Security Risk Identification and Mitigation for Renewable Energy-Integrated Power Systems Under Cyber-Attacks

Abstract

With the large-scale integration of renewable energy sources such as wind and photovoltaic power, their control systems have become highly dependent on communication networks, exposing grid-connected devices such as inverters to cyber intrusion risks. This study considers two representative cyberattack classes, namely false-data injection in measurement and feedback channels and control-command tampering in converter-control channels. These attacks can introduce active/reactive-power deviations or corrupted point-of-commoncoupling feedback, thereby exciting oscillatory interactions between the renewable energy subsystem and the rest of the power system. Such attacks may induce wideband oscillations in the power system, extending from the sub-synchronous to the supersynchronous frequency range and posing a serious threat to secure and stable system operation. The system is decomposed into NEW and REST subsystems, where open-loop eigenvalues are used for modal-resonance risk estimation and participation factors are employed to localize dominant parameters for mitigation. A fourmachine two-area wind-photovoltaic integrated power system is used to evaluate the proposed risk identification and mitigation framework. The results demonstrate that the proposed method can accurately identify power-system operational security risks caused by cyber-attacks on renewable energy grid integration.