ENHANCED FAULT DETECTION TECHNIQUES FOR SMART GRIDS UNDER VARIABLE RENEWABLE GENERATION

Abstract

Smart grids are becoming more dependent on renewable energy sources such as solar and wind power. However, the unstable and fluctuating nature of renewable energy creates serious challenges for accurate fault detection. Variations in voltage, current, frequency, and power flow can sometimes appear similar to fault conditions, which may increase false alarms or delay fault identification. This paper focuses on enhancing fault detection in smart grids under fluctuating renewable energy supply by using intelligent monitoring and data-based fault analysis. The study evaluates fault detection performance under different renewable penetration levels and changing operating conditions. The results indicate that the proposed fault detection approach improves detection accuracy, reduces false alarm rates, and maintains strong performance during renewable power fluctuations. The findings also show improved response time, better classification of fault types, and increased robustness against noise. Overall, the study demonstrates that intelligent fault detection can improve smart grid reliability, reduce power interruptions, and support safer integration of renewable energy into modern power systems.