Estimation of Conductivity at Reduced Time for Sensing Moisture Content of Oil-Paper Insulation

Abstract

Conductivity is an important parameter which has definite correlation with the amount of moisture present within the transformer insulation. However, in existing methods conductivity is usually estimated from time domain (PDC) measurement, which is inadvertently noise prone and time consuming. Considering this issue, in this article presents a novel technique for conductivity estimation for moisture sensing of oil-paper insulation using frequency domain spectroscopy measurement (FDS). To this end, FDS measurement of oil-paper insulation was performed from 50mHz to 1kHz to obtain the imaginary complex permittivity $\varepsilon ''$ ( $\omega$ ), which is a function of conductivity ( $\sigma$ ) as well as imaginary complex susceptibility $\chi ''$ ( $\omega$ ). From the knowledge of frequency variation of both $\sigma $ and $\chi ''$ ( $\omega$ ), we developed an electrical equivalent model of the insulation. The equivalent model parameters were optimized until $\varepsilon ''$ ( $\omega$ ) computed from the proposed model and that obtained from original FDS measurement were almost identical. The conductivity values obtained from the equivalent model showed good agreement when compared with PDC measurement. To validate the practicability of the proposed method, experiments were conducted on various test samples and also on a few real life transformers. Most importantly, the measurement time was found to be reduced by 78.5%, enabling diagnosis of transformer insulation at a significantly reduced time.