A Modified Dissolved Gas Analysis Technique as a Diagnostic Tool for Faults in Power Transformers

Ward, Sayed A.; Elfaraskoury, Adel A.; Badwi, Mohamed; Ibrahim, Shimaa A.

doi:10.1109/mepcon47431.2019.9008209

Cited by 7 publications

(6 citation statements)

References 7 publications

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“…This proposed technique is developed based on the integration among the results of conventional and non-conventional techniques. These techniques are five techniques; conditional probability [32], clustering [33], Duval, Roger's four ratios refined [7,34], and artificial neural network (ANN) [35] techniques. A total of 360 samples of known actual faults are used in developing the proposed technique, and also are used as a dataset for testing the technique accuracy.…”

Section: Proposed Dga Based Fault Diagnostic Techniquementioning

confidence: 99%

“…During the normal transformer operation, some low concentrated gases are released such as Hydrogen (H2), Methane (CH 4 ), Acetylene (C 2 H 2 ), Ethylene (C 2 H 4 ), Ethane (C 2 H 6 ), Carbon monoxide (CO), and Carbon Dioxide (CO 2 ). While during fault conditions, these gases are produced with high concentration levels, and hence DGA techniques depend on detecting the released concentration level in case of thermal and electrical stresses [7,8].…”

mentioning

confidence: 99%

“…Many conventional techniques were developed and used for interpretation of transformer incipient faults based on DGA such as key gas ratio [9], Rogers' ratio [9,10], IEC gas ratio [10], Dornenburg ratio technique [9], and Duval Techniques [11,12]. The conventional approaches do not often yield accurate analysis while missing important incipient faults, thereby leading to the 'no decision' issue [7]. Most of the existing DGA techniques have limited diagnostic accuracy and may fail to interpret the oil faults in transformers [13].…”

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confidence: 99%

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Reliable Estimation for Health Index of Transformer Oil Based on Novel Combined Predictive Maintenance Techniques

et al. 2022

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Section: Proposed Dga Based Fault Diagnostic Techniquementioning

confidence: 99%

mentioning

confidence: 99%

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confidence: 99%

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Reliable Estimation for Health Index of Transformer Oil Based on Novel Combined Predictive Maintenance Techniques

et al. 2022

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“…The oil common incipient electrical faults are Partial discharge (PD), and arcing discharge of high and low energy (D2 and D1). While the thermal types of faults as high, medium and low (T3, T2, and T1) are types of thermal faults (S. S. M. Ghoneim, 2021, E. Bezerra, 2020, H. Salem, 2022, S. A.Ward, 2019, H. C. Chen, 2022. Hence, for improving the power system reliability and lowering the risk of transformer failure, it is crucial to identify the oil insulation levels with regular proactive and predicative maintenance program.…”

Section: Introductionmentioning

confidence: 99%

Identification of Transformer Oil incipient Faults Based on the Integration between Different DGA Techniques

Ward

Ibrahim

Elfaraskoury

et al. 2023

Delta University Scientific Journal

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Premature diagnosis of transformer oil faults enables the operator for diagnosing the transformer condition and hence operating the transformer continuously without outage. DGA is one of the most popular chemical tests used for fault diagnosis and there are many techniques which have been developed in this regard. This paper presents a proposed DGA technique for transformer oil fault identification based on the results of the recently published techniques. The proposed technique has been constructed based on the integration between the outputs of two recently established DGA techniques; Conditional probability and artificial neural network. A total of 532 datasets, obtained from the Egyptian Electricity Transmission Company (EETC) with known faults, have been used for designing and testing the proposed technique. The proposed fault diagnostic technique's accuracy attained 86.6 %, which is higher than the results of the combined techniques; 81.7% for ANN and 82.8% for conditional probability technique. The proposed developed technique came to the conclusion that integrating several DGA techniques, with higher accuracy, enhances fault detection's overall accuracy.

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“…Key gasses formed by the degradation of oil and paper insulation are: (1) hydrogen (H 2 ), (2) ethylene (C 2 H 4 ), (3) acetylene (C 2 H 2 ), (4) carbon dioxide (CO 2 ), (5) ethane (C 2 H 6 ), (6) methane (CH 4 ), and (7) carbon monoxide (CO). The gas concentrations, generation rates, specific gas ratios, and the total combustible gas are important parameters for interpreting the result of DGA [ 6 , 7 , 8 , 9 ].…”

Section: Introductionmentioning

confidence: 99%

Towards Precise Interpretation of Oil Transformers via Novel Combined Techniques Based on DGA and Partial Discharge Sensors

Ward

Elfaraskoury

Badawi

et al. 2021

Sensors

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Power transformers are considered important and expensive items in electrical power networks. In this regard, the early discovery of potential faults in transformers considering datasets collected from diverse sensors can guarantee the continuous operation of electrical systems. Indeed, the discontinuity of these transformers is expensive and can lead to excessive economic losses for the power utilities. Dissolved gas analysis (DGA), as well as partial discharge (PD) tests considering different intelligent sensors for the measurement process, are used as diagnostic techniques for detecting the oil insulation level. This paper includes two parts; the first part is about the integration among the diagnosis results of recognized dissolved gas analysis techniques, in this part, the proposed techniques are classified into four techniques. The integration between the different DGA techniques not only improves the oil fault condition monitoring but also overcomes the individual weakness, and this positive feature is proved by using 532 samples from the Egyptian Electricity Transmission Company (EETC). The second part overview the experimental setup for (66/11.86 kV–40 MVA) power transformer which exists in the Egyptian Electricity Transmission Company (EETC), the first section in this part analyzes the dissolved gases concentricity for many samples, and the second section illustrates the measurement of PD particularly in this case study. The results demonstrate that precise interpretation of oil transformers can be provided to system operators, thanks to the combination of the most appropriate techniques.

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A Modified Dissolved Gas Analysis Technique as a Diagnostic Tool for Faults in Power Transformers

Cited by 7 publications

References 7 publications

Reliable Estimation for Health Index of Transformer Oil Based on Novel Combined Predictive Maintenance Techniques

Reliable Estimation for Health Index of Transformer Oil Based on Novel Combined Predictive Maintenance Techniques

Identification of Transformer Oil incipient Faults Based on the Integration between Different DGA Techniques

Towards Precise Interpretation of Oil Transformers via Novel Combined Techniques Based on DGA and Partial Discharge Sensors

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