基于网络结构和潮流追踪的电网关键节点识别

doi:10.16088/j.issn.1001-6600.2019.01.015

广西师范大学学报（自然科学版） ›› 2019, Vol. 37 ›› Issue (1): 133-141.doi: 10.16088/j.issn.1001-6600.2019.01.015

• 第二十四届全国信息检索学术会议专栏 • 上一篇下一篇

基于网络结构和潮流追踪的电网关键节点识别

邹艳丽^*, 姚飞, 汪洋, 王瑞瑞, 吴凌杰

广西师范大学电子工程学院,广西桂林541004

收稿日期:2018-06-03 出版日期:2019-01-20 发布日期:2019-01-08
通讯作者: 邹艳丽(1972—),女,河北沧州人,广西师范大学教授,博士。E-mail:zouyanli72@163.com
基金资助:
国家自然科学基金(11562003);广西多源信息挖掘与安全重点实验室系统性研究课题基金(13-A-02-03)

Critical Node Identification for Power Systems Based on Network Structure and Power Tracing

ZOU Yanli^*,YAO Fei,WANG Yang,WANG Ruirui,WU Lingjie

College of Electronic Engineering, Guangxi Normal University, Guilin Guangxi 541004,China

Received:2018-06-03 Online:2019-01-20 Published:2019-01-08

摘要/Abstract

摘要： 本文综合电网拓扑结构和基于潮流追踪技术,提出一种关键节点识别方法。首先根据潮流运算,得到电力网络中节点之间的潮流流向,然后对电力网络进行潮流追踪运算,得到节点之间的链接强度,并以此建立电网的加权有向网络模型,定义加权有向网络中的出、入强度,根据节点强度和负荷权重定义节点的重要性评价指标。以IEEE39节点系统和IEEE14节点系统为测试案例,得到各系统中节点的重要性排序。按照排序结果对节点进行过负荷攻击,以系统在节点受到攻击后潮流熵的变化来验证节点重要度排序是否合理,研究表明本文提出的方法在电网关键节点识别中更加合理有效。

关键词: 加权有向网络, 潮流追踪, 潮流熵, 过负荷攻击, 关键节点识别

Abstract: Based on the topology of the power grid and the power tracing technique, a critical node identification method is proposed. Firstly,according to the result of the power flow calculation, the power flow direction between nodes can be obtained and then the power grid can be traced,so as to get the link strength matrix of nodes and establish the weighted directed network model for the power grid.Accordingly, the outbound and inbound strengths of the nodes as well as an evaluation index of nodes can be defined according to their importance based on the node strength and load weight.Taking IEEE39 system and IEEE14 system as testing cases, the importance of the nodes in each system is ranked. According to the results of ranking, the nodes will be overload attacked. To verify whether the order of importance of the nodes is reasonable,the change of power flow entropy is calculated after the node is overload attacked. The results show that the proposed method is more reasonable and effective in identifying the critical nodes of the power grid.

Key words: weighted-directed network, power tracing, power flow entropy, overload attack, critical node identification

中图分类号:

TM74

邹艳丽, 姚飞, 汪洋, 王瑞瑞, 吴凌杰. 基于网络结构和潮流追踪的电网关键节点识别[J]. 广西师范大学学报（自然科学版）, 2019, 37(1): 133-141.

ZOU Yanli,YAO Fei,WANG Yang,WANG Ruirui,WU Lingjie. Critical Node Identification for Power Systems Based on Network Structure and Power Tracing[J]. Journal of Guangxi Normal University(Natural Science Edition), 2019, 37(1): 133-141.

