Study of Parameters Affecting the Aging of Transformer Oil

2022 ◽  
Vol 1048 ◽  
pp. 89-100
Author(s):  
S. Tamil Selvi ◽  
Madhusudan Saranathan ◽  
Pa Hari Krishna Achuthan ◽  
R. Abhishek ◽  
Adhitya Ravi

An electricity board acquires several transformers from a manufacturer in a belief that their advertised lifetime of the transformer thus purchased is true. However, they don’t take in the case of negligence in maintenance of transformer, which is a strenuous job. The advertised thirty-year lifetime is reduced to a mere two-year lifetime, mainly because of the degradation of the insulation medium (Transformer oil), thus increasing losses in the transformer and decreasing its efficiency. The degradation of transformer oil leads to safety hazards like transformer bursting, consequently forcing the electricity board to replace the transformer, thus incurring huge amount of costs. This is the most relatable problem faced by the electricity board in every state. This research work aims at listing out various properties of transformer oil and ascertaining major impurities in a transformer oil by testing it using various techniques. The proposed work deals with long term observation and analysis of transformer oil to determine its degradation rate. Breakdown voltage, Moisture content, Resistivity, Acidity, Furan Analysis and Dissolved Gas Analysis were done using Mushroom electrodes, Karl Fischer Titration test, Tan delta test, Potassium Hydroxide Titration, High performance liquid chromatography, and dissolved gas analyzer respectively. The results reveal that, deviation of Breakdown Voltage, Moisture content, and 2-Furaldehyde (1197ppb) from the permissible limits can indicate the aging of the transformer.

2014 ◽  
Vol 556-562 ◽  
pp. 502-506
Author(s):  
Yi Chen ◽  
Bin Song

Dissolved gas analysis (DGA) in transformer oil is considered as one of the preferred projects to discover the potential faults of the transformer. To identify the aging characteristics of oil-immersed transformer oil in long-term operations, it is important to study relationship between total hydrocarbon and gases dissolved in transformer oil. This paper used Pearson correlation coefficient to analyze the relationship with the data of DGA. At last, it gives the result that the correlations between the total hydrocarbon and carbon monoxide, methane, ethane, ethylene, acetylene was positive. Therefore, this study lays the foundation which help to diagnose the aging status of transformer.


2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Nitin K. Dhote ◽  
Jagdish B. Helonde

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.


2014 ◽  
Vol 519-520 ◽  
pp. 98-101
Author(s):  
De Wen Wang ◽  
Zhi Wei Sun

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.


IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 72012-72019 ◽  
Author(s):  
Zhenwei Chen ◽  
Xiaoxing Zhang ◽  
Hao Xiong ◽  
Dachang Chen ◽  
Hongtu Cheng ◽  
...  

2014 ◽  
Vol 535 ◽  
pp. 157-161
Author(s):  
Jeeng Min Ling ◽  
Ming Jong Lin ◽  
Chao Tang Yu

Dissolved gas analysis (DGA) is an effective tool for detecting incipient faults in power transformers. The ANSI/IEEE C57.104 standards, the most popular guides for the interpretation of gases generated in oil-immersed transformers, and the IEC-Duval triangle method are integrated to develop the proposed power transformer fault diagnosis method. The key dissolved gases, including H2, CH4, C2H2, C2H4, C2H6, and total combustible gases (TCG), suggested by ASTM D3612s instruction for DGA is investigated. The tested data of the transformer oil were taken from the substations of Taiwan Power Company. Diagnosis results with the text form called IEC-Duval triangle method show the validation and accuracy to detect the incipient fault in the power transformer.


ACS Omega ◽  
2020 ◽  
Vol 5 (28) ◽  
pp. 17801-17807 ◽  
Author(s):  
Qian Zhou ◽  
Guozhi Zhang ◽  
Shuangshuang Tian ◽  
Xiaoxing Zhang

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