
To reduce the impact of line parameters changes on fault location of distribution network,a fault location method based on preset offset value is proposed.By analyzing the propagation characteristics of fault traveling wave in distribution network,the preset offset value of the line terminal is defined via con⁃sidering the relationship between the preset fault position and the real fault position.Then an optimization model with the minimum preset offset value as its object is established,where the preset fault position and traveling wave velocity are variables.Further,according to the gray wolf optimization algorithm,the principle of solving the minimum preset fault location is analyzed.The selection method of the preset fault position and the preset traveling wave velocity are proposed to reduce the influence of uncertainty of traveling wave velocity on fault location of distribution network and achieve the accurate fault location.Simulative results show that the proposed method can effectively identify the fault branches and accurately locate faults.The location results are not easily affected by the uncertainty of line parameters,thus effectively improving the accuracy of fault location in distribution network.
作者
谢李为
李勇
罗隆福
曾祥君
喻锟
侯亮
曹一家
XIE Liwei;LI Yong;LUO Longfu;ZENG Xiangjun;YU Kun;HOU Liang;CAO Yijia(School of Electrical and Information Engineering,Hunan University,Changsha 410082,China;School of Electrical and Information Engineering,Changsha University of Science and Technology,Changsha 410114,China;CYG SUNRI Co.,Ltd.,Shenzhen 518057,China)
出处
《电力自动化设备》
EI
CSCD
北大核心
2023年第6期78-85,共8页
Electric Power Automation Equipment
基金
国家自然科学基金资助项目(52061130217)
深圳市承接国家重大科技资助项目(CJGJZD20200617102405015)。
关键词
配电网
故障定位
行波法
预设偏移值
灰狼优化算法
distribution network
fault location
traveling wave method
preset offset value
gray wolf optimiza⁃tion algorithm