Back to Search Start Over

Investigation on Molecular Dynamics Simulation for Predicting Kinematic Viscosity of Natural Ester Insulating Oil.

Authors :
Zheng, Hanbo
Feng, Yongji
Li, Xufan
Yang, Hang
Lv, Weijie
Li, Songjiang
Source :
IEEE Transactions on Dielectrics & Electrical Insulation. Oct2022, Vol. 29 Issue 5, p1882-1888. 7p.
Publication Year :
2022

Abstract

Natural ester insulating oil not only has a biodegradation rate of almost 100% but also meets the carbon emission requirements of China’s “Carbon Peak and Carbon Neutrality” and the “European Green Deal” proposed by the European Union. It is considered to be a good substitute for mineral insulating oil. However, due to its higher kinematic viscosity than traditional mineral oil in low-temperature environments, it limits the safety promotion and application of transformers in cold regions. First, we design an experiment to test the kinematic viscosity and density of natural ester insulating oil. Under extremely harsh experimental conditions, we measure key experimental data such as kinematic viscosity. Second, the structure of the four main triglyceride molecules is optimized, and the molecular dynamics (MD) simulation technology is used to establish an MD model that can predict the kinematic viscosity of natural ester insulating oil (−20 °C to 20 °C). Finally, the model is further simplified by the free volume theory to better predict the kinematic viscosity of natural ester insulating oil. This study makes up for the lack of laboratory low-temperature testing of the kinematic viscosity of natural ester insulating oil and provides a convenient and reliable tool for predicting the kinematic viscosity of natural ester insulating oil. It can not only predict the natural ester insulating oil mixed in various proportions but also predict the kinematic viscosity of a certain natural ester molecule. Furthermore, it also provides a guiding direction for the improvement of low-temperature kinematic viscosity of natural ester insulating oil, as well as a strong reference for predicting other properties of other substances. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10709878
Volume :
29
Issue :
5
Database :
Academic Search Index
Journal :
IEEE Transactions on Dielectrics & Electrical Insulation
Publication Type :
Academic Journal
Accession number :
160691498
Full Text :
https://doi.org/10.1109/TDEI.2022.3198763