Evaluation Method for Insulation Degradation Based on Furfural Content in 35kVField Transformer Oil

Tang, Xiaofeng; Cui, Linli; He, Jinmei; Su, Zhengyuxi; Chen, Peng

doi:10.1109/cieec47146.2019.cieec-2019276

Cited by 1 publication

(2 citation statements)

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“…These degradation types lead to 2-FAL formation in insulating oil, which is used as an indicator of the DP value and information about insulating paper state. 2-FAL can be measured using HPLC [15].…”

Section: Introductionmentioning

confidence: 99%

“…Most researchers have interpreted insulating paper condition based on the DP value, which is based on 2-FAL in the insulating oil [12][13][14][15]. The interpretation has some shortcomings [16,17] for the following reasons: (i) the reduced concentration of the 2-FAL in some insulating paper fails because the paper is adsorbed to 2-FAL, thus making the results of the 2-FAL concentration in the transformer oil incorrect [16,18], (ii) the logarithmic relationship between the DP and 2-FAL reveal that a significant change in the DP can result from a small change of 2-FAL concentration [16,19], and (iii) the measurement technique for 2-FAL cannot indicate the real state of the insulating paper for the initial aging stage [16].…”

Section: Introductionmentioning

confidence: 99%

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Determination of Transformers’ Insulating Paper State Based on Classification Techniques

Ghoneim

2021

Processes

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The continuity of transformer operation is very necessary for utilities to maintain a continuity of power flow in networks and achieve a desired revenue. Most failures in a transformer are due to the degradation of the insulating system, which consists of insulating oil and paper. The degree of polymerization (DP) is a key detector of insulating paper state. Most research in the literature has computed the DP as a function of furan compounds, especially 2-furfuraldehyde (2-FAL). In this research, a prediction model was constructed based on some of most periodical tests that were conducted on transformer insulating oil, which were used as predictors of the insulating paper state. The tests evaluated carbon monoxide (CO), carbon dioxide (CO2), breakdown voltage (VBD), interfacial tension (IF), acidity (ACY), moisture (M), oil color (OC), and 2-furfuraldehyde (2-FAL). The DP, which was used as the key indicator for the paper state, was categorized into five classes labeled 1, 2, 3, 4, and 5 to express the insulating paper normal aging rate, accelerating aging rate, excessive aging danger zone, high risk of failure, and the end of expected life, respectively. The classification techniques were applied to the collected data samples to construct a prediction model for the insulating paper state, and the results revealed that the fine tree was the best classifier of the data samples, with a 96.2% prediction accuracy.

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Section: Introductionmentioning

confidence: 99%