, Volume 26, Issue 6, pp 3891–3908 | Cite as

Aging condition assessment of transformer oil-immersed cellulosic insulation based upon the average activation energy method

  • J. Liu
  • X. Fan
  • H. ZhengEmail author
  • Y. Zhang
  • C. Zhang
  • B. Lai
  • J. Wang
  • G. Ren
  • E. Zhang
Original Research


It is widely accepted that the service life of transformer oil–paper insulation is determined by the aging condition of transformer cellulosic insulation. Therefore, it is rather meaningful to accurately and reliably evaluate the aging condition of transformer cellulose insulation. Existing studies have shown that activation energy can eliminate the temperature effect on the frequency dielectric spectroscopy, however, the traditional activation energy might not be suitable for assessing the aging condition of transformer cellulosic insulation. The aim of the work is to assess the aging condition of cellulosic insulation by using average activation energy technique. The experiment process is firstly discussed. Then, the second-order dynamic equation formed by Arrhenius equation and Ekenstam equation is strictly investigated to accurately calculate the degree of polymerization value of transformer cellulosic insulation. The experimental results preliminarily show that the average activation energy can effectively assess aging condition of transformer cellulosic insulation.

Graphical abstract


Cellulosic insulation Arrhenius equation Ekenstam equation Ageing condition assessment Average activation energy 



The authors acknowledge the National Natural Science Foundation of China (61473272; 51867003), the Natural Science Foundation of Guangxi (2018JJB160056; 2018JJB160064; 2018JJA160176). J.L., H.Z. and Y.Z. designed the algorithms and performed the writing, and they contributed equally to this work; H.Z. and Y.Z. are both corresponding authors; X.F., C.Z., B.L., J.W., G.R., and E.Z. analyzed the data; all authors have approved the submitted manuscript. The authors also thank the anonymous reviewers and the editor for their valuable comments.


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© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Guangxi Key Laboratory of Power System Optimization and Energy TechnologyGuangxi UniversityNanningChina

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