Dissolved Gas Analysis: A Proactive Approach for Recognization of Faults in Transformer using MATLAB GUI

  • Simon Babukutty PG Student, Electrical Engineering Dept., Pune University Matoshri College of Engineering and Research Centre Nashik, India
  • S.S. Khule HOD, Electrical Engineering Department Matoshri College of Engineering and Research Centre Nashik, India

Abstract

Transformer plays an important role in Power transmission network. For a reliable power supply utmost attention is required. The mineral oil employed is exposed to high thermal and electrical stresses and thus gasses are formed due putrefaction of the mineral oil. To reduce the failure in transformers diagnosis of mineral oil for faults needs to be carried out. The Dissolved gas analysis (DGA) is used for assessment of oil for liquified gases formed due to faults. DGA involves five classical methods Key Gas Method, IEC Ratio method, Rogers Ratio Method, Doernenburg Ratio Method and Duval triangle Method. This paper presents a MATLAB GUI for five classical methods with 93% accuracy when compared to reliable individual method of 83% accuracy.              


How to cite this article:
Babukutty S, Khule SS. Dissolved Gas Analysis: A
Proactive Approach for Recognization of Faults
in Transformer using MATLAB GUI. J Adv Res Sig
Proc Appl 2019; 1(2): 23-28.

References

[1] IEEE Std. C57.104-2008. IEEE Guide for the Interpretation of Gases Generated in Oil-Immersed Transformers. Institute of Electrical and Electronics Engineers, Inc., New York. 2008: 9–27.
[2] ANSI/IEEE Std C57.104-1991. "IEEE Guide for the Interpretation of Gases Generated in Oil-Immersed Transformers". IEEE Power Engineering Society. 1992.
[3] Osama E. Gouda, Saber M. Saleh, Salah Hamdy EL-Hoshy, “Power Transformer Incipient Faults Diagnosis Based on Dissolved Gas Analysis” ijeecs.v1.i1.pp10-16 DOI: 10.11591, January-2016
[4] N.A. Muhamad, B.T. Phung, T.R. Blackburn, K.X Lai, “Comparative Study and Analysis of DGA Methods for Transformer Mineral Oil” IEEE Lausanne Power Tech, July 2007
[5] Siva Sarma, D.V.S.S. and G.N.S. Kalyani, “ANN Approach for Condition Monitoring of Power Transformers using DGA”. 2004 IEEE Region 10 Conference, TENCON 2004., 2004. C: p. 444- 447.
[6] Abubakar A. Suleiman, Ali S. Alghamdi, Nor Asiah Mohamad, Nouruddeen Bashir, Mohd Aizam, “Improving accuracy of DGA interpreation of oil-filled power transformers needed for effective condition monitoring”, IEEE International Conference on Condition Monitoring and Diagnosis, 23-27 September 2012.
[7] Andri Febriyanto, Tapan Kumar Saha, “Oil-immersed Power Transformers Condition Diagnosis with Limited Dissolved Gas Analysis (DGA) Data”, Australasian Universities Power Engineering Conference (AUPEC), pp-073, 2008.
[8] ANSI/IEEE Std C57.104-1991, “IEEE Guide for the Interpretation of Gases Generated in Oil-Immersed Transformers”, IEEE Power Engineering Society, 1992
[9] Sherif S. M.Ghoneim, IEEE Member, Sayed A. Ward, “ Dissolved gas Analysis an Early Identification of Transformer Faults”, Advances in Electrical Engineering Systems (AEES), Vol. 1, No. 3, 2012, ISSN 2167-633X
[10] FIST3-31, Facilities Instructions, Standards and Techniques Volume 3-31 Transformer Diagnostics. 2003, Bureu of Reclamation Hydroelectric Research and Technical Services Group Denver. p. 5-13
[11] M. Duval and A. de-Pabla, "Interpretation of gas-in-oil analysis using new IEC publication 60599 and IEC TC 10 databases," IEEE Dielectrics and Electrical Insulation Society Electrical Insulation Magazine vol. 17, 2001 [DOI: http://dx.doi.org/10.1109/57.917529]
[12] IEEE Std. C57.104-2008. IEEE Guide for the Interpretation of Gases Generated in Oil-Immersed Transformers. Institute of Electrical and Electronics Engineers, Inc., New York. 2008: 9–27.
Published
2021-10-03
How to Cite
BABUKUTTY, Simon; KHULE, S.S.. Dissolved Gas Analysis: A Proactive Approach for Recognization of Faults in Transformer using MATLAB GUI. Journal of Advanced Research in Signal Processing and Applications, [S.l.], v. 1, n. 2, p. 14-19, oct. 2021. Available at: <http://thejournalshouse.com/index.php/SignalProcessing-Applications/article/view/441>. Date accessed: 19 may 2024.