Power Transformer Degradation Condition and Insulation Index Estimation Based on Historical Oil Dat

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Muhammad Fuad Al Hamdani, Rahman Azis Prasojo, Suwarno, A. Abu-Siada

2019 Proceedings of the 2nd International Conference on High Voltage Engineering and Power Systems: Towards Sustainable and Reliable Power Delivery, ICHVEPS 2019 Conference paper Cited by 13 Quartile

Abstract

Power transformer is one of the most important assets for any electricity utility. The overall power transformer health condition can be assessed through the condition of its insulation system. Recent result of transformer oil measurements for parameters such as furan, dissolved gas analysis, water content, breakdown voltage, interfacial tension, acidity, and oil color scale are commonly used to assess the health condition of power transformers. Degradation rate of power transformer insulation system, especially paper insulation, reflects the transformer aging condition and can be used to estimate the useful remnant life of the asset. Unfortunately, continuous aging process of power transformer insulation system cannot be avoided due to the severe operating conditions that a transformer is operating on. So, it is very important to regularly monitor the condition of power transformer insulation to maintain its reliability. Historical data of transformer insulations are very substantial to define the history of power transformer health condition. This paper introduces two methods, first one to assess the degradation rate of power transformers insulation, and then estimate the insulation condition index based on historical data. © 2019 IEEE.

Affiliations

Institut Teknologi Bandung, PT. PLN (Persero), School of Electrical Engineering and Informatics, Jakarta, Indonesia; State Polytechnic of Malang, School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Department of Electrical Engineering, Bandung, Indonesia; Institut Teknologi Bandung, School of Electrical Engineering and Informatics, Bandung, Indonesia; Curtin University, School of Electrical Engineering Computer and Mathematical Science, Perth, WA, Australia

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