Machine Learning based Dynamic Overload Surge Protection System for Electrical Appliances

This paper introduces a Dynamic Overload Surge Adjustment Protection (DOSAP) system aimed at improving the safety and reliability of electrical appliances in both industrial and residential settings. The DOSAP system features a microcontroller that monitors and calculates overload limits in real time, with easy integration into SCADA systems via UART. It provides extensive protection against both low and high voltage, as well as over-current issues, using the XGBoost machine learning model to dynamically predict and adjust overload thresholds. This novel approach enhances protection accuracy and operational efficiency by minimizing the need for manual intervention and adapting to changing electrical conditions.