2013 Annual Report Conference on Electrical Insulation and Dielectric Phenomena, 2013
ABSTRACT Defects such as cracks and voids in the insulation medium of a power transformer may aff... more ABSTRACT Defects such as cracks and voids in the insulation medium of a power transformer may affect the dielectric response of transformer insulation system. This paper uses the finite element method (FEM) to analysis the influence of electric field distribution on the dielectric response of transformer oil-paper insulation system. Firstly a simple transformer winding insulation model consisting of several layers of pressboard and oil ducts is established in FEM. Here, two circumstances are taken into consideration to represent normal insulation and insulation with cracks penetrating all the layers. The complex capacitance (real part and imaginary part) is calculated to obtain general tendency of dielectric response of winding insulation in a transformer. Secondly, this paper proposes FEM model of a three phase oil-immersed power transformer insulation system. Based on the developed model, the dependency between electric field displacement, current density at the selected point with the applied electric field is discussed in detail. Moreover, the complex capacitance of transformer insulation is also studied. This will help to understand the correlations among insulation defects, electric field variations, and dielectric response of insulation.
2011 21st Australasian Universities Power Engineering Conference Aupec 2011, 2011
Power transformers are one of the most critical equipments in electricity network. A number of te... more Power transformers are one of the most critical equipments in electricity network. A number of techniques such as dissolved gas analysis (DGA), polarization and depolarization currents (PDC) measurement and frequency domain spectroscopy (FDS) have been adopted across utilities for transformer insulation diagnosis. However, there are still considerable challenges remaining in interpreting measured data of these techniques. This paper develops machine learning algorithms, which utilise archived data for making insulation diagnosis on the transformer of interest. Analysis and interpretation of field test data are presented in the paper.
2013 Annual Report Conference on Electrical Insulation and Dielectric Phenomena, 2013
ABSTRACT Defects such as cracks and voids in the insulation medium of a power transformer may aff... more ABSTRACT Defects such as cracks and voids in the insulation medium of a power transformer may affect the dielectric response of transformer insulation system. This paper uses the finite element method (FEM) to analysis the influence of electric field distribution on the dielectric response of transformer oil-paper insulation system. Firstly a simple transformer winding insulation model consisting of several layers of pressboard and oil ducts is established in FEM. Here, two circumstances are taken into consideration to represent normal insulation and insulation with cracks penetrating all the layers. The complex capacitance (real part and imaginary part) is calculated to obtain general tendency of dielectric response of winding insulation in a transformer. Secondly, this paper proposes FEM model of a three phase oil-immersed power transformer insulation system. Based on the developed model, the dependency between electric field displacement, current density at the selected point with the applied electric field is discussed in detail. Moreover, the complex capacitance of transformer insulation is also studied. This will help to understand the correlations among insulation defects, electric field variations, and dielectric response of insulation.
2011 21st Australasian Universities Power Engineering Conference Aupec 2011, 2011
Power transformers are one of the most critical equipments in electricity network. A number of te... more Power transformers are one of the most critical equipments in electricity network. A number of techniques such as dissolved gas analysis (DGA), polarization and depolarization currents (PDC) measurement and frequency domain spectroscopy (FDS) have been adopted across utilities for transformer insulation diagnosis. However, there are still considerable challenges remaining in interpreting measured data of these techniques. This paper develops machine learning algorithms, which utilise archived data for making insulation diagnosis on the transformer of interest. Analysis and interpretation of field test data are presented in the paper.
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