Análises multifísica via método de elementos finitos para o auxílio à manutenção preditiva em transformadores de potência. - SOUSA, Antonio Roniel Marques de (Universidade Federal do Pará, 2018)
The National Interconnected System (NIS) is an organ of fundamental importance in the Brazilian panorama. Its function is to electrically connect generating centers and consumer centers, whether they are business, commercial or residential. The main equipment responsible for the connection and transmission of electric power from the generating centers to the consumers are the power transformers. This equipment is subject to several types of faults that can affect its components, in some cases compromising the operation of this equipment, and consequently the supply of electric energy. In this work, a multiphysical analysis is performed on power transformers, coupling thermal and structural electromagnetic simulations with the objective of providing the operator with information about the ideal moment for performing predictive maintenance, avoiding unplanned shutdowns. For this, computational simulations using the Finite Element Method (FEM) were used and from this, we analyzed the different situations that these equipments can be submitted, in the nominal condition, as well as extreme conditions of operation like current of inrush and current short-circuit. In this perspective, analyzes of the effects that the thermal expansion and the axial forces and radia exerted contributing to possible defects in these equipments were carried out. As a study object, the simulations were performed in a 50 MVA single-phase transformer, which is an equipment that is in operation in the northern region of the country. For a more validation of the methodology used in this work the simulations were validated with real measurement data and with results present in current literature. In this way, this work presents a methodology that can help the technical framework of an industry in the decision of the appropriate moment of stop in a power transformer for the accomplishment of predictive maintenance.