Abstract：In this paper, in order to effectively discover the important links in a network, a method of identifying critical nodes in a power network is proposed, which is based on the network structure and the node dynamics. This method combines two kinds of existing node importance evaluation indicators, which are the degree centrality and the closeness centrality, at the same time, defines two evaluation indicators considering the network dynamics. The importance of a node is determined by comprehensive considering the influence of four kinds of evaluation indicators, which overcomes the one sidedness of single evaluation indicator, can get the more accurate node importance evaluation result than using single evaluation indicator. Simulation test on IEEE14 and IEEE57 node systems verifies the rationality and effectiveness of the proposed method.
傅杰, 邹艳丽, 谢蓉. 结合网络动力学的电网关键节点识别[J]. 复杂系统与复杂性科学, 2017, 14(2): 31-38.
FU Jie, ZOU Yanli, XIE Rong. Identification of Critical Nodes in a Power Network with Considering the Network Dynamics[J]. Complex Systems and Complexity Science, 2017, 14(2): 31-38.
[1] Pagani G A, Aiello M. From the grid to the smart grid, topologically[J].Physica A: Statistical Mechanics and its Applications, 2016, 449: 160-175. [2] 王光增, 曹一家, 包哲静,等. 一种新型电力网络局域世界演化模型[J].物理学报, 2009, 6: 3597-3602. Wang Guangzeng, Cao Yijia, Bao Zhejing, et al. A novel local-world evolving network model for power grids[J].Chinese Journal of Physics, 2009, 6: 3597-3602. [3] Conti J P. The day the samba stopped[power blackouts] [J].Engineering and Technology, 2010, 5(4): 46-47. [4] Bhangu N S, Singh R, Pahuja G L. Reliability centred maintenance in a thermal power plant: a case study[J].International Journal of Productivity and Quality Management. 2011, 7(2): 209-228. [5] Park J W, Seol W C. Considerations for severe accident management under extended station blackout conditions in nuclear power plants[J].Progress in Nuclear Energy, 2016, 88: 245-256. [6] Aguiar A S, Lamego Simoes Filho F F, Alvim A C M, et al. Station blackout in unit 1 and analysis of the wind field in the region of Angra dos Reis[J].Annals of Nuclear Energy. 2015, 78: 93-103. [7] Watanabe T, Ishigaki M, Hirano M. Analysis of BWR long-term station blackout accident using TRAC-BF1[J].Annals of Nuclear Energy 2012, 49: 223-226. [8] Zeng B, Ouyang S, Zhang J, et al. An analysis of previous blackouts in the world: lessons for China′s power industry[J].Renewable and Sustainable Energy Reviews, 2015, 42: 1151-1163. [9] 林伟芳, 汤涌, 孙华东,等. 巴西“2.4”大停电事故及对电网安全稳定运行的启示[J].电力系统自动化, 2011, 35(9): 1-5. Lin Weifang, Tang Yong, Sun Huadong, et al. Brazil “2.4” blackout accident and its implications for power system security and stability operation[J].Automation of Electric Power System, 2011, 35(9): 1-5. [10] 汤涌, 卜广全, 易俊. 印度“7.30”、 “7.31”大停电事故分析及启示[J].中国电机工程学报, 2012, 32(25): 167-174. Tang Yong, Bu Guangquan, Yi Jun. India “7.30” and “7.31” blackout accident analysis and revelation[J].Proceedings of the CSEE, 2012, 32(25): 167-174. [11] Hu J T, Du Y X, Mo H M, et al. A modified weighted TOPSIS to identify influential nodes in complex networks[J].Physica A: Statistical Mechanics and Its Applications, 2016, 444: 73-85. [12] Mo H M, Gao C, Deng Y. Evidential method to identify influential nodes in complex networks[J].Journal of Systems Engineering & Electro-nics, 2015, 26(2): 381-387. [13] Zhao J, Yu L, Li J R, et al. Identifying influential nodes based on graph signal processing in complex networks[J].Chinese Physics B, 2015, 24(5): 58904-58913. [14] Zhang T P, Fang B, Liang X Y. A novel measure to identify influential nodes in complex networks based on network global efficiency[J].Modern Physics Letters B, 2015, 29(28): 1550168. [15] Du Y, Gaoa C, Hub Y, et al. A new method of identifying influential nodes in complex networks based on TOPSIS[J].Phys A, 2014, 399: 57-69. [16] 刘彬, 王文吉, 李雅倩,等. 基于能量因素的无线传感器网络关键节点判定算法[J].电子与信息学报, 2014, 36(7): 1728-1734. Liu Bin, Wang Wenji, Li Yaqian, et al. Key nodes decision algorithm for wireless sensor networks based on energy factor[J].Journal of Electronics & Information Technology, 2014, 36(7): 1728-1734. [17] 张喜平, 李永树, 刘刚,等. 节点重要度贡献的复杂网络节点重要度评估方法[J].复杂系统与复杂性科学, 2014, 11(3): 26-32. Zhang Xiping, Li Yongshu, Liu Gang, et al. Evaluation method of complex network node importance based on node importance contribution[J].Complex Systems and Complexity Science, 2014, 11(3): 26-32. [18] 肖卫东, 谭文堂, 葛斌,等. 网络节点重要度的快速评估方法[J].系统工程理论与实践, 2013, 33(7): 1898-1904. Xiao Weidong, Tan Wentang, Ge Bin, et al. A fast evaluation method for the importance of network nodes[J].Systems Engineering-Theory & Practice, 2013, 33(7): 1898-1904. [19] 许立雄, 刘俊勇, 刘洋,等. 节点重要度的分类综合评估[J].中国电机工程学报, 2014, 34(10): 1609-1617. Xu Lixiong, Liu Junyong, Liu Yang, et al. Classification and synthesis evaluation of node importance[J].Proceedings of the CSEE, 2014, 34(10): 1609-1617. [20] 鞠文云, 李银红. 基于最大流传输贡献度的电力网关键线路和节点辨识[J].电力系统自动化, 2012, 36(9): 6-12. Ju Wenyun, Li Yinhong. Key lines and nodes identification of power network based on maximum transmission contribution degree[J].Automation of Electric Power Systems, 2012, 36(9): 6-12. [21] 于会, 刘尊, 李勇军. 基于多属性决策的复杂网络节点重要性综合评价方法[J].物理学报, 2013, 2(12): 1-8. Yu Hui, Liu Zun, Li Yongjun. Comprehensive evaluation method of complex network node importance based on multi attribute decision making[J].Chinese Journal of Physics, 2013, 2(12): 1-8. [22] Filatrella G, Nielsen A H, Pedersen N F. Analysis of a power grid using a kuramoto-like model[J].European Physical Journal. B, 2008, 61(4): 485-491.
