Skip to main content
Log in

Recognition of combined defects with high-temperature overheating based on the dissolved gas analysis

  • Published:
Sādhanā Aims and scope Submit manuscript

Abstract

The paper presents the results of a complex analysis of gas content in 259 high-voltage transformers, in which overheating with temperatures above 700\(^{\circ }\)C accompanied by discharges with different intensity, were detected. To increase the recognition reliability, ranges of gas percentage and gas ratio values have been determined and 15 nomograms corresponding to the high-temperature overheating, which were accompanied by discharges with different intensity, have been drawn. The analysis of the values of pair correlation coefficients between the concentrations of gases dissolved in transformer oil has been performed. The dynamics of nomogram changes during the development of combined defects with a high-temperature overheating has been analysed. The results of comparative analysis of the recognition reliability of high-temperature overheating, which are accompanied by discharges with different intensity, using the diagnostic criteria values regulated by current standards and methods of interpretation of the dissolved gas analysis results, are presented.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8

Similar content being viewed by others

Abbreviations

DGA:

Dissolved gas analysis

HED:

High-energy density

HTO:

High-temperature overheating

HVT:

High-voltage transformer

PD:

Partial discharges

\({\mathrm{H}}_{2}\) :

Hydrogen

\({\mathrm{CH}}_{4}\) :

Methane

\({\mathrm{C}}_{2}{\mathrm{H}}_{6}\) :

Ethane

\({\mathrm{C}}_{2}{\mathrm{H}}_{4}\) :

Ethylene

\({\mathrm{C}}_{2}{\mathrm{H}}_{2}\) :

Acetylene

References

  1. Bakar N A, Abu-Siada A and Islam S 2014 A review of dissolved gas analysis measurement and interpretation techniques. IEEE Electrical Insulation Magazine. 30(3): 39–49. https://doi.org/10.1109/MEI.2014.6804740

    Article  Google Scholar 

  2. Golarz J 2016 Understanding dissolved gas analysis (DGA) techniques and interpretations. In: 2016 IEEE/PES Transmission and Distribution Conference and Exposition (T &D), Dallas, TX, USA, pp. 1–5. https://doi.org/10.1109/tdc.2016.7519852

  3. Kulyk O 2020 Analysis of the diagnostic criteria used to defect type recognition based on the results of analysis of gases dissolved in oil. Bulletin of the National Technical University “KhPI”. Series: Energy: Reliability and Energy Efficiency. 1: 15–25. https://doi.org/10.20998/2224-0349.2020.01.03

  4. IEC 60599:2015 Mineral oil-filled electrical equipment in service—guidance on the interpretation of dissolved and free gases analysis

  5. SOU-N EE 46.501:2006 Diagnosis of oil-filled transformer equipment by chromatographic analysis of free gases sampled from the gas relay and gases dissolved in the insulating oil. Methodological guidelines (in Ukrainian)

  6. STO 34.01-23-003-2019 Methodological guidelines for the technical diagnosis of developing defects in oil-filled high-voltage electrical equipment based on the results of dissolved gas analysis (in Russian)

  7. Dörnenburg E and Strittmater W 1974 Monitoring oil-cooled transformers by gas analysis. Brown Boveri Review. 61: 238–274

    Google Scholar 

  8. Rogers R 1978 IEEE and IEC codes to interpret incipient faults in transformers, using gas in oil analysis. IEEE Transactions on Electrical Insulation. EI-13(5): 349–354. https://doi.org/10.1109/tei.1978.298141

    Article  Google Scholar 

  9. Müller A, Schliesing H and Soldner K 1977 Die Beurteilung des Betriebszustandes von Transformatoren durch Gasanalyse. Elektrizitätswirtschaft. 76: 345–349 (in German)

    Google Scholar 

  10. Duval M 2008 The duval triangle for load tap changers, non-mineral oils and low temperature faults in transformers. IEEE Electrical Insulation Magazine. 24(6): 22–29. https://doi.org/10.1109/mei.2008.4665347

    Article  Google Scholar 

  11. Duval M and Lamarre L 2014 The duval pentagon-a new complementary tool for the interpretation of dissolved gas analysis in transformers. IEEE Electrical Insulation Magazine. 30(6): 9–12. https://doi.org/10.1109/mei.2014.6943428

