Development of a Real-time Power Quality Monitoring System for Low-Voltage Transformers Using IoT and Firebase Cloud

Abstract

Currently, low-voltage distribution transformers (22/0.4 kV) frequently encounter overloading and phase unbalance issues. Traditional manual inspections lack continuity, while Supervisory Control and Data Acquisition (SCADA) systems incur prohibitively high installation costs. This research article aims to develop a real-time three-phase power quality monitoring system for low-voltage distribution transformers using Internet of Things (IoT) technology to overcome the limitations of inspection latency. The system architecture consists of a Schneider PM2230 meter as the primary measurement unit, processed via an Arduino Mega 2560 microcontroller, and transmits data through a SIM7600E module to the Firebase Cloud Database. Laboratory calibration results indicate that the developed system achieves high accuracy, with an average error of only 0.55% for voltage and 0.04% for current compared to a FLUKE 115 standard reference instrument. The highlight of this research is its ability to immediately detect phase unbalance problems at a significantly lower installation cost than standard SCADA systems. By providing real-time alerts, the system successfully reduces the detection time from hours to seconds, which is highly beneficial for the implementation of future predictive maintenance strategies for distribution transformers.