On-line Condition Monitoring of Power Transformer Health Status Enforced by Temperature and Electrical Signatures

Abstract

Transformers play a vital role in the electrical power system network, loss of a power transformer has severe consequences on both the utility and customers depending on how long time it is out-of-service. Internal faults are said to be the most likely cause of disruption in transformer's performance and, consequently, interruption of power supplied. Developing an on-line method to monitor and investigate the health of a transformer will help asset managers to assess infrastructure while it is operational, leading to reduced running costs and increased component life. This research develops methods of on-line and on-going condition monitoring of power transformers based on monitoring the transformer signatures (voltage and current on both sides of the transformer), winding and core temperature. An experimental study has been conducted to investigate the behaviour of a transformer under healthy and unhealthy conditions. A transformer designed to provide access to sections/turns terminals was used to generate short circuit test in different locations during operational time, thermocouples are distributed across the transformer windings' discs in order to record their temperature during normal and abnormal operation. The results confirm the possibility of, in real time, detecting the presence of a short circuit fault, indicating its location and its severity. The correlation between the measured variables indicate the magnitude of the circulating current, thus the fault severity can be classified. The transformer temperature may also indicate the faulty windings and moreover which disc in each winding is short circuited.

Development of the Smart Transformer Detection Learning Kit Using IoT

“…The obtained data from various parameters can be used to analyze data in various conditions to find causes of the problems or malfunctions, forecasting events in near future, etc. [3]. Then, the survey of students' satisfaction with the learning kit was delivered to investigate students' perceptions of the kit in the aspects of the accuracy of the transformer detection system and the quality of the learning kit.…”