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Determination of Dielectric Models Based on Effective Multi-Exponential Fittings

Author(s)
Raxsa, Jedsada
Nimsanong, Phethai
Mai-Eiam, Thanatorn
Yutthagowith, Peerawut
Date Issued
June 1, 2023
Type
Article
DOI
10.3390/en16124615
Abstract
In high-voltage (HV) transmission and distribution systems, HV apparatuses are subjected to electrical, thermal, and mechanical stresses that deteriorate the insulation performance. The polarization and depolarization current (PDC) measurement is an effective tool used for evaluating insulation performances. The depolarization current represented by the summation of the discharge currents with the different time constants can be utilized for the development of the dielectric model based on the extended Debye’s model (EDM). This paper presents effective techniques for determining the dielectric model. Iterative approaches with predetermination of the time constants and least squares methods (either linear ordinary or percentage ones) were utilized to fit the depolarization current in the form of multi-exponential functions. The fitting parameters determined by the proposed method with the linear ordinary least squares (OLLS) method and provided by commercial software agree very well only in the high current and beginning range. Application of the linear percentage least squares (PLLS) method shows better accuracy than that of the OLLS method, and the deviation from the measured one in the low current range and the late measuring time were reduced significantly. The fitted current by this proposed technique with the PLLS method agrees well with the measured current throughout the whole recording time, even in the low current and late time range. From the accurately fitted currents, the dielectric model and the dielectric loss factors can be determined precisely, and the insulation condition of HV equipment can be evaluated properly.
Citation
Energies, 16(12), 2023
Subjects

dielectric loss facto...

extended Debye’s mode...

multi-exponential fun...

PDC measurement

percentage least squa...

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