Linking Dielectric Response with Transformer Moisture Content Through Vector Fitting Analysis and Havriliak–Negami Model

This paper presents a method for estimating moisture content (%MC) in power transformers. It primarily relies on the analysis of the statistical properties of relaxation times characterizing the dielectric frequency response (DFR), which is fitted as a sum of rational functions using the Vector Fitting (VF) tool. The DFR is modeled as a sum of Debye terms (accounting for materials exhibiting different relaxation times due to multiple polarization processes) characterized by poles and residues provided by VF. These parameters are then used to derive statistical factors that correlate with the shape of the dielectric response curve in the context of the Havriliak–Negami (HN) model, which is known for its effectiveness in characterizing materials with multiple relaxation times. By correlating the statistical factors with the HN model parameters, substantial insights into the insulation condition can be achieved. A moisture index (MI) is proposed from these parameters, which, when combined with conductivity, allows for accurate %MC estimation in the solid insulation system (cellulose). The combined MI and conductivity capture combined effects on moisture behavior, addressing both conductivity and polarization losses at different frequencies. The proposed method provides an efficient and straightforward non-invasive approach to insulation assessment without complex optimization algorithms. Experimental work on transformers at varying moisture levels provides validation of the proposed approach and demonstrates strong correlation with industry standards. The results confirm its reliability for moisture evaluation in transformer monitoring.