A Graph Signal Processing Framework for Detecting and Locating Cyber and Physical Stresses in Smart Grids
A Graph Signal Processing Framework for Detecting and Locating Cyber and Physical Stresses in Smart Grids
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DOI：
10.1109/tsg.2022.3177154
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发表时间：
2022-09-01
影响因子：
9.6
通讯作者：
Rahnamay-Naeini, Mahshid
中科院分区：
文献类型：
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作者：
Abul Hasnat, Md;Rahnamay-Naeini, Mahshid
监测智能电网涉及分析来自部署在整个系统中的各种测量设备的连续数据流，这些测量设备在拓扑上分布并且在结构上相互关联。在本文中，一个图形信号处理（GSP）框架被用来表示和分析智能电网的安全性和可靠性分析的相互关联的测量数据。在不同的GSP域，包括顶点域，图形频率域，和联合顶点频率域中的系统中的各种网络和物理应力的影响进行评估。提出了两种新的技术的基础上的顶点频率能量分布，和局部光滑的图形信号，其性能进行了评估，用于检测和定位各种网络和物理应力。基于所提出的分析，所提出的技术表现出有前途的性能，用于检测复杂的应力，在发病时没有急剧的变化，用于检测突然的负载变化，也用于定位应力。
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, a graph signal processing (GSP) framework is used to represent and analyze the inter-related smart grid measurement data for security and reliability analyses. The effects of various cyber and physical stresses in the system are evaluated in different GSP domains including vertex domain, graph-frequency domain, and the joint vertex-frequency domain. Two novel techniques based on vertex-frequency energy distribution, and the local smoothness of graph signals are proposed and their performance have been evaluated for detecting and locating various cyber and physical stresses. Based on the presented analyses, the proposed techniques show promising performance for detecting sophisticated stresses with no sharp changes at the onset, for detecting abrupt load changes, and also for locating stresses.