Unscented Kalman filter technique for cyberattack detection for reliable distance relay operation

The digitization of substations and automation in power systems signifies a transition toward smart grids. Using standard protocols allows for data sharing and real-time monitoring across networked substation automation and protection systems. However, this development exposes the system vulnerable to threats, especially cyberattack. Cyberattacks possess the capability to induce undesired trip signal in relays, and when coordinated, they can lead to a complete system blackout with cascaded tripping in the network. This research paper presents a cyberattack detection scheme based on dynamic state estimation. The suggested technique utilizes sampled value measurement and estimate the states to distinguish between cyberattacks and normal operations. This solution utilizes the network's physical laws and unscented kalman filter technique to identify cyberattack and prevent undesired trip signals from distance relays. A variety of cyberattack scenarios are used to evaluate the suggested cyberattack detection scheme on IEEE 9 bus test system. The simulation results show the effectiveness of the suggested method in mitigating undesired relay tripping induced by cyberattacks.