Analysis of excessive hydrogen generation in transformers in service

Piotrowski, T.; Rózga, Paweł; Kozak, Ryszard

doi:10.1109/tdei.2015.005347

Cited by 19 publications

(15 citation statements)

References 11 publications

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“…Piotrowaki et al [7] analyzed the excess hydrogen in the gas content of oil; it was confirmed by the IEC 60599 ratio methodology and the Duval triangle methodology that a partial discharge phenomenon occurred in the power transformer, but the case described in CIGRE manual 2965 may be caused by the incompatibility between the material and the oil.…”

Section: Related Workmentioning

confidence: 99%

“…In statistical hypothesis testing [20], a type-I error is the rejection of a true null hypothesis H 0 , and a type-II error fails to reject a false null hypothesis. Here, the diagnostic rule presented in (6) is used, and the probabilities of these two types of detection errors are expressed as shown in (7) and (8), respectively. The probability of obtaining a detection error can therefore be obtained as shown in (9)…”

Section: B Validity Verification and Performancementioning

confidence: 99%

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A Methodology for Diagnosing Faults in Oil-Immersed Power Transformers Based on Minimizing the Maintenance Cost

Lin

Chen

2020

IEEE Access

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Section: Related Workmentioning

confidence: 99%

Section: B Validity Verification and Performancementioning

confidence: 99%

A Methodology for Diagnosing Faults in Oil-Immersed Power Transformers Based on Minimizing the Maintenance Cost

Lin

Chen

2020

IEEE Access

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“…Several studies [48,49,50,51,52,53,54,55,56] indicate that the best method for the faults identification in the transformer insulation is the Duval triangle method (DTM).The Duval pentagon method (DPM) was created to improve DTM results. Several recent studies [48,49] indicate that the DPM success rate improves those of the DTM, since the DPM allows to identify the normal aging of the transformer insulation.…”

Section: Dissolved Gas-in-oil Analysismentioning

confidence: 99%

Dissolved Gas Analysis Equipment for Online Monitoring of Transformer Oil: A Review

Bustamante

Canteli

Arroyo

et al. 2019

Sensors

116

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Power transformers are the most important assets of electric power substations. The reliability in the operation of electric power transmission and distribution is due to the correct operation and maintenance of power transformers. The parameters that are most used to assess the health status of power transformers are dissolved gas analysis (DGA), oil quality analysis (OQA) and content of furfuraldehydes (FFA) in oil. The parameter that currently allows for simple online monitoring in an energized transformer is the DGA. Although most of the DGA continues to be done in the laboratory, the trend is online DGA monitoring, since it allows for detection or diagnosis of the faults throughout the life of the power transformers. This study presents a review of the main DGA monitors, single- or multi-gas, their most important specifications, accuracy, repeatability and measurement range, the types of installation, valve or closed loop, and number of analogue inputs and outputs. This review shows the differences between the main existing DGA monitors and aims to help in the selection of the most suitable DGA monitoring approach according to the needs of each case.

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“…Stage 4. High-energy sparking not only causes the formation of carbonized traces on the pressboard surface, but also leads—due to dissociation of oil molecules—to the formation of hydrogen [67], gaseous hydrocarbons (mainly C 2 H 2 and CH 4 ), and wax-like substances [68]. As the path length increases, the apparent charge of the surface discharges decreases to ~500 pC‒5 nC, and it is high enough to continue the degradation of cellulose.…”

Section: Investigated Types Of Partial Discharges and Electrode Symentioning

confidence: 99%

Development of Acoustic Emission Sensor Optimized for Partial Discharge Monitoring in Power Transformers

Sikorski

2019

Sensors

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The acoustic emission (AE) technique is one of the unconventional methods of partial discharges (PD) detection. It plays a particularly important role in oil-filled power transformers diagnostics because it enables the detection and online monitoring of PDs as well as localization of their sources. The performance of this technique highly depends on measurement system configuration but mostly on the type of applied AE sensor. The paper presents, in detail, the design and manufacturing stages of an ultrasensitive AE sensor optimized for partial discharge detection in power transformers. The design assumptions were formulated based on extensive laboratory research, which allowed for the identification of dominant acoustic frequencies emitted by partial discharges in oil–paper insulation. The Krimholtz–Leedom–Matthaei (KLM) model was used to iteratively find optimal material and geometric properties of the main structures of the prototype AE sensor. It has two sensing elements with opposite polarization direction and different heights. The fully differential design allowed to obtain the desired properties of the transducer, i.e., a two-resonant (68 kHz and 90 kHz) and wide (30‒100 kHz) frequency response curve, high peak sensitivity (−61.1 dB ref. V/µbar), and low noise. The laboratory tests confirmed that the prototype transducer is characterized by ultrahigh sensitivity of partial discharge detection. Compared to commonly used commercial AE sensors, the average amplitude of PD pulses registered with the prototype sensor was a minimum of 5.2 dB higher, and a maximum of 19.8 dB higher.

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Analysis of excessive hydrogen generation in transformers in service

Cited by 19 publications

References 11 publications

A Methodology for Diagnosing Faults in Oil-Immersed Power Transformers Based on Minimizing the Maintenance Cost

A Methodology for Diagnosing Faults in Oil-Immersed Power Transformers Based on Minimizing the Maintenance Cost

Dissolved Gas Analysis Equipment for Online Monitoring of Transformer Oil: A Review

Development of Acoustic Emission Sensor Optimized for Partial Discharge Monitoring in Power Transformers

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