Effect of Communication Failures on State Estimation of 5G-Enabled Smart Grid
Effect of Communication Failures on State Estimation of 5G-Enabled Smart Grid
复制标题
通信故障对 5G 智能电网状态估计的影响
DOI：
10.1109/access.2020.3002981
复制
发表时间：
2020
期刊：
影响因子：
3.9
通讯作者：
B. Helvik
中科院分区：
文献类型：
--
作者：
T. A. Zerihun;M. Garau;B. Helvik
信息和通信技术（ICT）、广域测量系统（WAMS）和状态估计是可靠、准确地了解电网的关键工具，也是智能电网信息化运行的基础。然而，信息通信技术给电网运营带来了新的潜在漏洞，需要进行评估。电力系统和ICT系统之间的强烈相互依赖性需要新的方法将智能电网建模为信息物理系统（CPS），并最终分析ICT故障对电网运行的影响。本文提出了一种新颖的方法，结合随机活动网络 (SAN) 建模和数值计算，对基于 5G 的 WAMS 进行可靠性分析。考虑组件故障等内部影响和降雨效应等外部影响，并通过 WAMS 功能评估这些故障的影响，为执行准确的电力网络状态估计提供可靠的数据。不同的状态估计方法（传统 SCADA 和基于 PMU 的算法）和天气条件在平均状态估计误差和安全性方面进行了比较。结果强调，基于 5G 的 WAMS 产生了接近理想的行为，这增强了智能电网监控应用未来采用的前景。
Information and Communication Technologies (ICT), Wide Area Measurement Systems (WAMS) and state estimation represent the key-tools for achieving a reliable and accurate knowledge of the power grid, and represent the foundation of an information-based operation of Smart Grids. Nevertheless, ICT brings new potential vulnerabilities within the power grid operation, that need to be evaluated. The strong interdependence between power system and ICT systems requires new methodologies for modeling the smart grid as a Cyber Physical System (CPS), and finally analyzing the impact of ICT failures on the power grid operation. This paper proposes a novel methodological approach that combines Stochastic Activity Networks (SAN) modeling and numerical computation for dependability analysis of a 5G-based WAMS. Internal influences such as component failures and external influences such as rain effect are considered, and the impact of these failures are assessed over the WAMS capability to provide reliable data for performing an accurate power network state estimation. Different state estimation approaches (traditional SCADA and PMU-based algorithms) and weather conditions are compared in terms of mean states estimation error and safety. The results highlight that 5G based WAMS result in a close-to-ideal behavior which enforces the prospect of a future adoption for smart grid monitoring applications.