Improved Modeling of Power Transformer Winding Using PSO

The paper discusses an improved modeling of transformer windings based on particle swarm optimization algorithm (PSO) and frequency response analysis (FRA). With the purpose to accurately identify transformer windings parameters a model-based identification approach is introduced using a well-known lumped parameter model. It includes search space estimation using analytical calculations, which is used for the subsequent model parameters identification with a novel PSO. The newly introduced PSO, being developed upon a bacterial foraging behavior, is described in detail. Simulations and discussions are presented to explore the potential of the proposed approach using simulated and experimentally measured FRA responses taken from two transformers. The PSO identification results are compared with those using genetic algorithm. It is shown that the proposed PSO delivers satisfactory parameter identification and improved modeling can be used for FRA results interpretation.