基于分层多智能体的智能电网广域保护异常检测

Vivek Kumar Singh, Altay Ozen, M. Govindarasu
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引用次数: 15

摘要

未来的智能电网能力为扩展先进的信息通信技术向密集互联的网络物理系统演进提供了保证。补救行动方案(RAS)广泛用于广域保护,依赖于互联网络和数据共享设备,暴露在众多漏洞中。本文提出了一种基于多智能体的RAS方案,用于对抗系统感知的隐形网络攻击。具体来说,我们提出了两级分层架构,该架构由分布式本地RAS控制器(rasc)组成,作为本地代理,在不同的区域/区域运行,由监督者(中央代理)不断监控。本地控制器接收本地和随机变化的外部区域测量,并循环转发给监督员。监督员使用异常检测算法识别损坏的控制器,该算法处理来自本地控制器的测量,使用本地和外部区域测量计算测量误差,执行验证检查,最后根据两步验证检测异常。接下来,作为概念验证,我们在爱荷华州立大学PowerCyber试验台的网络物理环境中实施并验证了所提出的方法。我们还实现了协调攻击向量,包括破坏本地控制器,然后对系统的生成器进行隐形攻击。我们在在线测试期间对其检测率和延迟性进行了评估。实验结果表明,该方法可以有效地检测各种类型的攻击,包括斜坡攻击和脉冲攻击。
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A Hierarchical Multi-Agent Based Anomaly Detection for Wide-Area Protection in Smart Grid
Future smart grid capabilities provide assurance to expand the advanced information and communication technologies to evolve into densely interconnected cyber physical system. Remedial Action Scheme (RAS), widely used for wide-area protection, relies on the interconnected networks and data sharing devices, which are exposed to the multitude of vulnerabilities. This paper presents our proposed approach to developing multi-agent based RAS scheme against the system-aware stealthy cyber-attacks. Specifically, we propose the two-level hierarchical architecture which consists of distributed local RAS controllers (RAScs) as local agents, operating at different zones/ areas, which are constantly monitored by an overseer, the central agent. The local controllers receive local and randomly changing outside zonal measurements and cyclically forwards to the overseer. The overseer identifies the corrupted controller using the anomaly detection algorithm which processes the measurements coming from the local controllers, compute measurement errors using local and outside zonal measurements, perform validation checks, and finally detect anomalies based on the two-step verification. Next, as a proof of concept, we have implemented and validated the proposed methodology in cyber physical environment at Iowa State’s PowerCyber testbed. We have also implemented the coordinated attack vectors which involve corrupting the local controller and later performing stealthy attacks on the system’s generator. We have evaluated its performance during the online testing in terms of detection rate and Iatency. The experimental results show that it is efficient in detecting different classes of attacks, including ramp and pulse attacks.
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