Machine Learning Approached for Sophisticated Relay to Mitigate Blackouts in Power System

This research presents an advanced relay selection framework that leverages artificial intelligence to enhance the reliability of power systems. The proposed approach integrates various machine learning (ML) models to identify and select smart relays in real-time, effectively mitigating blackout conditions. Among the models explored, Random Forest framework demonstrated superior performance in dynamic power system environments. The findings reveal that the proposed framework significantly reduces computational complexity compared to exhaustive search strategies, while delivering the highest performance metrics compared to existing methods. Furthermore, the approach achieves near-optimal secrecy performance, offering a robust and efficient solution for modern power systems.