Fractal Analysis of Time Domain Dielectric Response to Reduce Complexity of Insulation Condition Diagnosis Methodology

Abstract

The health of cellulosic insulation, present in a power transformer, continuously degrades due to its exposure to paper moisture and high temperature. The moisture content of such insulation further accelerates the ageing phenomena. Recent developments made in the field of power transformer insulation diagnosis show that condition-based maintenance of power transformers is more important rather than time-based maintenance. On the other hand, utilities always prefer to monitor the condition of power transformers in short measurement time. The present work proposes a fractal analysis-based condition monitoring technique. The method utilizes only a 600 s measured profile of polarization current. This paper estimates various ageing-sensitive performance parameters evaluated from fractal features for insulation diagnosis. The suggested technique can be used in a non-intrusive way to estimate performance measures such as %pm and paper conductivity. With the least amount of shutdown time, this technique quickly assesses the insulating state of power transformers. This strategy has shown to be more successful than existing approaches for monitoring insulation status.