Cast-resin dry-type transformer thermal modeling based on particle swarm optimization

Abstract

In this research paper, a novel approach for dynamic thermal modeling of cast-resin dry-type transformer is introduced. In order to analyze the dynamic behavior of the temperatures in this type of transformer, a new thermal model has been introduced which is based on the particle swarm optimization (PSO) algorithm. Selecting a typical 400 kVA dry-type transformer, the models parameters have been estimated (by employing the PSO) and validated using the experimental data. The PSO is used to estimate the models parameters with a good performance. The estimated second-order model describes the thermal behavior of the cast-resin transformer completely. Using this model, dynamic thermal behavior of the transformer has been analyzed and the effects of load variation on thermal behavior of transformer have been discussed in this paper. It has been shown that the newly introduced thermal model that is estimated using the PSO is an accurate and efficient model for analyzing the dynamic thermal behavior of the cast-resin dry-type transformer.