论文标题
使用图形信号处理检测和定位智能网格中的网络和身体应力
Detection and Locating Cyber and Physical Stresses in Smart Grids using Graph Signal Processing
论文作者
论文摘要
智能电网是大型且复杂的网络物理基础架构，需要实时监视以确保系统的安全性和可靠性。监视智能电网涉及分析整个系统中部署的各种测量设备的连续数据流，这些设备在拓扑分布和结构上相互关联。在本文中，图形信号处理（GSP）已用于表示和分析电网测量数据。结果表明，GSP可以为电网的结构化数据和互连组件的动力学启用各种分析。特别是，在信号的顶点和图形频率域中评估并讨论了电网中各种网络和物理应力的影响。已经提出了几种基于GSP技术的检测和定位网络和身体应力的技术，并且已经评估和比较它们的性能。提出的研究表明，GSP可能是分析电网数据的一种有前途的方法。
Smart grids are large and complex cyber physical infrastructures that require real-time monitoring for ensuring the security and reliability of the system. Monitoring the smart grid involves analyzing continuous data-stream from various measurement devices deployed throughout the system, which are topologically distributed and structurally interrelated. In this paper, graph signal processing (GSP) has been used to represent and analyze the power grid measurement data. It is shown that GSP can enable various analyses for the power grid's structured data and dynamics of its interconnected components. Particularly, the effects of various cyber and physical stresses in the power grid are evaluated and discussed both in the vertex and the graph-frequency domains of the signals. Several techniques for detecting and locating cyber and physical stresses based on GSP techniques have been presented and their performances have been evaluated and compared. The presented study shows that GSP can be a promising approach for analyzing the power grid's data.