参考文献

[1] MOTTER A E,LAI Yingcheng.Cascade-based attacks on complex networks[J].Physical Review E,2002,66(6):065102. DOI:10.1103/PhysRevE.66.065102.
[2] PASTOR-SATORRAS R,VESPIGNANI A.Immunization of complex networks[J].Physical Review E,2002,65(3): 036104.DOI:10.1103/PhysRevE.65.036104.
[3] ZHAO Ming,ZHOU Tao,WANG Binghong,et al.Enhanced synchronizability by structural perturbations[J].Physical Review E,2005,72(5):057102.DOI: 10.1103/PhysRevE.72.057102.
[4] 印永华,郭剑波,赵建军,等.美加“8.14”大停电事故初步分析以及应吸取的教训[J].电网技术,2003,27(10):8-11,16.DOI: 10.13335/j.1000-3673.pst.2003.10.002.
[5] ZAMORA-LOPEZ G,ZHOU Changsong,KURTHS J.Cortical hubs form a module for multisensory integration on top of the hierarchy of cortical networks[J].Frontiers in Neuroinformatics,2010,4:1.DOI: 10.3389/neuro.11.001.2010.
[6] 徐行,李华强,赵祥云,等.基于运行状态和网络结构的节点综合脆弱性评估[J].电网技术,2014,38(3):731-735.DOI: 10.13335/j.1000-3673.pst.2014.03.028.
[7] 郑京,邹艳丽,何郁郁,等.两种分布式电站连接策略对网络动态特性的影响[J].广西师范大学学报(自然科学版),2015,33(2):15-21.DOI: 10.16088/j.issn.1001-6600.2015.02.003.
[8] 徐林,王秀丽,王锡凡.电气介数及其在电力系统关键线路识别中的应用[J].中国电机工程学报,2010,30(1):33-39. DOI:10.13334/j.0258-8013.pcsee.2010.01.007.
[9] 梁颖,方瑞明,卢小芬,等.基于复杂网络理论的电力系统脆弱线路辨识研究现状[J].电力系统保护与控制,2012,40(20):151-155.DOI:10.3969/j.issn.1674-3415.2012.20.027.
[10] 张富超,谢成荣,沈立新,等.基于源流路径链和输电介数的电网关键线路辨识[J].电力系统保护与控制,2015,43(21):7-12.
[11] ALBERT R,ALBERT I,NAKARADO G L.Structural vulnerability of the North American power grid[J].Physical Review E,2004,69(2):025103.DOI:10.1103/PhysRevE.69.025103.
[12] KINNEY R,CRUCITTI P,ALBERT R,et al.Modeling cascading failures in the North American power grid[J].European Physical Journal B:Condensed Matter and Complex Systems,2005,46(1):101-107.DOI:10.1140/epjb/e2005-00237-9.
[13] 谭玉东,李欣然,蔡晔,等.基于电气距离的复杂电网关键节点识别[J].中国电机工程学报,2014,34(1):146-152.DOI: 10.13334/j.0258-8013.pcsee.2014.01.017.
[14] 林鸿基,赵昱宣,林冠强,等.基于改进节点重要度贡献矩阵的电网关键节点识别[J].电力建设,2017,38(10):62-68. DOI:10.3969/j.issn.1000-7229.2017.10.009.
[15] 曹一家,陈晓刚,孙可.基于复杂网络理论的大型电力系统脆弱线路辨识[J].电力自动化设备,2006,26(12):1-5,31. DOI:10.3969/j.issn.1006-6047.2006.12.001.
[16] 王涛,高成彬,顾雪平,等.基于功率介数的电网关键环节辨识[J].电网技术,2014,38(7):1907-1913.DOI:10.13335/j. 1000-3673.pst.2014.07.029.
[17] 王佳裕,顾雪平,王涛,等.一种综合潮流追踪和链接分析的电力系统关键节点识别方法[J].电力系统保护与控制,2017,45(6):22-29.DOI:10.7667/PSPC160434.
[18] 谢开贵,李春燕,赵渊,等.电力系统功率分配的解析模型和算法[J].中国电机工程学报,2005,25(22):27-31.DOI:10. 13334/j.0258-8013.pcsee.2005.22.005.
[19] 曹一家,王光增,曹丽华,等.基于潮流熵的复杂电网自组织临界态判断模型[J].电力系统自动化,2011,35(7):1-6.

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基于网络结构和潮流追踪的电网关键节点识别

Critical Node Identification for Power Systems Based on Network Structure and Power Tracing

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