Self-Organized Critical State Identification of Power Systems Based on Structural Equilibrium Theory
Gu Xueping1, Liu Yumemg1, Wang Tao1, Qin Xiaohui2
1. School of Electrical & Electronic Engineering North China Electric Power University Baoding 071003 China; 2. China Electric Power Research Institute Beijing 100192 China
Abstract:Self-organized critical state identification has the important value for preventive control of cascading failures and power network planning. First, the transmission lines are represented as virtual nodes and the power flow interactive relations between the transmission lines as virtual links. Synthesizing the initial load rate, load rate increment and average of load rate increment, this paper defines the sign properties of the virtual links and then constructs a state correlation networks where importance degree of lines is used as node weight and the link sign properties as link weight. Based on the structural equilibrium theory of signed networks, the balance structure pattern and classification of power system operating states is established and analyzed. On this basis, a comprehensive of power network imbalance evaluation index is proposed to represent the power flow distribution characteristic and quantify power system disturbance dissolving ability, which can identify the self-organized criticality of a power system. Numerical results indicate that the defined imbalance index can effectively indicate the self-organized criticality of a power system in different network topologies, load rates and power flow entropy, and especially it works well when the system load rate and power flow entropy is lower.
顾雪平, 刘雨濛, 王涛, 秦晓辉. 基于结构平衡理论的电网自组织临界态辨识[J]. 电工技术学报, 2018, 33(17): 4136-4145.
Gu Xueping, Liu Yumemg, Wang Tao, Qin Xiaohui. Self-Organized Critical State Identification of Power Systems Based on Structural Equilibrium Theory. Transactions of China Electrotechnical Society, 2018, 33(17): 4136-4145.
[1] 孙伟卿, 王承民, 张焰, 等. 电力系统运行均匀性分析与评估[J]. 电工技术学报, 2014, 29(4): 173-180. Sun Weiqing, Wang Chengmin, Zhang Yan, et al.Analysis and evaluation on power system operation homogeneity[J]. Transactions of China Electrotechni- cal Society, 2014, 29(4): 173-180. [2] 蔡晔, 曹一家, 谭玉东, 等. 基于标准化结构熵的电网结构对连锁故障的影响[J]. 电工技术学报, 2015, 30(3): 36-43. Cai Ye, Cao Yijia, Tan Yudong, et al.Influences of power grid structure on cascading failure based on standard structure entropy[J]. Transactions of China Electrotechnical Society, 2015, 30(3): 36-43. [3] 沈鑫, 束洪春, 曹敏, 等. 大区互联电网的动态稳定风险评估研究与应用[J]. 电工技术学报, 2016, 31(增刊1): 230-238. Shen Xin, Shu Hongchun, Cao Min, et al.Risk assessment and research of dynamic stability for large-scale interconnected grids and its application[J]. Transactions of China Electrotechnic- al Society, 2016, 31(S1): 230-238. [4] 王涛, 李渝, 顾雪平, 等. 电网关键线路序元搜索方法[J]. 电工技术学报, 2016, 31(2): 153-162. Wang Tao, Li Yu, Gu Xueping, et al.Study of grid’s key line sequence search method[J]. Transactions of China Electrotechnical Society, 2016, 31(2): 153-162. [5] 毕如玉, 林涛, 陈汝斯, 等. 交直流混合电力系统的安全校正策略[J]. 电工技术学报, 2016, 31(9): 50-57. Bi Ruyu, Lin Tao, Chen Rusi, et al.The security correction strategy in AC and DC hybrid power system[J]. Transactions of China Electrotechnical Society, 2016, 31(9): 50-57. [6] 蔡永智, 陈皓勇, 万楚林. 基于局部信息融合和估计投影法的多区域电力系统状态估计[J]. 电工技术学报, 2017, 32(1): 69-77. Cai Yongzhi, Chen Haoyong, Wan Chulin, et al.Multi-area power system state estimation based on partial information fusion and estimate projection[J]. Transactions of China Electrotechnical Society, 2017, 32(1): 69-77. [7] Ren Hui, Watts D.Early warning signals for critical transitions in power systems[J]. Electric Power Systems Research , 2015, 124: 173-180. [8] Zhang Yudong, Bao Zhejing, Cao Yijia, et al.Long-term effect of different topology evolutions on blackouts in power grid[J]. Electric Power and Energy System, 2014, 62: 718-726. [9] 项胜, 何怡刚, 吴可汗. 基于分形理论的国内大停电分析[J]. 电工技术学报, 2013, 28(增刊2): 367-371. Xiang Sheng, He Yigang, Wu Kehan.Blackout analysis of domestic power based on fractal theory[J]. Transactions of China Electrotechnical Society, 2013, 28(S2): 367-371. [10] Bak P.How nature works: the science of self-organized criticality[M]. New York: Copernicus Press, 1996. [11] 易俊, 周孝信, 肖逾男. 