Performance Evaluation of Early Warning System for Transformer Faults at 20KV Distribution Substation

This paper presents the implementation of an internet of things (IoT)-based early warning system for transformer disturbances at a 20KV distribution substation. This system is designed for real-time monitoring of distribution substations over long distances. system is designed as a solution to problems that often occur in 20KV distribution substations where the transformers show different usage patterns at peak load times. This occurs when usage is high during the day and low at night. This research is a solution to provide protection for distribution substations against conditions that have the potential to cause damage or system failure to transformer components. Distribution transformers are one of the vital components of the electric power system infrastructure. The heat produced by electromagnetic energy can increase the temperature of the transformer and potentially damage the components inside, so temperature is the main thing whose value must be measured and monitored at all times to ensure that the components in the substation remain safe. Temperature can be sensed using the DS18B20 sensor, and the reading results of the environment can be accessed remotely using IoT media. From the test results of this system, it was found that the load ratio calculation on the transformer during the day was around 516.67 kVA, equivalent to 41.336% of the load, while at night it was around 414.65 kVA, equivalent to 33.172% of the load. A transformer with a capacity of 1250 kVA may be loaded continuously when the temperature is around 20°C, whereas under installation conditions at a temperature of around 30°C, it can only be loaded 90%.