Energy grid state estimation under random and structured bad data
Energy grid state estimation under random and structured bad data
复制标题
随机和结构化不良数据下的电网状态估计
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
A. Tajer
中科院分区：
文献类型：
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作者：
A. Tajer
电网的状态恢复问题和不良数据检测问题虽然是强互联的，但又各自独立处理。此外，虽然已经对状态恢复进行了深入研究，但当测量被认为受到随机坏数据（由于传感器故障）或结构化坏数据（由于网络攻击）的污染时，对状态恢复的研究较少。本文提供了一个统一的框架，考虑状态恢复与坏数据检测之间的内在联系，以完成检测随机和结构化坏数据的组合任务，并为网格和注入的坏数据提供可靠的状态估计。对最优检测器和估计器进行了表征。
The problems of state recovery and bad data detection in energy grids, while being strongly interconnected, have been treated independently. Furthermore, while state recovery has been studied intensively, it has been less well studied when the measurements are deemed to be contaminated by random bad data (due to sensor failures) or structured bad data (due cyber attacks). This paper provides a unifying framework that takes into account the inherent connection between state recovery and bad data detection in order to accomplish the combined tasks of detecting the presence of random and structured bad data, and providing reliable estimates for the state of the grid and injected bad data. Optimal detectors and estimators are characterized.