Predicción de la temperatura de un transformador de distribución para centros de transformación tipo interior y subterráneos

Abstract

Distribution transformers in the transformation

centres, which produce thermal losses, are

closely linked with their correct proper

operation, maintenance and life of these

transformers. In a practical way it would be

useful to estimate the temperature of the

transformer from easily measurable data such as

its outside temperature, the ground temperature

(in underground transformers) and the power

supplied by the transformer.

The aim of this research is to model the

behaviour of a transformer (either inside or

underground transformer) in order to predict

the temperature of the transformer, to optimize

operating system installation and to extend the

life of the machine.

The methods proposed in this study for such a

model are artificial neural networks (RNA) and

least squares polynomial regressions (RP). There

were used three transformation centres for data

collection.