Research On Vulnerability Of Power Optical Transmission Network Based On Complex Network Theory

With the deep coupling of power network and information network,communication system has become the most important nerve center of power system.The power optical transmission network is an important means to ensure the safety,stability and economic operation of the power grid,and the failure of any internal node may have a major impact on the power system.Accurate identification of key nodes in the network and effective analysis of network vulnerability are of great significance for enhancing the stability of the power system and guiding the planning and construction of communication networks.However,the existing vulnerability analysis methods of power optical transmission networks still have some disadvantages.On the one hand,the general topological vulnerability identification method considers a single angle and cannot accurately reflect the structural vulnerability of the network;On the other hand,the comprehensive vulnerability analysis method combined with the power optical transmission network industry background also fails to reasonably evaluate the influence of multi-dimensional factors on the comprehensive importance of nodes.In this context,based on complex network theory,this paper studies the substantial vulnerability of power optical transmission networks.The main research work is as follows:1.Research on complex characteristics of power optical transmission network.Based on the basic methods of graph theory and complex networks,the complex topology model of the power optical transmission network is constructed,and the actual properties and inherent vulnerability mechanism of the network are analyzed by calculating various basic parameters of the network,comparing the static characteristics of the network,and fitting the statistical characteristics of the network.The results show that the provincial power optical transmission network is a small-world network,but it has certain scale-free characteristics,and the importance of nodes in the network is greatly different.It is necessary to identify the key nodes in the network to analyze the network vulnerability.2.Research on structural vulnerability of power optical transmission networks.Starting from the general topology structure of complex networks,a Key Node Identification Algorithm based on Multi-attribute Weighted Fusion(KNIA-MWF)is proposed to address the shortcomings of the current key node identification methods for complex networks.KNIA-MWF comprehensively considers the node’s own,local and global information,and integrates these multi-angle features through a combination of subjective and objective weight distribution.Based on five open source networks and provincial power optical transmission networks,it can be verified that the proposed algorithm can identify the structurally vulnerable nodes more accurately and meticulously than the existing single-angle evaluation and multi-angle simple weighted evaluation algorithms by analyzing the ranking fiequency(RF)distribution of the algorithm and the changes in network connectivity coefficient and network efficiency after attacking high-importance nodes.3.Research on comprehensive vulnerability of power optical transmission networks.In view of the shortcomings of the current comprehensive vulnerability identification methods,this paper proposes a Multi-dimensional Refined Key Node Identification(MRKNI)model,combined with the industry background of the power optical transmission network and the rich data of different dimensions provided by the current smart grid.MRKN1 model comprehensively considers the voltage level and load capacity of the site in the physical layer,the self,local and global topology characteristics in the network layer,the communication flow in the transport layer,and the quality requirements of the service in the application layer.It is verified that the proposed MRKNI model can more accurately and effectively identify the key vulnerable nodes and analyze the actual vulnerability of the provincial power optical transmission network by analyzing the RF distribution of node in different identification models and the change of network single-layer vulnerability and crosslayer vulnerability entropy(CVE)after attacking the top-ranked nodes.