access icon free Improved low-frequency transformer model based on Jiles–Atherton hysteresis theory

Transformers are the most widely used apparatus in power systems to transfer electrical energy from one side to another. Despite remarkable achievements in transformer modelling over the past few years, three-phase transformer modelling techniques have not progressed to that of their single-phase counterparts, mainly because of topological correctness of core and coil structure, complicated interaction between fluxes of the three iron core legs, and non-linear saturation of ferromagnetic material. An improved three-phase transformer model with extended inverse Jiles–Atherton (JA) hysteresis theory is proposed in this study. The extended inverse JA model with anisotropic anhysteretic magnetisation function is addressed, and the classical eddy-current-loss term and anomalous-loss term are directly incorporated into the original energy balance equation to represent the non-linearity and iron core losses rather than representing them with a parallel combination of resistances and saturable inductances (R//L model) as most previous studies have done. The results of inrush current case indicate that the proposed transformer model can predict the residual flux, include eddy-current-loss and anomalous-loss, and predict the inrush current peak values with relative error less than 6%.

Inspec keywords: transformer cores; ferromagnetic materials; coils; eddy current losses

Other keywords: iron core losses; electrical energy transfer; improved low-frequency transformer model; anomalous-loss; inrush current; anisotropic anhysteretic magnetisation function; nonlinear saturation; JA hysteresis theory; extended inverse JA model; coil structure; residual flux; iron core legs; original energy balance equation; three-phase transformer modelling technique; core structure; Jiles-Atherton hysteresis theory; ferromagnetic material; eddy-current-loss

Subjects: Magnetic cores; Ferromagnetic materials; Inductors and transformers

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http://iet.metastore.ingenta.com/content/journals/10.1049/iet-gtd.2016.0866
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