Design and implementation of a 100 kVA transformer monitoring and fault detection system for distribution network

Abstract The increasing complexity of today’s power distribution networks requires reliable and intelligent monitoring and maintenance systems, especially as the demand for electricity increases due to technological and population growth. Transformers, as critical infrastructure components, are susceptible to faults such as overloads, phase losses and neutral failures. These faults can result in service interruptions, high maintenance costs and reduced power quality. Despite the various approaches that have been explored in the literature, existing systems often lack phase-specific fault detection, real-time reporting, and effective integration with communication technologies. This paper presents the design and implementation of a 100 kVA distribution transformer monitoring and fault detection system using IoT and GSM technologies. The system features advanced sensors, local and remote data logging, and immediate fault reporting via SMS, real-time data acquisition and an IoT platform (ThingSpeak). It addresses specific limitations of current systems. These include the inability to confirm transformer energization status during fault events. The test results validate the accuracy and reliability of the system and demonstrate its effectiveness in improving the life of transformers, reducing downtime and enabling predictive maintenance. The accuracy of the system is demonstrated by a Pearson correlation coefficient of > 0.96 when compared to traditional instruments (multimeters). The solution is affordable, scalable and in line with the digital transformation of the electrical infrastructure, which makes it particularly suitable for use in developing countries' power grids.