Internet of Things-Based Transformer Winding Lumped Parameters Monitoring

Accurate measurement of transformer lumped parameters is crucial for efficiency, performance optimization, and fault detection. This study proposes an IoT system to address the issue of often computationally aided and non-physical measurements. The system automates real-time measurement and monitoring of parameters such as resistance, inductance, and capacitance using temperature, current, and voltage sensors. Data is wirelessly transmitted to a central unit, enhancing modeling and simulation of transformer behavior, aiding analysis and validation of mathematical models. The system allows continuous circuit analysis, timely anomaly detection, and intervention, aiding efficiency improvement. IoT data assists design optimization, informed decision-making, and proactive failure analysis by detecting deviations from expected values and potential transformer failures. By integrating IoT into larger electrical systems, engineers can enhance system integration, stability, and performance characteristics.