An Alternative Approach for Oil-immersed High Voltage Power Transformer Dissolved Gas Analysis Diagnostic Techniques

Authors

DOI:

https://doi.org/10.11113/elektrika.v18n2.123

Keywords:

Power transformer, Fault diagnosis, DGA, Fuzzy Logic, neural network

Abstract

This article presents alternative analyzing method of extracted dissolved gases related to insulating oil of power transformers. Analysis of soluble and free gas is one of the most commonly used troubleshooting methods for detecting and evaluating equipment damage. Although the analysis of oil-soluble gases is often complex, it should be expertly processed during maintenance operation. The destruction of the transformer oil will produce some hydrocarbon type gases. The development of this index is based on two examples of traditional evaluation algorithms along with fuzzy logic inference engine. Through simulation process, the results of the initial fractures in the transformer are obtained in two ways by the "Duval Triangle method†and "Rogers’s ratios". In continue, three digit codes containing the fault information are created based on the fuzzy logic inference engine to achieve better results and eliminate ambiguous zones in commonly used methods, especially in the “Duval Triangle methodâ€. The proposed method is applied to 80 real transformers to diagnose the fault by analyzing the dissolved oil based on fuzzy logic. The results illustrate the proficiency of this alternative proposed algorithm. Finally, with utilization of a neural network the alternative practical inference function is derived to make the algorithm more usable in the online condition monitoring of power transformers.

References

D. R. Morais, "Ferramenta inteligente para detecção de falhas incipientes em transformadores baseada na análise de gases dissolvidos no óleo isolante," 2004.

E. Dornenburg and O. Gerber, "Analysis of dissolved and free gases for monitoring performance of oil-filled transformers," Brown Boveri Rev, vol. 54, pp. 104-111, 1967.

B. Barraclough, E. Bayley, I. Davies, K. Robinson, R. Rogers, and E. Shanks, "CEGB experience of the analysis of dissolved gas in transformer oil for the detection of incipient faults," in IEE Conference Publication, 1973.

R. Rogers, "UK Experience in the interpretation of incipient faults in power transformers by dissolved gas-in-oil chromatographic analysis," in Doble Conference Index of Minutes, 1975, pp. 10-201.

C. E. Lin, J.-M. Ling, and C.-L. Huang, "An expert system for transformer fault diagnosis using dissolved gas analysis," IEEE transactions on Power Delivery, vol. 8, pp. 231-238, 1993.

R. R. de Aquino, M. M. Lira, T. Filgueiras, H. Ferreira, O. N. Neto, A. M. Silva, et al., "A fuzzy system for detection of incipient fault in power transformers based on gas-in-oil analysis," in Fuzzy Systems (FUZZ), 2010 IEEE International Conference on, 2010, pp. 1-6.

H.-T. Yang, C.-C. Liao, and J.-H. Chou, "Fuzzy learning vector quantization networks for power transformer condition assessment," IEEE Transactions on Dielectrics and Electrical Insulation, vol. 8, pp. 143-149, 2001.

T. Committee, "IEEE guide for the interpretation of gases generated in oil-immersed transformers," Institute of Electrical & Electronics Engineers, Inc., NY, 1992.

M. Duval, "A review of faults detectable by gas-in-oil analysis in transformers," IEEE electrical Insulation magazine, vol. 18, pp. 8-17, 2002.

T. M. Barbosa, M. A. F. Finocchio, J. G. Ferreira, and W. Endo, "Development of software based of the Duval Triangle method," in Industry Applications (INDUSCON), 2016 12th IEEE International Conference on, 2016, pp. 1-8.

J. Tang; F. Meng, "An approach to interval-valued intuitionistic fuzzy decision making based on induced generalized symmetrical Choquet Shapley operator", Scientia Iranica journal, pp. 1456-1470, 2018.

M. Najafi, H. Haghighi and T. Zohdi Nasab" A survey on

formal, object-oriented program development approaches ", Scientia Iranica journal, pp. 1001-1017, 2015.

M. Amjadzadeh, K. Ansari-Asl," An Innovative Emotion Assessment using Physiological Signals Based on The Combination Mechanism" Scientia Iranica journal, pp. 3157-3170, 2017.

A. Shemshadi, et al., “Dielectric Recovery Process in Vacuum Interrupters Regarding to Contact Materials during Post Arc Intervalâ€, IEEE Transactions on Dielectrics and Electrical Insulation, Vol. 22, No. 5; pp. 3059-3064, 2015.

A. Shemshadi, S. Jalali Kashani, “The Requisition of Auto Synchronism for Vacuum Interrupters during Quenching Arc Intervalâ€, Latin American Applied Research, Vol. 48, pp. 1-5, 2018. [18]

S. Alipour, M. Ghodsi, and Amir Jafari,

"Randomized approximation algorithms for planar visibility counting problemâ€, theoretical computer science, Vol. 707, Pages 46-55, 2018.

M. Rahnavard, S. M. H. Alavi, S. Khorasani, M. Vakilian, M. Fardmanesh," Educational Robot for Principles of Electrical Engineering", Scientia Iranica journal, pp. 1582-1592, 2018.

S. Bahrani, M. Razavi, J. A. Salehi," Crosstalk Reduction in Hybrid Quantum-Classical Networks", Scientia Iranica journal, pp. 2898-2907, 2016.

M. H. Abdi, N. B. Ibrahim, H. Baqiah, S.A. Halim," Structural, electrical, and magnetic characterization of nickel-doped tin oxide film by a sol–gel method", Scientia Iranica journal, pp. 2459-2467, 2014.

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Published

2019-08-31

How to Cite

Mehrabadi, A. K., Shemshadi, A., & Shateri, H. (2019). An Alternative Approach for Oil-immersed High Voltage Power Transformer Dissolved Gas Analysis Diagnostic Techniques. ELEKTRIKA- Journal of Electrical Engineering, 18(2), 1–7. https://doi.org/10.11113/elektrika.v18n2.123

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