Temperature Sensor Integration into the Node-RED Platform for Transformer Monitoring

Abstract

Transformers must be continuously monitored to guarantee dependable and effective performance. The combination of Internet of Things (IoT) technology and sophisticated data processing systems opens up new possibilities for improved transformer monitoring in this context. To enable real-time monitoring of transformer conditions, this study focuses on the integration of IoT temperature sensors into the Node-RED platform. The suggested method gathers temperature information from several locations inside the scale laboratory transformer using IoT temperature sensors. The Node-RED platform receives the collected data and processes, analyzes, and visualizes it in real time. Comprehensive monitoring is made possible by the platform, allowing operators to quickly identify any unusual temperature swings or potential problems inside the transformer. For older transformers built with normal Kraft paper, the rated hot spot temperature is either 90°C according to IEEE or 97°C according to IEC. The Node-RED platform's incorporation of IoT devices not only provides real-time monitoring capabilities but also offers the flexibility to implement predictive maintenance strategies. By harnessing the power of data analytics and visualization, operators can make informed decisions to optimize transformer performance, extend its lifespan, and minimize downtime. The results of this study demonstrate the effectiveness of the IoT temperature sensor integration into the Node-RED platform for laboratory transformer monitoring. Based on the measurement winding temperature at the transformer has reached 90 °C at full load, and then the system starts to activate the blower to cool the transformer. The approach contributes to the advancement of transformer management practices, ensuring the reliability and efficiency of critical energy infrastructure.