Application of Feasibility Area for Cybersecurity of Electric Power Systems

The utilization of digital communication in modern power grids helps deploy the advanced and real-time power system control systems to withstand renewable energy fluctuations. This, however, could open the door to cyberattacks on the communication data. Cybersecurity layers presented by Bad Data Detection (BDD) and pre-occurrence False Data Injection (FDI) detection layers are developed to block these attacks. Such layers, however, cannot guarantee a 100% success rate, and thus, stealthy FDI attacks, which mask the system operation, can penetrate the pre-occurrence layers to change the optimal operation points. To detect the infiltrated stealthy attacks, a new post-occurrence FDI detection layer is proposed in this paper by using the concept of the Feasibility Area (FA), which identifies the region where a power system parameter exits in normal operation conditions using a historical window of data. Deterministic and non-deterministic shapes are used to represent the FA. The state of the power system parameters, such as bus voltage phasors, current phasors, apparent power, and their pattern is utilized to identify the existence of FDI cyberattacks using Pattern Recognition Neural Network (PRNN). The proposed method shows a high performance in detecting stealthy FDI cyberattacks.