电力系统自组织临界特性分析与仿真模型[J]. 电网技术, 2008, 32(3): 7-12. Yi Jun, Zhou Xiaoxin, Xiao Yunan.Analysis on power system self-organized criticality and its simulation model[J]. Power System Technology, 2008, 32(3): 7-12. [12] Dobson I, Carreras B A, Lynch V E, et al.Complex systems analysis of series of blackouts: cascading failure, critical points, and self- organization[J]. Chaos: An Interdisciplinary Journal of Nonlinear Science, 2007, 17: 026103. [13] 钟庆, 张哲, 许中, 等. 广州配电网故障停电事故的自组织临界特征[J]. 电力自动化设备, 2017, 37(4): 109-113. Zhong Qing, Zhang Zhe, Xu Zhong, et al.SOC characteristics of power-supply failure of Guangzhou distribution network[J]. Electric Power Automation Equipment, 2017, 37(4): 109-113. [14] Zhu Z Q, Wu L J, Xia Z P.An accurate subdomain model for magnetic field computation in slotted surface- mounted permanent-magnet machines[J]. IEEE Transactions on Magnetics, 2010, 46(4): 1100-1115. [15] 何飞, 梅生伟, 薛安成, 等. 基于直流潮流的电力系统停电分布及自组织临界性分析[J]. 电网技术, 2006, 30(14): 7-12. He Fei, Mei Shengwei, Xue Ancheng, et al.Blackouts distribution and self-organized criticality of power system based on DC power flow[J]. Power System Technology, 2006, 30(14): 7-12. [16] 梅生伟, 薛安成, 张雪敏. 电力系统自组织临界特性与大电网安全[M]. 北京: 清华大学出版社, 2009. [17] 周孝信, 肖逾男. 用连锁故障搜索算法判别系统的自组织临界状态[J]. 中国电机工程学报, 2007, 27(25): 1-5. Zhou Xiaoxin, Xiao Yunan.Determining the self-organized criticality state of power systems by the cascading failures searching method[J]. Proceedings of the CSEE, 2007, 27(25): 1-5. [18] 于群, 曹娜, 郭剑波. 负载率对电力系统自组织临界状态的影响分析[J]. 电力系统自动化, 2012, 36(1): 24-27, 37. Yu Qun, Cao Na, Guo Jianbo.Analysis on influence of load rate on power system self-organized criticality[J]. Automation of Electric Power Systems, 2012, 36(1): 24-27, 37. [19] 刘文颖, 但扬清, 朱艳伟, 等. 复杂电网自组织临界态辨识物理指标研究[J]. 电工技术学报, 2014, 29(8): 274-280, 288. Liu Wenying, Dan Yangqing, Zhu Yanwei, et al.Research on physical indicators to identify power system self-organized critical state[J]. Transactions of China Electrotechnical Society, 2014, 29(8): 274-280, 288. [20] 刘文颖, 蔡万通, 张宁, 等. 基于联合加权熵的电网自组织临界状态演化[J]. 中国电机工程学报, 2015, 35(6): 1363-1370. Liu Wenying, Cai Wantong, Zhang Ning, et al.Evolution of self-organizing of grid critical state based on united weighted entropy theory[J]. Proceedings of the CSEE, 2015, 35(6): 1363-1370. [21] 刘文颖, 蔡万通, 张宁, 等. 基于加权网络拓扑熵的电网自组织临界状态演化[J]. 中国电机工程学报, 2015, 35(22): 5740-5748. Liu Wenying, Cai Wantong, Zhang Ning, et al.Evolution of grid’s self-organizing critical state based on weighted network topology entropy[J]. Proceedings of the CSEE, 2015, 35(22): 5740-5748. [22] 曹一家, 张宇栋, 林辉, 等. 基于同配性的电力系统自组织临界性识别[J]. 电力自动化设备, 2013, 33(7): 6-11. Cao Yijia, Zhang Yudong, Lin Hui, et al.Power system self-organized criticality recognition based on assortativity[J]. Electric Power Automation Equipment, 2013, 33(7): 6-11. [23] 程苏琦, 沈华伟, 张国清, 等. 符号网络研究综述[J]. 软件学报, 2014, 25(1): 1-15. Cheng Suqi, Shen Huawei, Zhang Guoqing, et al.Survey of signed network research[J]. Journal of Software, 2014, 25(1): 1-15. [24] 张维玉, 吴斌, 刘旸. 融合多特征的符号网络连边符号预测[J]. 北京邮电大学学报, 2014, 37(5): 80-84. Zhang Weiyu, Wu Bin, Liu Yang.Integrating multi-feature for link sign prediction in signed networks[J]. Journal of Beijing University of Posts and Telecommunications, 2014, 37(5): 80-84. [25] Reuven Cohen, Shlomo Havlin.复杂网络健壮性[M]. 江逸楠, 译. 北京: 国防工业出版社, 2014. [26] 韩忠明, 陈炎, 李梦琪, 等. 一种有效的基于三角结构的复杂网络节点影响力度量模型[J]. 物理学报, 2016, 65(16): 285-296. Han Zhongming, Chen Yan, Li Mengqi, et al.An efficient node influence metric based on triangle in complex networks[J]. Acta Physica Sinica, 2016, 65(16): 285-296. [27] 周涛, 肖伟科, 任捷, 等. 网络集团度的幂律分布[J]. 复杂系统与复杂性科学, 2007, 4(2): 10-17. Zhou Tao, Xiao Weike, Ren Jie, et al.Power-law clique-degree distribution[J]. Complex Systems and Complexity Science, 2007, 4(2): 10-17. [28] Dobson I, Carreras B A, Lynch V E, et al.An initial model for complex dynamics in electric power system blackouts[C]//The 34th Hawaii International Conference on System Science, Hawaii, 2001, 2: 710-718.