A new cyber-security approach for load frequency control of hybrid interconnected renewable power systems

Abstract

Countries worldwide are embracing the trend toward smart grids, depending on advanced technology and communication networks. However, the smart grid is more vulnerable to cyberattacks than its traditional counterpart, especially the false data injection attack (FDIA), which aims to add false data into the transmitted signals to cause undesirable behavior. This article proposes a new scheme to detect and estimate the FDIA on load frequency control (LFC) of modern interconnected power systems considering renewable energy sources (RESs) and high voltage direct current (HVDC) link. The proposed scheme is based on the Kalman filter (KF) and artificial neural networks (ANNs). The KF is used to detect the FDIA in the transmitted system signals and indicates the possibility of an attack in each transmitted signal, where the role of ANNs is to estimate the transmitted signal before attacking. Hence, based on KF and ANNs, the proposed scheme can ensure the detection of false data and remove the attack simultaneously. The proposed cyber-security scheme is considered a thorough solution that can effectively reduce the impact of the FDIA on any of the four transmitted signals within the two-area interconnected power system, all while simulating the virtual inertia control strategy. The simulation results of the studied low-inertia interconnected power system are carried out using MATLAB/Simulink® software. The simulation results successfully demonstrate the proposed scheme's efficacy, accuracy, and acceptability to detect and eliminate the FDIA on the LFC of low-inertia interconnected power grids.