IoT-Enabled Real-Time Monitoring and Loss-of-Life Estimation of Distribution Transformers
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Date
2025
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Universitas Sriwijaya, Indralaya, Indonesia
Abstract
A distribution transformer is required in power distribution networks to step down the
voltage relevant and usable for consumers. Its failure not only disrupts electricity
supply but also incurs high replacement costs, with broader economic implications.
Ensuring reliable operation, therefore, requires accurate and continuous monitoring of
its performance. This paper presents IoT-Enabled Real-Time Monitoring and Loss-of-
Life Estimation of Distribution Transformers developed and tested on a 10 kVA, 0.415
kV prototype distribution transformer, connected to three residential loads. A dedicated
data acquisition system was developed, which monitors key parameters: load current,
phase voltage, transformer oil level, ambient temperature, and oil temperature in real
time over 14 days. An algorithm was implemented to analyze daily load profiles and
hotspot temperature data, which were then used to estimate transformer loss of life. The
results show that transformer ageing is highly sensitive to load variation. During
weekdays, the cumulative equivalent ageing reached 2.22 hours per day, corresponding
to a daily loss of life of 0.00296%. On weekends, higher residential loads increased
cumulative ageing to 4.79 hours, with a corresponding life loss of 0.0063%. A
simulated one-hour peak load of 1.43 pu resulted in 25.75 hours of ageing, translating
to a life loss of 0.034%, demonstrating the severe impact of overloads. These findings
emphasize that peak load periods dominate insulation ageing and can substantially
reduce service life if unchecked.
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Keywords
IoT, real-time monitoring, loss of life, distribution transformer