IoT-Driven Transformer Health Monitoring and Fault Detection: Advancing Reliability in Emerging Power Systems

Abstract

Transformers in electrical systems constitute basic devices in any modern power generation system because they allow efficient transfer of energy and they also contribute greatly toward the stability of the entire electrical system. The fact that they are using aging infrastructure with heavy overloading, however, is among the factors that significantly contribute to the risk that transformer failures might take place, thus cause a service outage and cause major economic losses. To address such challenges, this paper introduces Transformer Health Monitoring System (THMS) which is an Internet of Things (IoT) based system. The suggested system will include a NodeMCU platform and a set of sensors to continuously monitor key parameters, including temperature, voltage, current, and oil level. The obtained information is stored in a Firebase cloud database to enable real-time monitoring, and in case of surpassing operating limits, automated messages to mobile devices are dispatched. In addition, geolocation applications enable the detection and location of faults in distributed installations in a very short time. The experimental findings demonstrate that the proposed solution increases fault detection efficiency, reduces response time, and lowers maintenance costs compared to traditional monitoring practices, thereby enhancing the reliability and efficiency of transformer operation.