Abstract
The study of the degradation of power transformers in the electrical network has become a subject of relevant analysis by network operators and companies, associated with the probability of failures and operation quality. For this reason this paper firstly presents the classification of a set of 12 Asset Management models related to power transformers monitoring and, then, the application of three of them in three substations of the National Laboratory of Smart Grids (LAB+i) located at Bogot´a Campus of the Universidad Nacional de Colombia. As a result, the main challenges were identified concerning the Asset Management application in transformer fleets related to data availability and precision. Finally, it was identified that the development of an Asset Management model that uses non-invasive real-time measurements is needed for continuous monitoring of power systems and diagnosis.
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