# Determination of dielelctric model parameters from the results of voltage response measurement

OData: XML JSON What's this?Continuous energy production is required to satisfy the electricity need of consumers. Since today's electricity storage is based on small-scale and non-mature technologies. Both public and industrial customers are served on high-value electrical transmission and distribution grids. Malfunctions on grids can cause significant financial loss, thereofre continuous system diagnostic is an important task. Therefore, the main aim of my work is to support the insulation diagnostics by determination of the equivalent circuit of insulation based on the voltage response measurement. The algorithm, which provides the parameters of the insulation model, was developed in MatLAB software environment. The equivalent circuit illustrates the dielectric processes in the insulation namely the conduction and the polarization. With the change of dielectric processes, the two most important deterioration processes of the insulation are aging and moistening.

The measurement data includes the return voltage response of the given discharge time and the geometry capacity of transformer which were the input data of the program. The MatLAB code finds the optimum for the R-C parameters and their values based on the voltage response method which represent polarization processes with different time constants. The target function was the smallest square of the difference between the measured and the calculated value of voltage response. Another aim of the optimization is to model of the insulation with the smallest number of R-C parameters. This determines which R-C terms do not significantly contribute to the measured return voltage response.

The validation of the program was carried out by test circuit with different numbers of given R-C branches. The return voltages were also determined by measured and calculated at given discharge times which provide the initial conditions for the program and the known R-C pairs constituted the boundary conditions. The program optimized these R and C values with a few percent error, so the algorithm is proved. The graphical user interface provides easier handling, with many other benefits. The interface able to read the voltage response data from Excel files so the isolation of substitute model can easily be evaluated. The result of the optimization becomes visible to user and it is possible to save the optimized results for further data processing. The functions of program also include a diagnostic-relevant capacity-time constant diagram which is outstanding relevant for diagnostic, the number of R-C members, their optimized values, and the comparison of the models of different insulating materials.

Overall, developing a model with user-friendly interface can greatly facilitate the simpler diagnosis of insulation of transformer for professionals which can be used to predict failure, so decreasing number of malfunctions can be predicted for the future.