Optimizing Fault Detection Algorithms in Synchronous Generators Using Wavelet Transform and Fuzzy Logic for Enhanced Fault Analysis

This paper introduces a refined fault detection and analysis model for 126 MVA synchronous generators interfaced with 16kV and 230kV transmission lines, developed in Matlab Simulink. The model simulates various fault scenarios, including short-circuit and unbalanced load faults, aiming to improve fault detection accuracy through an optimized algorithm. By integrating wavelet transform for precise signal decomposition and fuzzy logic for intelligent decision-making, the algorithm enhances the capability to detect and classify faults in real-time. The improvements in signal processing allow for faster identification and localization of faults, while the fuzzy logic system provides more reliable classification, reducing false positives. This advanced algorithm demonstrates significant improvements in the protection control of synchronous generators, offering robust, timely, and accurate fault detection. The results suggest the algorithm’s potential for deployment in modern power systems, where reliable fault detection is critical for ensuring stability and efficiency.