Operating State Reconstruction in Cyber Physical Smart Grid for Automatic Attack Filtering
Huaizhi Wang, Xichang Wen, Yinliang Xu, Bin Zhou, Jianchun Peng, Wenxin Liu
Abstract
Eliminating the erroneous state bias from cyberattack is essential to ensure the real-time control and secure operation of the smart grid, especially when cyberattack flourishes in recent years. For this reason, this article, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">for the first time</i> , proposes a new operating state reconstruction scheme to automatically filter out possible cyberattacks in smart grid. This scheme consists of an attack separation method, a state forecasting algorithm, and a state recovery approach. Based on P-Q decomposition, the attack separation method takes into account the network parameter perturbations and prediction uncertainties to analytically estimate the regular deviation of each state, thereby identifying potential abnormal states. Then, a particle filtering-based state forecasting algorithm is developed to evaluate the original operating level of the detected contaminated states. Finally, we propose a fast bilinear state recovery approach to mitigate the smearing effect of undetected contaminated states due to cyberattacks. The proposed state reconstruction method can not only detect cyberattacks but also realize automatic correction of the erroneous states, thus mitigating the devastating impact of attack on smart grids. The feasibility and effectiveness of our reconstruction scheme are extensively validated on IEEE standard 9-, 14-, 30-, 57- and 118-bus power systems. The obtained results show that the proposed scheme exhibits strong robustness, high stability, and promising performance for automatic attack filtering, indicating a great potential for implementations in deep cyber-penetrated smart grids.