Design of an IoT-Based loads priority and predictive maintenance for industrial transformer systems

Abstract

This research project's goal is to address the issues with electricity supply that customers encountered in developing industries, where most of the time the power outage is the big issue to deal with. The industrial transformer is the key component of the industry for power transition to satisfy electrical requirements of loads. In this context, the lack of Load priority and Predictive Maintenance of Industrial Transformers causes the problems to for ensuring power stability for the machines. Establishing a reliable and affordable electricity supply is crucial for power utilities to maintain a positive image and business orientation. modern technologies, particularly the Internet of Things (IoT), can be a good solution for Load priority and Predictive Maintenance. Many Industrial Transformers do not yet have a remote mechanism in place to quickly Load priority and Predictive Maintenance of Industrial Transformers. Due absence of this good technology, it is very difficult to deal and react on the abnormality of power supply systems, and can result to damage to of the connected loads and transformers. The IoT system and machine learning composed of microcontroller has been introduced to deal with these issues. The main parameters that are automatically detected are: voltage, current and temperature. When the transformer is overloaded, the system switching relay to disconnect the same machines to ensure the safety of the transformer. Remote control has also the ability to activate the buzzer when there is any fault. The integration of an IoT devices will support in Loads priority and Predictive Maintenance.