| 引用本文: | 吴润泽,吴万旭,李莉,樊冰,唐良瑞.基于节点影响力的电力通信网拓扑结构诊断[J].电力系统保护与控制,2019,47(10):147-155.[点击复制] |
| WU Runze,WU Wanxu,LI Li,FAN Bing,TANG Liangrui.Topology diagnosis of power communication network based on node influence[J].Power System Protection and Control,2019,47(10):147-155[点击复制] |
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| 摘要: |
| 结合电力通信网络的结构特征，建立了面向电力通信网络的复杂网络模型，从节点邻居拓扑特征和网络聚合特征出发定义了节点影响力。采用网络属性值信息熵计算网络拓扑特征及其对节点影响力的整体贡献度，从连通性和网络效率的角度分析节点故障后对网络拓扑抗毁性和鲁棒性的影响。分别针对BA网络、WS网络、地市骨干电力通信网络和省级骨干电力通信网络的节点影响力进行了仿真分析。结果显示在网络效率和连通度方面，与采用其他复杂网络指标的方法相比，所提出的方法能够更好地反映关键节点的传播影响力。 |
| 关键词: 节点影响力 复杂网络 电力通信网 网络抗毁性 网络鲁棒性 网络诊断 |
| DOI：10.7667/PSPC20191020 |
| 投稿时间：2018-06-11修订日期：2018-08-20 |
| 基金项目:国家自然科学基金资助项目(51507063);中央高校基本科研业务费专项基金(2016MS05) |
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| Topology diagnosis of power communication network based on node influence |
| WU Runze,WU Wanxu,LI Li,FAN Bing,TANG Liangrui |
| (School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China;State Grid Jibei Economic Research Institute, Beijing 100160, China) |
| Abstract: |
| Based on the structural characteristics of the power communication network, this paper establishes a complex network model for the power communication network, and the node influence is defined from the neighbor topology characteristics and network aggregation characteristics of nodes. This paper uses the information entropy of network attribute value to calculate the overall contribution degree of network topology to node influence, and then analyzes the effect after node deletion on network topology vulnerability from the perspective of network connectivity and efficiency. Finally, the simulation analysis is conducted on the influence of the nodes in BA network, WS network, the regional backbone power communication network and the provincial backbone power communication network. The results show that this method can better reflect the impact of key nodes in terms of network efficiency and connectivity compared with other methods using complex network indicators. This work is supported by National Natural Science Foundation of China (No. 51507063) and Fundamental Research Funds for the Central Universities (No. 2016MS05). |
| Key words: node influence complex network power communication network network survivability network robustness network diagnosis |
