• Dr. Mihir K Patel
  • Dr. Alpesh M. Patel


In any power system or grid network transformer device use for power from one circuit to another circuit without changing the frequency with high efficiency levels. Due to number of usages Transformer protection is very important now a days for electric supply which is fault free, efficiency and to increase the transformer life cycle. This paper is a brief discussion about the concentration of different gases like CO, CO2, H2, C2H6, C2H4, C2H2 and CH4 related faults which is known as DGA analysis with the help of various classical techniques gives different conditions for the same sample unit. This paper presents MATLAB simulation of ANN and Machine learning based high accuracy design techniques for DGA analysis and the results are compared with the classical techniques like Key Gas Method, IEC Ratio method, Duval triangle Method and Rogers Ratio Method, but in this paper we have done only Duval triangle Method for Comparison using Matlab. The Simulation result of the proposed methods shows that overall DGA analysis using Machine learning algorithm is better than conventional Duval triangle method Performance.

Keywords: DGA, Duval Triangle, IEC Ratio, Rogers Ratio, etc.


Download data is not yet available.


[1] Xiang Zhang, Gockenbach E., ―Asset-management of transformers based on condition monitoring and standard diagnosis,‖ IEEE Electrical Insulation Magazine, vol.24, no. 4, pp. 26-40, 2008.
[2] CIGRE Working Group 12.05, ―An international survey on failures in large power transformers in service,‖ Electra, no. 88, pp. 21-47, 1983.
[3] J. P. Gibeault , J. K. Kirkup, ―Early detection and continuous monitoring of dissolved key fault gases in transformers and shunt reactors,‖ in Proc. Elect. Electronics Insul. Conf., Elect. Manufact. Coil Winding Conf., pp. 285–293, Sep. 1995.
[4] B. Pahlavanpour, A. Wilson, ―Analysis of transformer oil for transformer condition monitoring,‖ in IEE Colloq. Engineer. Rev. Liquid Insul., pp. 1/1–1/5, Jan. 1997.
[5] B. Sparling, J. Aubin, ―Field experience with multigas on-line monitoring of power transformers,”in Proc. IEEE Transmission Distrib. Conf., vol. 2, pp. 895–900, April 1999.
[6] B. Sparling, ―Transformer monitoring and diagnostics,‖ Proceeding of IEEE Power Engineer. Society Winter Power Meeting, vol.2, New York, pp. 978–980, 1999.
[7] J. Lapworth, ―A novel approach (scoring system) for integrating dissolved gas analysis results into a life management system,‖ in Conf. Record of IEEE Int. Symp. Elect. Insul., pp. 137–144, April 2002.
[8] J. Sabau, L. Silberg, Paul Vaillancourt, ―The impact of oil decay on gassing and reliability of aging power transformers,‖ in Annual Reprt Conf. Elect. Insul. Dielect. Phenomena, pp. 408–411, Oct. 2002.
[9] A. Shahsiah, R. C. Degeneff, ―A new dynamic model for propagation of characteristic gases in transformer oil-cellulose structures due to temperature variations,‖ in Annual Report Conf. Elect. Insul. Dielect. Phenomena, pp. 269–272, Oct. 2005.
[10] J. Sabau, R. Stokhuyzen, ―The side effects of gassing in transmission power transformers,‖ in Annual Report Conf. Elect. Insul .Dielect. Phenomena, vol. 1, pp. 264–267, Oct. 2000.
0 Views | 0 Downloads
How to Cite
Patel, D. M. K., & Patel, D. A. M. (2021). SIMULATION AND ANALYSIS OF DGA ANALYSIS FOR POWER TRANSFORMER USING ADVANCED CONTROL METHODS. Asian Journal For Convergence In Technology (AJCT), 7(1), 102-109.