Impact Analysis of False Data Injection Attack on Smart Grid State Estimation Under Random Packet Losses

Supervisory control and data acquisition (SCADA) system has been widely used in traditional power systems for operation and control. As increasingly more ICT technologies are deployed to improve the smartness of the power grid, cyber security is becoming an important issue in the development of smart grids, for example, false data injection attack (FDIA) poses a serious threat. The paper analyzes the impact of false data injection attack on smart grid state estimation under random packet losses. First, a measurement model of power grids under random packet loss is established, and an attack vector range that can fool the attack detector is acquired. Then, a mean square error matrix of weighted least squares estimation is proposed, taking into account potential false data injection attacks. A IEEE-14 nodes system is used to evaluate the performance of the weighted least squares state estimation under three different scenarios, namely false data injection attack only, random packet loss only, and under both random packet loss and false data injection attack.