Cascading failure modeling and robustness evaluation based on AC power flow

被引：0
作者：
Hu F. [1 ]
Chen L. [1 ]
Chen J. [1 ]
机构：
[1] School of Electrical Engineering and Automation, Jiangsu Normal University, Xuzhou
来源：
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | 2021年 / 49卷 / 18期
基金：
中国国家自然科学基金;
关键词：
AC power flow; Cascading failures; Complex network; Vulnerable transmission lines;
D O I：
10.19783/j.cnki.pspc.201509
中图分类号：
学科分类号：
摘要：
Cascading failures are one of the main causes of blackouts, and fragile lines play an extremely critical role in the evolution of cascading failures. To identify potential fragile lines in cascading failures, based on complex network theory and actual characteristics of power systems, taking line apparent power as line flow, an AC power flow cascading failure model is proposed. Four indicators of electrical in-degree electrical out-degree, and electrical betweenness centrality, as well as weighted power flow transfer entropy are proposed to identify vulnerable lines from the three aspects of network local, global and power flow functional characteristics. Finally, the robustness of the power grid are evaluated through 6 IEEE standard test systems. The results show that the deliberate attack strategy based on the electrical in-degree centrality index will cause the greatest damage to the grid after a cascading failure, and the robustness of the power grid will gradually increase as the network scale increases. © 2021 Power System Protection and Control Press.
引用
收藏
页码：35 / 43
页数：8
相关论文
共 30 条
  • [21] SUN Qiming, SHI Libao, SI Dajun, Et al., Research on transmission grid risk assessment based on cascading failure accident chain search, Power System Protection and Control, 45, 19, pp. 27-34, (2017)
  • [22] ZHANG X, ZHAN C, CHI K T., Modeling the dynamics of cascading failures in power systems, IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 7, 2, pp. 192-204, (2017)
  • [23] ZHAN C, CHI K T, SMALL M., A general stochastic model for studying time evolution of transition networks, Physica A: Statistical Mechanics and its Applications, 464, pp. 198-210, (2016)
  • [24] JIN Bo, XIAO Xianyong, CHEN Jing, Et al., Cascading failure risk assessment considering protection failure and power grid dynamic balance characteristics, Power System Protection and Control, 44, 8, pp. 1-7, (2016)
  • [25] WU Chen, HAN Haiteng, QI Wanchun, Et al., Research on power grid vulnerability identification method based on improved line efficiency, Power Engineering Technology, 37, 5, pp. 64-68, (2018)
  • [26] FANG J, SU C, CHEN Z, Et al., Power system structural vulnerability assessment based on an improved maximum flow approach, IEEE Transactions on Smart Grid, 9, 2, pp. 777-785, (2018)
  • [27] KOC Y, WARNIER M, KOOIJ R E, Et al., A robustness metric for cascading failures by targeted attacks in power networks, 2013 10th IEEE International Conference on Networking, Sensing and Control (ICNSC), pp. 48-53, (2013)
  • [28] LIU B, LI Z, CHEN X, Et al., Recognition and vulnerability analysis of key nodes in power grid based on complex network centrality, IEEE Transactions on Circuits and Systems II: Express Briefs, 65, 3, pp. 346-350, (2018)
  • [29] FAN W, ZHANG X, MEI S, Et al., Vulnerable transmission line identification using ISH theory in power grids, IET Generation Transmission & Distribution, 12, 4, pp. 1014-1020, (2018)
  • [30] LIU J, XIONG Q, SHI W, Et al., Evaluating the importance of nodes in complex networks, Physica A: Statistical Mechanics and its Applications, 452, pp. 209-219, (2016)
123