    Article  Google Scholar 

  12. Cheim L, Duval M and Haider S 2020 Combined duval pentagons: a simplified approach. Energies. 13(11): 2859. https://doi.org/10.3390/en13112859

    Article  Google Scholar 

  13. IEEE Std. C57.104-2019 IEEE guide for the interpretation of gases generated in mineral oil-immersed transformers. https://doi.org/10.1109/IEEESTD.2019.8890040

  14. Gouda O, El-Hoshy S and El-Tamaly H 2018 Proposed heptagon graph for DGA interpretation of oil transformers. IET Generation, Transmission & Distribution. 12(2): 490–498. https://doi.org/10.1049/iet-gtd.2017.0826

    Article  Google Scholar 

  15. Mansour D 2015 Development of a new graphical technique for dissolved gas analysis in power transformers based on the five combustible gases. IEEE Transactions on Dielectrics and Electrical Insulation. 22(5): 2507–2512. https://doi.org/10.1109/tdei.2015.004999

    Article  Google Scholar 

  16. Dukarm J, Draper Z and Piotrowski T 2020 Diagnostic simplexes for dissolved-gas analysis. Energies. 13(23): 6459. https://doi.org/10.3390/en13236459

    Article  Google Scholar 

  17. Electric Technology Research Association 2009 Guideline for the refurbishment of electric power transformers. 65(1) (in Japanese)

  18. Kawamura T, Kawada H, Ando K, Yamaoka M, Maeda T and Takatsu T 1986 Analyzing gases dissolved in oil and its application to maintenance of transformers. In: Report 12-05. CIGRE Session

  19. Bakar R and Desai P 2016 Dissolved gas analysis in power transformer using artificial neural network. International Journal of modern Trends in Engineering and Research. Special Issue of ICRTET’2016. 3(4): 322–326

    Google Scholar 

  20. Palke R and Korde P 2020 Dissolved gas analysis (DGA) to diagnose the internal faults of power transformer by using fuzzy logic method. In: 2020 International Conference on Communication and Signal Processing (ICCSP), Chennai, India, pp. 1050–1053. https://doi.org/10.1109/iccsp48568.2020.9182279

  21. Koldaev A, Evdokimov A and Shebzukhova B 2020 An approach to neuro-fuzzy monitoring of power transformers. In: 2020 International Multi-conference on Industrial Engineering and Modern Technologies (FarEastCon), Vladivostok, Russia, pp. 1–5. https://doi.org/10.1109/fareastcon50210.2020.9271394

  22. Kherif O, Benmahamed Y, Teguar M, Boubakeur A and Ghoneim S 2021 Accuracy improvement of power transformer faults diagnostic using KNN classifier with decision tree principle. IEEE Access. 9: 81693–81701. https://doi.org/10.1109/access.2021.3086135

    Article  Google Scholar 

  23. Benmahamed Y, Kherif O, Teguar M, Boubakeur A and Ghoneim S 2021 Accuracy improvement of transformer faults diagnostic based on DGA data using SVM-BA classifier. Energies. 14(10): 2970. https://doi.org/10.3390/en14102970

    Article  Google Scholar 

  24. Patel D and Chothani N 2020 Relevance Vector Machine Based Transformer Protection. In: Digital Protective Schemes for Power Transformer. Power Systems, pp. 107–131. https://doi.org/10.1007/978-981-15-6763-6

  25. Abu-Siada A 2019 Improved consistent interpretation approach of fault type within power transformers using dissolved gas analysis and gene expression programming. Energies. 12(4): 730. https://doi.org/10.3390/en12040730

    Article  Google Scholar 

  26. Shutenko O and Kulyk O 2020 Combined defects recognition in the low and medium temperature range by results of dissolved gas analysis. In: 2020 IEEE KhPI Week on Advanced Technology (KhPIWeek), Kharkiv, Ukraine, pp. 65–70. https://doi.org/10.1109/khpiweek51551.2020.9250131

  27. Shutenko O and Kulyk O 2020 Recognition of overheating with temperatures of 150-300\(^{\circ }\)C by analysis of dissolved gases in oil. In: 2020 IEEE 4th International Conference on Intelligent Energy and Power Systems (IEPS), Istanbul, Turkey, pp. 71–76. https://doi.org/10.1109/ieps51250.2020.9263145

