Comparison of Artificial Intelligence Techniques and Conventional Techniques for Power Transformer Fault Diagnosis with Dissolved Gas Analysis (DGA): Challenges and Opportunities

Nurullah Açıkgöz; Murat Sazlı

doi:10.33769/aupse.1757488

Comparison of Artificial Intelligence Techniques and Conventional Techniques for Power Transformer Fault Diagnosis with Dissolved Gas Analysis (DGA): Challenges and Opportunities

Abstract

In power systems, transformers have a key role in terms of electrical energy sustainability in transmission and distribution. Moreover, this crucial instrument of power systems must be operated at optimum performance in electric transmission lines and power distribution system as well as rational economic conditions. When usual operating conditions is became, mineral oil comes out on a slow and typical degradation. If on the contrary due to thermal or electrical stress, the degradation status accelarates. In this case, some gases (ethylene,acetylene,carbonmonoxide,carbondioxied, hydrogen, methane,ethane) are occured in the mineral oil. For dissolved gas analysis (DGA), custom traditional methods seems to identify and classify the initial faults. However, they are unable to notice the status in case of multiple electrical and thermal errors simultaneously. While the serious limitation of conventional DGA methods in terms of accuracy and consistency, AI methods gives well prediction. In the study, future challenges and opportunities are elaborately presented for researchers.

Keywords

References

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Details

Primary Language

English

Subjects

Electrical Energy Transmission, Networks and Systems, Electrical Engineering (Other)

Journal Section

Research Article

Authors

Nurullah Açıkgöz ^*
0000-0003-4328-5758
Türkiye

Murat Sazlı
0000-0001-9235-3679
Türkiye

Publication Date

June 30, 2026

Submission Date

August 3, 2025

Acceptance Date

April 17, 2026

Published in Issue

Year 2026 Volume: 68 Number: 1

DOI

https://doi.org/10.33769/aupse.1757488

IZ

https://izlik.org/JA86DF79KC

Cite

RIS / Bibtex

APA

Açıkgöz, N., & Sazlı, M. (2026). Comparison of Artificial Intelligence Techniques and Conventional Techniques for Power Transformer Fault Diagnosis with Dissolved Gas Analysis (DGA): Challenges and Opportunities. Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering, 68(1), 57-74. https://doi.org/10.33769/aupse.1757488

AMA

1.Açıkgöz N, Sazlı M. Comparison of Artificial Intelligence Techniques and Conventional Techniques for Power Transformer Fault Diagnosis with Dissolved Gas Analysis (DGA): Challenges and Opportunities. Commun.Fac.Sci.Univ.Ank.Series A2-A3: Phys.Sci. and Eng. 2026;68(1):57-74. doi:10.33769/aupse.1757488

Chicago

Açıkgöz, Nurullah, and Murat Sazlı. 2026. “Comparison of Artificial Intelligence Techniques and Conventional Techniques for Power Transformer Fault Diagnosis With Dissolved Gas Analysis (DGA): Challenges and Opportunities”. Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering 68 (1): 57-74. https://doi.org/10.33769/aupse.1757488.

EndNote

Açıkgöz N, Sazlı M (June 1, 2026) Comparison of Artificial Intelligence Techniques and Conventional Techniques for Power Transformer Fault Diagnosis with Dissolved Gas Analysis (DGA): Challenges and Opportunities. Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering 68 1 57–74.

IEEE

[1]N. Açıkgöz and M. Sazlı, “Comparison of Artificial Intelligence Techniques and Conventional Techniques for Power Transformer Fault Diagnosis with Dissolved Gas Analysis (DGA): Challenges and Opportunities”, Commun.Fac.Sci.Univ.Ank.Series A2-A3: Phys.Sci. and Eng., vol. 68, no. 1, pp. 57–74, June 2026, doi: 10.33769/aupse.1757488.

ISNAD

Açıkgöz, Nurullah - Sazlı, Murat. “Comparison of Artificial Intelligence Techniques and Conventional Techniques for Power Transformer Fault Diagnosis With Dissolved Gas Analysis (DGA): Challenges and Opportunities”. Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering 68/1 (June 1, 2026): 57-74. https://doi.org/10.33769/aupse.1757488.

JAMA

1.Açıkgöz N, Sazlı M. Comparison of Artificial Intelligence Techniques and Conventional Techniques for Power Transformer Fault Diagnosis with Dissolved Gas Analysis (DGA): Challenges and Opportunities. Commun.Fac.Sci.Univ.Ank.Series A2-A3: Phys.Sci. and Eng. 2026;68:57–74.

MLA

Açıkgöz, Nurullah, and Murat Sazlı. “Comparison of Artificial Intelligence Techniques and Conventional Techniques for Power Transformer Fault Diagnosis With Dissolved Gas Analysis (DGA): Challenges and Opportunities”. Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering, vol. 68, no. 1, June 2026, pp. 57-74, doi:10.33769/aupse.1757488.

Vancouver

1.Nurullah Açıkgöz, Murat Sazlı. Comparison of Artificial Intelligence Techniques and Conventional Techniques for Power Transformer Fault Diagnosis with Dissolved Gas Analysis (DGA): Challenges and Opportunities. Commun.Fac.Sci.Univ.Ank.Series A2-A3: Phys.Sci. and Eng. 2026 Jun. 1;68(1):57-74. doi:10.33769/aupse.1757488