Event-Triggered Intelligent Control Scheme for Data Integrity Attack Mitigation in Multi-Area Power Grids

The power grids are becoming smarter with adoption of various IoT Technologies (Internet of Things). IoT calls for sensors, which are transacting real time data through communication channels, installed at various locations in power system. These communication channels not only become overloaded by high volume of state-estimation data from these sensors but are also prone to cyber-attacks. The cyber-attack may infirmly affect the load frequency control (LFC) schemes which are implemented across multi-area grids using state estimation techniques. The cyber-attack may modify system frequency via signal false data injections in system and therefore deteriorates system performance or may even lead to blackout. In this work, artificial intelligent (AI) estimator and nonlinear sliding mode controller (SMC) are combined together to form event-triggered intelligent control scheme which not only optimise the use of communication infrastructure but also attenuates cyber intrusions. The AI observer predicts grid states and also senses cyber intrusions via the back propagation error algorithm in presence of cyber-attacks. The proposed event-triggered SMC rejects the undesirable impact of cyber intrusions on the plant trajectories. The proposed event-triggered control strategy when subjected to cyber attack and power penetration from the distributed renewable resources is demonstrated through MATLAB simulations.