Study of Fault Location by Algorithm of Rough Sets for Distribution Network

被引:0
|
作者
Xu, Tongyu [1 ]
Cao, Yingli [1 ]
Zheng, Wei [1 ]
机构
[1] Shenyang Agr Univ, Sch Informat & Elect Engn, Shenyang 110161, Peoples R China
关键词
rough set; distribution network; decision table; fault location; WebGIS;
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
A new algorithm for Web GIS fault location in distribution network is presented by using the trouble calling information in this paper. Through deeply study of rough set theory, the algorithm is considered the topology characteristics of the distribution network which have the large-scale and multi-line equipment. Based on the methods of identification matrix attribute reduction and improved value reduction, the algorithm simplifies the decision table which based on the distribution network topology, removes the inherent redundancy in the complaint information and synthesizes new minimum fault diagnosis expert decision library. In this method the trivial calculation is not necessary. The time for fault location and isolation can be greatly shortened. While the information of trouble calling is not imperfect, the fault location can still be finished quickly and accurately. Because of the good fault tolerant performance the method ensures the objectivity of the fault diagnosis rules. Simulation results and applications show that the method is simple, feasible and effective.
引用
下载
收藏
页码:594 / 597
页数:4
相关论文
共 50 条
  • [41] Fault location of power distribution network based on fruit fly optimization algorithm
    Wang W.
    Wang C.
    Ao X.
    Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control, 2019, 47 (18): : 108 - 114
  • [42] Fault Location of Underground Distribution Network Based on RBF Network Optimized by Improved PSO Algorithm
    Tian, Shu
    Zhao, Min
    FIFTH INTERNATIONAL CONFERENCE ON MACHINE VISION (ICMV 2012): ALGORITHMS, PATTERN RECOGNITION AND BASIC TECHNOLOGIES, 2013, 8784
  • [43] A Fault Diagnosis Method Combining Rough Sets And Neural Network
    Jie, Yang
    ICICTA: 2009 SECOND INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION TECHNOLOGY AND AUTOMATION, VOL II, PROCEEDINGS, 2009, : 483 - 486
  • [44] Fault location for distribution network based on fault distance distribution function
    Tan, D. (453786800@qq.com), 1600, Power System Technology Press (36):
  • [45] Fault Diagnosis of Computer Network Based On Rough Sets and BP Neural Network
    Shang, Zhixin
    Zhou, Yu
    Ye, Qingwei
    Wang, Xiaodong
    2012 INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, NETWORKING AND MOBILE COMPUTING (WICOM), 2012,
  • [46] Fault management: analysis of fault location algorithm in optical network
    ZHENG, Yan-lei
    HUANG, Shan-guo
    ZHANG, Xian
    GU, Wan-yi
    Journal of China Universities of Posts and Telecommunications, 2009, 16 (04): : 23 - 28
  • [48] Study on fault location of single-phase-to-ground for distribution network
    Zhang, Li
    Yang, Xiuyuan
    Ren, Junling
    ADVANCES IN POWER AND ELECTRICAL ENGINEERING, PTS 1 AND 2, 2013, 614-615 : 1101 - 1106
  • [49] Dynamic Testing Algorithm Based on Rough Sets for Multiple Fault Diagnosis
    Gao, Lei
    Zeng, Guangzhou
    FIFTH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, VOL 3, PROCEEDINGS, 2008, : 157 - 163
  • [50] Fault location of multistage feeders in distribution network
    Chen, Yanxia
    Wang, Lu
    Ji, Hongquan
    Wang, Jian
    Yu, Xijuan
    Gu, Jun
    2019 4TH INTERNATIONAL CONFERENCE ON INTELLIGENT GREEN BUILDING AND SMART GRID (IGBSG 2019), 2019, : 49 - 53