Construction of transformer core model for frequency response analysis with genetic Algorithm

This paper presents a novel model-based identification approach to determining laminated core parameters of power transformers on the basis of frequency response analysis (FRA) measurements. A genetic algorithm is employed for parameter identification of a transformer core model, established using the duality principle between magnetic and electrical circuits. A well-known lumped parameter model of a 3-phase transformer is used to simulate reference input impedance frequency responses for analyzing the identification accuracy of the proposed approach. It is suggested that the approach can be applied for transformer core modeling and FRA result interpretation at low frequencies.