Contents I. Introduction
Transformers, potential transformers, and other iron core components, as critical devices in power systems, exhibit nonlinear properties including excitation saturation and hysteresis. These characteristics significantly influence their transmission and transformation behaviors [1]. Under certain conditions, iron core devices can trigger phenomena like inrush currents, DC bias, and ferromagnetic resonance, posing safety risks to power systems [2]–[4]. Thus, modeling and simulating ferromagnetic components with nonlinear characteristics has garnered widespread attention from researchers globally. The saturation, hysteresis, and dynamic losses of ferromagnetic materials are key factors influencing low-frequency electromagnetic transients in the iron core components. The precision of core hysteresis models directly affects the accuracy of power system electromagnetic transient simulations. Current models often use single-valued magnetization curves to approximate nonlinearities, but this could introduce significant errors. Furthermore, core losses, critical for electromagnetic energy conversion, are typically modeled with constant or nonlinear resistances, ignoring their dynamic variation with excitation voltage [5]. Neglecting both static and dynamic losses could lead to substantial errors in simulating steady-state and transient overvoltage and overcurrent [6].
