环保绝缘气体介电强度预测方法评估

doi:10.19595/j.cnki.1000-6753.tces.L10011

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Abstract SF₆ has a strong greenhouse effect, with a global warming potential (GWP) of 23 500. It needed to be alternated urgently. Gas dielectric strength prediction methods could quickly give the dielectric strength based on molecular parameters. The existing prediction methods are various. They use different parameters and discharge theories. The fitting samples they used were from different test conditions. That would lead to uniform dielectric strengths for the same gas in each perdition method. This paper evaluated the existing prediction methods to clarify the impact of the abovementioned factors on accuracy and reliability.
According to the parameters and model forms, five prediction methods with typical characteristics were selected. Method 1 used linear models of molecular polarization characteristics and ionization, adsorption energy, and other parameters. Method 2 added molecular geometric characteristics. Method 3 was based on the method 2 adding molecular symmetry factors, and the model is no linearized considering the discharge theory. Method 4 was a linear model using general interaction properties function (GIPF) parameters. Method 5 was the group contribution method. Nine frequently occurring gases (N₂, CO₂, N₂O, CF₄, SO₂F₂, c-C₄F₈, C₃F₈, C₅F₁₀O, and C₄F₇N) were selected to evaluate the prediction method. The relative dielectric strengths of nine gases relative to SF₆ were tested under the same conditions (50 Hz alternative current uniform electric field).
The results show that the prediction accuracy of each method was lower than the fitting results given in their papers. That was because the test conditions of the gases used in each prediction method were not uniform, and the relative dielectric strength of the gases used was inconsistent. Some gases' dielectric strength had significant difference with the test data in this paper. The unification of gas dielectric strength based the test results in this paper could improve the accuracy of methods and the predication results of 5 methods could be consistent with their fitting results. In addition, with the enrichment of molecular parameters and the intervention of discharge theory, the prediction accuracy of methods 1 to 4 gradually increased. In addition, method 3, validated by the out-of-sample data, had high accuracy before and after the unification. Method 5, using the group contribution, also had the above properties. However, the groups method 5 could predict was limited. Hence, the method 5 could not predict all of 9 gases' dielectric strength.
From the above evaluation results, it could be found that the gas data in the samples for fitting prediction models should be obtained under the same test conditions (electrode, electric field, voltage form, pressure, temperature, gap, et al). In addition, it is necessary to determine the applicable conditions and objects of the prediction method according to the sample data's test conditions and molecular characteristics. Towards the same sample, introducing the discharge theory, molecular geometric features, and new molecular parameters could help improve the accuracy of the prediction model. In addition, using out-of-sample data to validate the model and introducing the group contribution method could improve the inclusiveness of the prediction method for the sample data.

Key words： Eco-friendly insulation gases dielectric strength prediction quantitative structure-property relationships (QSPR) gas insulated transmission lines (GIL)

Received: 13 January 2023 Published: 09 November 2023

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	Zhou Wenjun
	Qiu Rui
	Zheng Yu
	Pascal Brault

Cite this article:

Zhou Wenjun,Qiu Rui,Zheng Yu等. The Evaluation of Dielectric Strength Prediction Methods for Eco-Friendly Insulation Gases[J]. Transactions of China Electrotechnical Society, 2023, 38(zk1): 214-221.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.L10011 OR https://dgjsxb.ces-transaction.com/EN/Y2023/V38/Izk1/214

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