Development of an IoT-Based Smart Distribution Transformer Monitoring System for Reliable Rural Electrification

• Olalekan OGUNBIYI

  Author

• Lambe M. ADESINA

  Author

• Ibrahim Z. ARIYO

  Author

Distribution transformers are essential components of electric power distribution networks, and their reliable operation depends on continuous monitoring of critical operating parameters. However, conventional inspection techniques are periodic, labour-intensive, and incapable of providing the real-time information required for proactive maintenance. This study presents the design, implementation, and experimental validation of an Internet of Things (IoT)-based smart distribution transformer monitoring system for real-time acquisition and remote visualisation of transformer operating parameters. The developed system integrates isolated voltage and current sensing circuits, an Arduino Uno microcontroller, an ESP8266 Wi-Fi communication module, a 16 × 2 liquid crystal display (LCD), and the Blynk cloud platform for simultaneous local and remote monitoring. The sensing circuits were calibrated using polynomial and exponential regression models to improve measurement accuracy, while the complete hardware was designed, simulated, and verified using the PROTEUS Design Suite before fabrication. Experimental evaluation was conducted over a voltage range of 181–249 V and load currents up to 9 A. The developed system exhibited excellent agreement with calibrated reference instruments, recording a maximum voltage deviation of approximately 1 V (less than 0.5%) and a maximum current deviation of 0.1 A (approximately 1.1%). In addition, the estimated apparent power, real power, and power factor closely matched the reference values. The communication subsystem maintained stable Wi-Fi connectivity, achieving a data transmission success rate exceeding 99% with dashboard refresh times below 2.1 s, thereby enabling reliable real-time cloud monitoring. The proposed monitoring system provides a low-cost, accurate, and scalable solution for continuous condition monitoring of distribution transformers and offers significant potential for predictive maintenance and intelligent asset management in modern smart grid applications.

• 45_Ogunbiyi et al. (2026)

Copyright (c) 2026 Olalekan OGUNBIYI, Lambe M. ADESINA, Ibrahim Z. ARIYO (Author)

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.