Lifespan Model of the Relationships between Ethanol Indicator and Degree of Polymerization of Transformer Paper Insulation

Zhang, Enze; Zheng, Hanbo; Zhang, Yiyi; Liu, Jiefeng; Shi, Zhen; Shi, Kuikui; Zhang, Chuansheng; Shao, Guangqi; Zhang, Chaohai; Schwarz, Harald

doi:10.1109/tdei.2021.009519

Cited by 12 publications

(7 citation statements)

References 20 publications

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“…These units are based on the south African power utility specification. Recent research [23,24] has established that, by analyzing dielectric oil samples by means of the furan test for 2FAL concentration dissolved into the oil throughout the The constancy of Furanic compounds intrigues the transformer manufacturing industry in view of the fact that they are of service in arriving at conclusions based on the concentration levels present in the dielectric oil. However, inconsistent Furanic compounds may bring about an erroneous conclusion to manufacturers.…”

Section: Furan Formation and Correlation Between 2-fal And Dpmentioning

confidence: 99%

“…These units are based on the south African power utility specification. Recent research [23,24] has established that, by analyzing dielectric oil samples by means of the furan test for 2FAL concentration dissolved into the oil throughout the Recent research [23,24] has established that, by analyzing dielectric oil samples by means of the furan test for 2FAL concentration dissolved into the oil throughout the ageing process, the indirect measurement of the cellulose paper sample can be carried out. During the transformer's intended operational lifetime, 2FAL compounds are released from the cellulose paper into the oil, and, by analyzing the oil, the DP value can be predicted.…”

Section: Furan Formation and Correlation Between 2-fal And Dpmentioning

confidence: 99%

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Prediction of the Degree of Polymerization in Transformer Cellulose Insulation Using the Feedforward Backpropagation Artificial Neural Network

Thango

Bokoro

2022

Energies

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The life expectancy of power transformers is primarily determined by the integrity of the insulating oil and cellulose paper between the conductor turns, phases and phase to earth. During the course of their in-service lifetime, the solid insulating system of windings is contingent on long-standing ageing and decomposition. The decomposition of the cellulose paper insulation is strikingly grievous, as it reduces the tensile strength of the cellulose paper and can trigger premature failure. The latter can trigger premature failure, and to realize at which point during the operational life this may occur is a daunting task. Various methods of estimating the DP have been proposed in the literature; however, these methods yield different results, making it difficult to accurately estimate a reliable DP. In this work, a novel approach based on the Feedforward Backpropagation Artificial Neural Network has been proposed to predict the amount of DP in transformer cellulose insulation. Presently, no ANN model has been proposed to predict the remaining DP using 2FAL concentration. A databank comprising 100 data sets—70 for training and 30 for testing—is used to develop the proposed ANN using 2-furaldehyde (2FAL) as an input and DP as an output. The proposed model yields a correlation coefficient of 0.958 for training, 0.915 for validation, 0.996 for testing and an overall correlation of 0.958 for the model.

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Section: Furan Formation and Correlation Between 2-fal And Dpmentioning

confidence: 99%

“…These units are based on the south African power utility specification. Recent research [23,24] has established that, by analyzing dielectric oil samples by means of the furan test for 2FAL concentration dissolved into the oil throughout the Recent research [23,24] has established that, by analyzing dielectric oil samples by means of the furan test for 2FAL concentration dissolved into the oil throughout the ageing process, the indirect measurement of the cellulose paper sample can be carried out. During the transformer's intended operational lifetime, 2FAL compounds are released from the cellulose paper into the oil, and, by analyzing the oil, the DP value can be predicted.…”

Section: Furan Formation and Correlation Between 2-fal And Dpmentioning

confidence: 99%

Prediction of the Degree of Polymerization in Transformer Cellulose Insulation Using the Feedforward Backpropagation Artificial Neural Network

Thango

Bokoro

2022

Energies

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“…According to the existing research [3], the ageing and dampness of oil‐paper insulation will reduce its property and performance. While the ageing and dampness of the oil‐paper insulation exceed the security threshold, the oil‐paper insulation system will be broken down, resulting in transformer damage and grid debacle [4]. Therefore, it is significant to research the ageing degrees and moisture contents of oil‐paper insulation.…”

Section: Introductionmentioning

confidence: 99%

Microscopic mechanisms analysis of various dielectric response processes in oil‐paper insulation with different insulating states

Jiang,

Liu,

Fan

et al. 2024

High Voltage

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Various dielectric response processes in the oil‐paper insulation are sensitively affected by the insulating states (ageing degrees and moisture contents). However, the existing research is still incomplete in revealing the microscopic mechanisms of various dielectric response processes in oil‐paper insulation with different insulating states. Given this issue, the genetic algorithm is first adopted to extract the Dissado–Hill (D–H) model parameters by simulating the frequency domain spectroscopy (FDS) of oil‐paper insulation. Then, the change laws of the extracted D–H model parameters are adopted to reveal the microscopic mechanisms of various dielectric response processes. Microscopic mechanisms of four dielectric response processes are studied, which are quasi‐dc relaxation, loss peak relaxation, optical frequency relaxation, and DC conductance. Meanwhile, due to the dielectric response processes being dominated by various polar particles (methanol, ethanol, furfural, and water molecule), the contents of various ageing by‐products dissolved in the insulating oil are measured to support the above analysis. In this respect, a dielectric theoretical reference for the FDS technique to research the insulating states of oil‐paper insulation is provided.

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“…With the increase in the service life of the transformer, its oil paper insulation structure is gradually aging under the influence of many factors, which is easy to cause the burning of the transformer, and bring personal and property safety risks to the power operators and residents [11,12]. In the internal insulation system of oil immersed transformer, the internal insulation life of transformer depends on the life of insulating paper, because insulating oil is replaceable, but cellulose paper as solid insulation is inconvenient to be repaired or replaced [13]. Therefore, the key way to estimate the insulation life of transformer is the aging state of cellulose paper [14,15].…”

Section: Introductionmentioning

confidence: 99%

A review on a novel method for aging evaluation of transformer insulating paper based on methanol

Chen

Sun

Cheng

et al. 2023

IET Generation Trans & Dist

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The insulation paper is a crucial factor for evaluating the insulation status of transformers. The traditional evaluation methods for insulation paper are dissolved gas component content analysis (CO and CO 2 ) and furfural (2-FAL) content analysis in oil. The detection principle of the former leads to its low accuracy, while the field application effect of the latter is not ideal due to the easy oxidation of furfural and low content. Methanol, result of its good stability and high production compared with other marker products (CO, CO 2 , 2-FAL) has been investigated as a novel marker for aging evaluation of transformer insulating paper in recent years. The results of the investigation indicated that there is a good correlation between the content of methanol in oil and the degree of polymerization under laboratory conditions, which reflected the insulation aging state of the transformer insulating paper more accurately. This paper summarizes the current research status of methanol formation mechanism, detection methods and aging evaluation in insulating oil, and points out the key problems to be solved and development prospects, hoping to provide relevant reference for aging evaluation of oil immersed power transformer.

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Lifespan Model of the Relationships between Ethanol Indicator and Degree of Polymerization of Transformer Paper Insulation

Cited by 12 publications

References 20 publications

Prediction of the Degree of Polymerization in Transformer Cellulose Insulation Using the Feedforward Backpropagation Artificial Neural Network

Prediction of the Degree of Polymerization in Transformer Cellulose Insulation Using the Feedforward Backpropagation Artificial Neural Network

Microscopic mechanisms analysis of various dielectric response processes in oil‐paper insulation with different insulating states

A review on a novel method for aging evaluation of transformer insulating paper based on methanol

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