arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2004.05143eess.SYcs.SY
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大规模电力系统遭受严重协同网络攻击时的弹性状态估计

Resilient State Estimation in Presence of Severe Coordinated Cyber-Attacks on Large-Scale Power Systems

Ana Jevtić, Marija Ilić

摘要:

鉴于电网受到严重的协同网络攻击,许多测量结果可能不可信,因此提供态势感知对于电网的可靠监控和弹性运行是必要的。在这种情况下,由于可观测性的损失,良好测量的集合本身不足以用于状态估计。本文提出了一种基于输出聚类的弹性状态估计算法。通过用相应的簇变量增广测量集,系统恢复了可观测性,并且可以计算可靠的状态估计。我们展示了我们所提出的算法的数值性能和它的能力,成功地取代损坏的测量使用集群变量通过IEEE 24总线电力系统的例子。

英文摘要:

Providing situational awareness in light of severe coordinated cyber-attacks on power grids, where many measurements may be untrusted, is necessary for reliable monitoring and resilient operation of the grid. In this scenario, the set of good measurements is by itself insufficient for state estimation due to loss of observability. In this paper, we present a resilient state estimation algorithm, based on output clustering. By augmenting the measurement set by respective cluster variables, the system observability is regained, and a reliable state estimate can be computed. We show the numerical performance of our proposed algorithm and its ability to successfully replace corrupted measurements using cluster variables through an example on the IEEE 24-bus power system.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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