Dielectric spectroscopy (FDS) is widely used to assess the condition of transformer oil-paper insulation systems. Typically the frequency dependent complex capacitance CHL between the high- and low-voltage windings is measured. This capacitance can be modeled analytically using simple RC-equivalent circuits, due to the homogenous electrical field distribution in the main insulation duct (XY or Pancake-model) [2]. A curve fitting of this model to the measured data enables extraction of dielectric parameters like oil conductivity and moisture content in pressboard. Apart from CHL it is also possible to measure the complex capacitance between HV windings and tank (CH) where we also have an oil-paper insulation system. The corresponding measurement data can't however be fitted to the conventional Pancake-model, because of the inhomogeneous field distribution between HV windings and tank. Hence a Finite Elements Analysis (FEA) based model which describes the dielectric behavior of the transformers isolation system between HV windings and tank was developed in this paper. This numerical model was combined with an optimization algorithm to determine the unknown dielectric parameters from dielectric spectroscopy data for CH. FDS measurements of CH and CHL from three power transformers were analyzed by the use of the conventional Pancake-model for CHL and the new FEA-model for CH. The results showed good agreement in dielectric parameters of oil and pressboard what leads to a strong verification of dielectric diagnosis results for a transformer by two independent models and measurements.
[1]
J. H. Yew,et al.
Influence of the geometrical parameters of power transformer insulation on the frequency domain spectroscopy measurement
,
2008,
2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century.
[2]
L. Fahrmeir,et al.
Regression - Modelle, Methoden und Anwendungen
,
2009
.
[3]
Laverne W. Stanton,et al.
Applied Regression Analysis: A Research Tool
,
1990
.
[4]
A. Christopoulos,et al.
Fitting Models to Biological Data Using Linear and Nonlinear Regression: A Practical Guide to Curve Fitting
,
2004
.
[5]
J. O. Rawlings,et al.
Applied Regression Analysis
,
1998
.
[6]
J. O. Rawlings,et al.
Applied Regression Analysis: A Research Tool
,
1988
.