Impact of transmission distortion of line-outage-state information on cascading failures

被引:0
|
作者
Zhang, Yudong [1 ]
Cao, Yijia [1 ,2 ]
Bao, Zhejing [1 ]
机构
[1] College of Electrical Engineering, Zhejiang University
[2] College of Electrical and Information Engineering, Hunan University
来源
Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2012年 / 36卷 / 24期
关键词
Cascading failure; Hidden failure; Information network; Large blackout; Power system reliability;
D O I
10.3969/j.issn.1000-1026.2012.24.002
中图分类号
学科分类号
摘要
The impact of failures in the information network on a power system is seldom, if ever, considered in the conventional research on cascading failures in power systems. Therefore, the information network is integrated with the hidden failure model to investigate the impact of node failures in the information network on the cascading failures in power systems. Take the New England 39-bus system as an example. A new index is used to identify the key-buses causing large blackouts. The index is very effective in identifying the key-buses which exert vital influence on blackouts in power systems operating in various states. Simulation results show that the failures of the information network may make the situation even worse and lead to large blackouts. Moreover, high-degree and, in fact, high-betweenness nodes in the information network, are not the key information nodes that generate important influence in the spread of cascading failures. Rather, compared with the topological characteristics of information nodes in their own network, the physical characteristics of the information nodes corresponding transmission lines are better able to characterize the importance of information nodes in the cascading failures of the power system. © 2012 State Grid Electric Power Research Institute Press.
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页码:4 / 9
页数:5
相关论文
共 16 条
  • [1] Han Z., Cao Y., Power system security and its prevention, Power System Technology, 28, 9, pp. 1-6, (2004)
  • [2] Watts D.J., Small Worlds: The Dynamics of Networks Between Order and Randomness, (1998)
  • [3] Meng Z., Lu Z., Song J., Comparison analysis of the small-world topological model of Chinese and American power grids, Automation of Electric Power Systems, 28, 15, pp. 21-29, (2004)
  • [4] Carreras B.A., Newman D.E., Dobson I., Et al., Evidence for self-organized criticality in electric power system blackouts, IEEE Trans on Circuits and Systems, 51, 9, pp. 1733-1740, (2004)
  • [5] Carreras B.A., Newman D.E., Dobson I., Et al., Initial evidence for self-organized criticality in electric power blackouts, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences, (2000)
  • [6] Yu Q., Guo J., Statistics and self-organized criticality characters of blackouts in China electric power systems, Automation of Electric Power Systems, 30, 2, pp. 16-21, (2006)
  • [7] Mei S., He F., Zhang X., Et al., An improved OPA model and the evaluation of blackout risk, Automation of Electric Power Systems, 32, 13, pp. 1-5, (2008)
  • [8] Dobson I., Chen J., Throp J.S., Et al., Examining criticality of blackouts in power system models with cascading events, Proceedings of the Annual 35th Hawaii International Conference on System Sciences, (2002)
  • [9] Stubna M.D., Fowler J., An application of the highly optimized tolerance model to electrical blackouts, International Journal of Bifurcation and Chaos, 13, 1, pp. 237-242, (2003)
  • [10] Cao Y., Ding L., Jiang Q., Et al., A predictive model of power system blackout based on synergetic theory, Proceedings of the CSEE, 25, 18, pp. 13-19, (2005)