A Computational Model for Aging Dependability in Polymeric Cable Insulation

This paper proposes a method to analyze aging response variance in terms of statistical parameters and geometry specifications of medium voltage power cable. The electric stress distribution in the single-core medium voltage power cable model is logged quantitatively using finite element modeling. The dependable parameters such as electrical conductivity, thermal conductivity, ambient temperature, relative permittivity, defect position and size, act as variables in the model to analyze simulated electric stress in the power cable. The variation in electrical stress distribution under the influence of different factors impact distinctly on cable degradation over time. Moreover, the correlation between these factors is quantified using derived statistical parameters to form a correlation matrix. In this work, both the variation coefficients and mean stress intensity are utilized as response measurement variables. A multivariable linear regression is applied to derive the relationship between the model parameters and the response variables. This study shows that the stress variation is strongly correlated with electrical conductivity and thermal conductivity, while the maximum stress intensity is most impact by defect sizes and position. The implication and consequence of the rest of the model parameters on electric stress distribution are also analyzed and discussed.