Adsorption of dissolved gas molecules in the transformer oil on silver-modified (002) planes of molybdenum diselenide monolayer: A DFT study

Dissolved gas analysis (DGA) of transformer oil has been one of the most reliable techniques to detect the incipient faults. Many conventional DGA methods have been developed to interpret DGA results obtained from gas chromatography. Although these methods are widely used in the world, they sometimes fail to diagnose, especially when DGA results fall outside conventional methods codes or when more than one fault exist in the transformer. To overcome these limitations, the fuzzy inference system (FIS) is proposed. Two hundred different cases are used to test the accuracy of various DGA methods in interpreting the transformer condition.

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Research and Application of Standard Oil Dispensing System for Dissolved Gases in Transformer Oil

Journal of Physics Conference Series ◽

10.1088/1742-6596/2125/1/012072 ◽

2021 ◽

Vol 2125 (1) ◽

pp. 012072

Author(s):

Yanping Li ◽

Yong Li

Keyword(s):

Electrical Equipment ◽

Transformer Oil ◽

Work Skills ◽

Dissolved Gas ◽

On Line ◽

Important Means ◽

Grid Operators ◽

Oil Gas ◽

Internal Potential ◽

Gas Component

Abstract Measuring the content of dissolved gas components in transformer insulating oil by gas chromatography is an important means to judge the internal potential faults of oil filled electrical equipment in the process of operation supervision. The necessary work skills of power grid operators include the ability to detect the content of dissolved gas in transformer oil and judge the operation state of transformer. This paper introduces a preparation method and equipment of transformer standard oil. It can quickly prepare standard oils with various gas component contents. The standard oil quantity value is accurate, the data stability period is greater than 90 days, and the uncertainty is less than 5%. The equipment can be used for training and evaluation of transformer oil gas chromatographic analysis practitioners and calibration of transformer oil on-line gas chromatograph.

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Adsorption and optical properties of H2S, CH4, NO, and SO2 gas molecules on arsenene: a DFT study

Journal of Computational Electronics ◽

10.1007/s10825-020-01565-8 ◽

2020 ◽

Vol 19 (4) ◽

pp. 1373-1379

Author(s):

Arshiya Abooali ◽

Fatemeh Safari

Keyword(s):

Optical Properties ◽

Dft Study ◽

Gas Molecules ◽

So2 Gas

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Estimation of dissolved gas concentrations in transformer oil from membranes

IEEE Electrical Insulation Magazine ◽

10.1109/mei.2011.5739420 ◽

2011 ◽

Vol 27 (2) ◽

pp. 30-33 ◽

Cited By ~ 7

Author(s):

Yangliu Li ◽

Xuezeng Zhao

Keyword(s):

Transformer Oil ◽

Dissolved Gas

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Parallelization Analysis of Dissolved Gases in Transformer Oil Based on Random Forest Algorithm

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.519-520.98 ◽

2014 ◽

Vol 519-520 ◽

pp. 98-101

Author(s):

De Wen Wang ◽

Zhi Wei Sun

Keyword(s):

Fault Diagnosis ◽

Random Forest ◽

Power Transformer ◽

Gas Analysis ◽

Transformer Oil ◽

Dissolved Gases ◽

Random Forest Algorithm ◽

Dissolved Gas ◽

Important Method ◽

Transformer Fault

Dissolved gas analysis (DGA) in oil is an important method for transformer fault diagnosis. This paper use random forest parallelization algorithm to analysis the dissolved gases in transformer oil. This method can achieve a fast parallel fault diagnosis for power equipment. Experimental results of the diagnosis of parallelization of random forest algorithm with DGA samples show that this algorithm not only can improve the accuracy of fault diagnosis, and more appropriate for dealing with huge amounts of data, but also can meet the smart grid requirements for fast fault diagnosis for power transformer. And this result also verifies the feasibility and effectiveness of the algorithm.

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