Uma contribuição para gestão de vida útil de transformadores de potência via manutenção preditiva de óleo isolante

Abstract

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.