Cyber-physical data stream assessment incorporating Digital Twins in future power systems

André Kummerow, Cristian Monsalve, Dennis Rösch, Kevin Schäfer, S. Nicolai
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引用次数: 3

Abstract

Reliable and secure grid operations become more and more challenging in context of increasing IT/OT convergence and decreasing dynamic margins in today’s power systems. To ensure the correct operation of monitoring and control functions in control centres, an intelligent assessment of the different information sources is necessary to provide a robust data source in case of critical physical events as well as cyber-attacks. Within this paper, a holistic data stream assessment methodology is proposed using an expert knowledge based cyber-physical situational awareness for different steady and transient system states. This approach goes beyond existing techniques by combining high-resolution PMU data with SCADA information as well as Digital Twin and AI based anomaly detection functionalities.
未来电力系统中包含数字孪生的网络物理数据流评估
在当今电力系统中,随着IT/OT融合程度的提高和动态边际的减少,可靠和安全的电网运营变得越来越具有挑战性。为了确保控制中心监测和控制功能的正确运行,有必要对不同信息来源进行智能评估,以便在发生关键物理事件和网络攻击时提供可靠的数据源。在本文中,提出了一种基于专家知识的基于网络物理态势感知的整体数据流评估方法,用于不同的稳态和瞬态系统状态。通过将高分辨率PMU数据与SCADA信息以及基于数字孪生和人工智能的异常检测功能相结合,该方法超越了现有技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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