计算机工程与应用 ›› 2023, Vol. 59 ›› Issue (16): 330-336.DOI: 10.3778/j.issn.1002-8331.2205-0513

• 工程与应用 • 上一篇    

面向电力调度数据网的节点重要性评估方法

徐志光,林晓康,陈励凡,陈洪,吴晓铭,刘延华   

  1. 1.国网福建省电力有限公司,国网福建省电力调度控制中心,福州 350003
    2.国网信通亿力科技有限责任公司,福州 350003
    3.新疆大学 软件学院,乌鲁木齐 830008
    4.福州大学 计算机与大数据学院,福州 350108
  • 出版日期:2023-08-15 发布日期:2023-08-15

Node Importance Evaluation Method for Power Dispatching Data Network

XU Zhiguang, LIN Xiaokang, CHEN Lifan, CHEN Hong, WU Xiaoming, LIU Yanhua   

  1. 1.State Grid Fujian Electric Power Co., Ltd., State Grid Fujian Power Dispatching Control Center, Fuzhou 350003, China
    2.State Grid Info-Telecom Great Power Science and Technology Co., Ltd., Fuzhou 350003, China
    3.School of Software, Xinjiang University, Urumqi 830008, China
    4.College of Computer and Data Science, Fuzhou University, Fuzhou 350108, China
  • Online:2023-08-15 Published:2023-08-15

摘要: 在电力调度数据网中,预先对网络中的节点进行系统性评估,从而对其中的关键节点进行保护,对维护整个电力系统的安稳运转具有重要意义。从网络边权的角度出发,通过先分析网络中边的重要性,再分析节点重要性,得到准确的节点重要性评估。该方法计算网络中不同链路的局部重要性、全局重要性和业务重要性,并利用各指标信息熵值得到综合的链路重要性。最后将链路的重要性分配给相邻的节点,从而得到各节点的实际影响力。通过仿真实验,在不同类型的网络上进行分析,验证了该方法在网络效率方面识别关键节点的有效性。

关键词: 电力调度数据网, 网络效率, 节点重要度, 业务重要度, 信息熵

Abstract: In the power dispatching data network, the nodes are systematically evaluated in advance, so as to protect the key nodes, which is of great significance to maintain the safe and stable operation of the whole power system. From the perspective of network edge weight, this paper proposes an accurate node influence evaluation method by analyzing the influence of edges in the network. Firstly, the local importance, global importance and business importance of different edges in the network are calculated, and then the comprehensive edge importance is obtained by calculating the index information entropy values. Finally, the importance of the edge is assigned to adjacent nodes, so as to obtain the actual influence of each node. Through simulation experiments, the effectiveness of the algorithm for identifying key nodes in the network efficiency is verified.

Key words: power dispatching data network, network efficiency, node importance, business importance, information entropy