An Improved IPM for Life Estimation of XLPE Under DC Stress Accounting for Space-Charge Effects

Inverse power model (IPM) is often used in the engineering field to estimate the electrical life of cross-linked polyethylene (XLPE) cable insulation and describe the relationship between applied voltage and insulation failure time. The voltage tolerance index n in IPM is also used as an important f...

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Bibliographic Details
Main Authors: Zhipeng Ma, Lijun Yang, Haoran Bian, Muhammad Shoaib Bhutta, Pengfei Xu
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8863335/
Description
Summary:Inverse power model (IPM) is often used in the engineering field to estimate the electrical life of cross-linked polyethylene (XLPE) cable insulation and describe the relationship between applied voltage and insulation failure time. The voltage tolerance index n in IPM is also used as an important factor to select appropriate AC cable thickness and pre-evaluation test voltage. However, under the influence of DC electric field, space charge accumulation changes the internal field strength of XLPE. As a result, the actual electric field strength is quite different from the applied value. Hence, the existing IPM model exhibits a large error in evaluating the electrical life of DC cables. In this paper, an improved IPM is proposed. The correction parameters &#x03B1; and &#x03B2; are introduced into the cumulative loss parameter C and voltage tolerance index n of the existing IPM to quantify the effect of space charge on distorting the electric field in electrical insulation life. Correlation between applied field strength (E<sub>a</sub>), maximum endurance field strength (E<sub>rm</sub>) and insulation failure time t of several XLPE with different thicknesses is obtained from DC voltage withstand test and pulsed electro acoustic test. In addition, the validity of the improved IPM is preliminarily verified. &#x03B1; and &#x03B2; predicted by using the space charge characteristic parameter matrix [P] is proposed to efficiently obtain the actual parameters. According to experimental analysis, the improved IPM with a certain thickness is predicted by using the neural network fitting method.
ISSN:2169-3536