Evaluation of the Cole-Cole Model for Oil-Paper Insulation in Extreme Cold Environments Via Dielectric Response and Parameter Optimization

Dielectric performance of oil paper insulation would significantly deteriorate under severe cold environments, leading to deviations in traditional frequency-dependent dielectric models. To assess the applicability of the widely used dielectric model under extreme low-temperature conditions. This study investigates the Cole-Cole model's accuracy in describing the dielectric response of oil-paper insulation exposed to subzero temperatures. Frequency Domain Spectroscopy (FDS) measurements were conducted under varying cold conditions to analyze deviations from standard dielectric behavior. The study further explores relaxation parameter extraction, focusing on key factors such as dielectric dispersion, conductivity, and polarization effects at ultra-low temperatures. To enhance predictive accuracy, an optimized parameter estimation approach is proposed, integrating genetic optimization algorithms and modified Cole-Cole modeling techniques. The results indicate that as temperature decreases, the traditional Cole-Cole model exhibits noticeable deviations, necessitating temperature-dependent modifications and fails to satisfy at critical low temperatures. The findings provide critical insights into improving high-voltage insulation reliability in Arctic environments, space applications, and cryogenic power systems. Furthermore, it can optimize insulation materials for enhanced performance in harsh climates, thereby ensuring improved operational stability and longevity of electrical infrastructure.