论文标题
在大型电力系统上存在严重协调的网络攻击的情况下，有弹性状态估计
Resilient State Estimation in Presence of Severe Coordinated Cyber-Attacks on Large-Scale Power Systems
论文作者
论文摘要
根据电网上的严重协调网络攻击，在许多测量中可能不信任，这对于网格的可靠监视和弹性操作是必不可少的，从而提供情境意识。在这种情况下，由于可观察性丧失，一组良好的测量本身不足以进行状态估计。在本文中，我们根据输出聚类提出了一种弹性状态估计算法。通过增加各个集群变量设置的测量，可以恢复系统的可观察性，并可以计算出可靠的状态估计值。我们通过IEEE 24-BUS Power System上的示例来显示我们提出的算法的数值性能及其成功替换损坏的测量结果的能力。
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.
