Power transformers are the most mandatory and most costly equipment in a power substation.
The reliability of this equipment is essential for the transmission and distribution businesses
from a financial and strategic point of view and, indirectly, for important sectors in the country's
development, such as trade, agribusiness and industry. Predictive maintenance aims to monitor
or observe the status of transformers through preventive diagnosis. Through the refinement of
these maintenance techniques, it is possible to reduce costs with replacements, maintenance,
avoid penalties for regulators for not complying with quality indices, avoid failures, ensure
greater reliability and availability, avoid unnecessary risks and extend the life of the equipment.
. With this, this work explores the different predictive maintenance techniques that involve
insulating oil, correlates the predictive maintenance data through a case study in an energy
distributor, stipulates criteria for diagnosing transformers based on the bibliography and
presents the use of the tool Power BI as a contribution to asset management, maintenance
planning, carrying out a contingency plan, logistics, strategy and equipment preservation.
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