  28. Kulyk O and Shutenko O 2019 Analysis of gas content in oil-filled equipment with spark discharges and discharges with high energy density. Transactions on Electrical and Electronic Materials. 20(5): 437–447. https://doi.org/10.1007/s42341-019-00124-8

    Article  Google Scholar 

  29. Shutenko O and Kulyk O 2020 Analysis of gas content in oil-filled equipment with low energy density discharges. International Journal on Electrical Engineering and Informatics. 12(2): 258–277. https://doi.org/10.15676/ijeei.2020.12.2.6

    Article  Google Scholar 

  30. Shutenko O and Kulyk O 2021 Recognition of mid-temperature overheating in high-voltage power transformers by dissolved gas analysis. In: 2021 IEEE KhPI Week on Advanced Technology (KhPIWeek), Kharkiv, Ukraine, pp. 401–406. https://doi.org/10.1109/KhPIWeek53812.2021.9570059

  31. Shutenko O and Kulyk O 2021 Recognition of high-temperature overheating in high-voltage power transformers by dissolved gas analysis. In: 2021 IEEE International Conference on Modern Electrical and Energy Systems (MEES), Kremenchuk, Ukraine, pp. 1–6. https://doi.org/10.1109/MEES52427.2021.9598575

  32. Shutenko O and Kulyk O 2022 Recognition of low-temperature overheating in power transformers by dissolved gas analysis. Electrical Engineering. https://doi.org/10.1007/s00202-021-01465-5

    Article  Google Scholar 

  33. Shutenko O and Jakovenko I 2017 Fault diagnosis of power transformer using method of graphic images. In: 2017 IEEE International Young Scientists Forum on Applied Physics and Engineering (YSF 2017), Lviv, Ukraine, pp. 66–69. https://doi.org/10.1109/YSF.2017.8126594

  34. Liu Y, Song B, Wang L, Gao J and Xu R 2020 Power transformer fault diagnosis based on dissolved gas analysis by correlation coefficient-DBSCAN. Applied Sciences. 10(13): 4440. https://doi.org/10.3390/app10134440

    Article  Google Scholar 

  35. Liang Y, Zhang Z, Li K and Li Y 2021 New correlation features for dissolved gas analysis based transformer fault diagnosis based on the maximal information coefficient. High Voltage. https://doi.org/10.1049/hve2.12136

    Article  Google Scholar 

  36. Gmurman V E 1977 Probability Theory and Mathematical Statistics. Moscow: High school (in Russian)

    MATH  Google Scholar 

  37. Shutenko O 2018 Faults diagnostics of high-voltage equipment based on the analysis of the dynamics of changing of the content of gases. Energetika. 64(1): 11–22. https://doi.org/10.6001/energetika.v64i1.3724

    Article  Google Scholar 

  38. Zarei J, Shasadeghi M and Ramezani A 2014 Fault prognosis in power transformers using adaptive-network-based fuzzy inference system. Journal of Intelligent & Fuzzy Systems. 26(5): 2577–2590. https://doi.org/10.3233/ifs-130929

    Article  Google Scholar 

  39. Geetha M, Jovitha J and Manikandan P 2014 Integrating fuzzy IEC expert system based fault diagnosis for power transformer using dissolved gas analysis. Journal of Electrical Engineering. 14(2): 348–354.

    Google Scholar 

  40. Illias H and Zhao Liang W 2018 Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation. PLOS ONE. 13(1): e0191366. https://doi.org/10.1371/journal.pone.0191366

    Article  Google Scholar 

  41. Li E, Wang L, Song B and Jian S 2018 Improved fuzzy C-means clustering for transformer fault diagnosis using dissolved gas analysis data. Energies. 11(9): 2344. https://doi.org/10.3390/en11092344

    Article  Google Scholar 

  42. Bilbao J, Rebollo C and Gonzalez P 2004 Expertise method to diagnose transformer conditions. In: WSEAS International Conference on APPLIED MATHEMATICS, Corfu, Greece

  43. Hameed I and Saher R 2021 Monitoring power transformer using fuzzy logic. Journal of Engineering and Development. 17(6): 146–163

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Oleksii Kulyk.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shutenko, O., Kulyk, O. Recognition of combined defects with high-temperature overheating based on the dissolved gas analysis. Sādhanā 47, 146 (2022). https://doi.org/10.1007/s12046-022-01919-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12046-022-01919-x

Keywords

Navigation