Abstract
In this paper, the hysteresis characteristics of a transformer core are determined from limited on-line measured voltages and currents under certain excitations. A method for calculating the magnetization curve and hysteresis loops of the transformer core under various excitation is developed based on limited excitation conditions, and using the deep neural network, support vector regressor and the Wlodarski model. The coercivity and the amplitude of magnetic field strength of hysteresis loops can be captured with high accuracy based on this method. Then, a finite element model of the transformer core is constructed to predict the distributed magnetic flux density and the excitation current using the calculated hysteresis loops. The currents from various excitation voltages on two different transformer structures are also measured to compared with simulated currents. The outcome indicates that the overall hysteresis loops and magnetization curve of the transformer core may be useful for modeling the magnetic field and excitation current under any voltage excitation.
Highlights
Transformer noise has become a pressing environmental issue as population growth and energy demand increasingly result in transformer stations being in close proximity to residential areas
We propose to use the on-line measured voltage and current collected from operating transformers and feed them into deep neural network (DNN) [19] and support vector regressor (SVR) [20] to obtain the overall magnetization curve and hysteresis loops of transformer cores under any excitation
The magnetization curve was modeled by a deep neural network with 99.95% correlation coefficient and the coercivity and amplitude of magnetic field strength were modeled by a support vector regressor with 96% and 97% correlation coefficients
Summary
Transformer noise has become a pressing environmental issue as population growth and energy demand increasingly result in transformer stations being in close proximity to residential areas. Accurate prediction of the magnetic field in a transformer is a difficult task due to the complicated assembly, boundary conditions, and nonlinear properties of the material [1]. The latter resulting from the nonlinear relationship between magnetic field strength (H) and magnetic flux density (B) within the ferromagnetic core. This nonlinear relationship is described by the magnetization curve and magnetic hysteresis loops and can be measured under material aspect [2,3,4] or by considering the equivalent circuit of entire equipments [5,6,7,8,9]. The Preisach model is relatively complicated to implement for practical application and the Jiles–Atherton model requires five key parameters which are not easy to be determined [14]
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