Power System Intra-Interval Operational Security Under False Data Injection Attacks

Abstract

In false data injection (FDI) attacks, the attackers can impose security impacts by injecting false data into meter measurements to affect the security-constraint economic dispatch, which develops the dispatch for the end of a dispatch interval. Thus, the existing security analysis methods basically assess the attack impact based on a snapshot of system condition at the interval end, at which the dispatch target is achieved. Such analysis falls into a static analytical framework (SAF). However, with the increasing share of intermittent resources, the system is suffering short-term fluctuations, which may increase the variability and render security weak points inside of a dispatch interval. Smart attackers can judiciously exploit these weak points to impose large impacts on the Intra-Interval operational security. Such cyber risk may be underestimated under the SAF adopted by existing methods. To address such risk, a dynamic analytical framework is proposed in this article for analyzing the Intra-Interval operational security impacts of potential FDI attacks by considering the system variability in the dispatch interval. Simulations are performed based on the historical wind data on the IEEE 118-bus system, which verify the effectiveness of the proposed approach and highlight the risk of such issues in power systems with significant wind penetration.