Transformer Health Monitoring System

Transformers are essential components in the power transmission and distribution network, responsible for voltage transformation and ensuring uninterrupted power supply to end-users. Their failure can lead to widespread outages, economic losses, and safety risks. Traditionally, transformer health has been monitored through periodic manual inspections, which are time-consuming, labour-intensive, and often inefficient in detecting early signs of failure. This paper presents a comprehensive IoT-based Transformer Health Monitoring System (THMS) designed to provide continuous, real-time surveillance of transformer parameters. The proposed system employs a combination of temperature sensors, current sensors, ultrasonic oil level sensors, and gas detection modules interfaced with an ESP8266 microcontroller. These components work collaboratively to monitor key operating parameters such as load current, winding temperature, oil level, and gas leaks—all of which are primary indicators of transformer health. Data collected from these sensors are processed and transmitted wirelessly to a cloud-based monitoring platform using IoT protocols, where the information is displayed in real time on a user-friendly dashboard. The system is programmed to detect abnormal conditions based on predefined thresholds and automatically triggers alerts through mobile devices or cloud notifications, enabling predictive maintenance and reducing the risk of unexpected transformer failures. Additionally, all sensor data is logged for historical analysis, allowing utility providers to identify trends and optimize transformer usage. The hardware implementation has demonstrated accurate data collection and successful remote alerts under test conditions. By integrating embedded systems, wireless communication, and IoT technologies, this solution offers a scalable, low-cost, and efficient approach to transformer health monitoring. It enhances grid reliability, reduces manual inspection effort, and supports the transition toward smarter power systems.