AI DRIVEN FAULT DETECTION IN SMART GRIDS FOR ENHANCED POWER SYSTEM RELIABILITY USING MATLAB SIMULINK

The growing complexity of modern power systems has increased the need for intelligent monitoring and protection techniques. Smart grids require fast and accurate fault detection to maintain stability and reduce system disturbances. This project presents an AI-based approach for detecting and classifying faults in a smart grid environment using MATLAB/Simulink. Different fault conditions such as single line-to-ground, line-to-line, double line-to-ground, and three-phase faults are simulated under varying operating conditions. Voltage and current signals are continuously analyzed to identify abnormalities. Based on these variations, the system detects and classifies faults efficiently. The proposed method improves response time, accuracy, and reliability, making it suitable for advanced power system protection and monitoring applications.