Application of adaptive neuro fuzzy inference system to support power transformer life estimation and asset management decision

Power transformer is a critical asset in electrical transmission and distribution networks that need to be carefully monitored during its entire operational life. Considering the fact that a significant number of worldwide in-service power transformers have approached the end of their expected operational life, utilities have adopted various transformer condition-based maintenance techniques to avoid any potential catastrophic failure to the equipment. The extent of transformer insulation system ageing can be quantified through measuring several diagnostic indicators such as interfacial tension number of the insulating oil which has a strong correlation with the number of transformer operating years. Moisture and furanic compounds generated due to paper insulation degradation are indicators for solid insulation ageing. This paper introduces a new adaptive neuro fuzzy logic model to estimate the life of mineral oil-filled power transformers based on the values of insulating oil interfacial tension number, furan content in oil and the moisture content within the cellulose insulation. Also, an integrated asset management decision model is proposed. Results of the proposed model are validated against practical data collected from utility and industry mineral oil-filled power transformers of different ratings, designs, operating conditions and lifespans.

[1]  K. S. Kassi,et al.  Impact of local overheating on conventional and hybrid insulations for power transformers , 2015, IEEE Transactions on Dielectrics and Electrical Insulation.

[2]  T. Ross.  Fuzzy Logic with Engineering Applications , 1994 .

[3]  T. Prevost,et al.  Cellulose insulation in oil-filled power transformers: Part I - history and development , 2006, IEEE Electrical Insulation Magazine.

[4]  Michel Duval,et al.  A review of faults detectable by gas-in-oil analysis in transformers , 2002 .

[5]  M. Arshad,et al.  A Novel Fuzzy Logic Technique for Power Transformer Asset Management , 2006, Conference Record of the 2006 IEEE Industry Applications Conference Forty-First IAS Annual Meeting.

[6]  Lotfi A. Zadeh,et al.  Fuzzy logic, neural networks, and soft computing , 1993, CACM.

[7]  Wang Fan,et al.  An approach to power transformer asset management using health index , 2009, IEEE Electrical Insulation Magazine.

[8]  L. Cheim,et al.  Furan analysis for liquid power transformers , 2012, IEEE Electrical Insulation Magazine.

[9]  Wenyu Guo,et al.  A field study of two online dry-out methods for power transformers , 2012, IEEE Electrical Insulation Magazine.

[10]  K. D. Srivastava,et al.  Review of condition assessment of power transformers in service , 2002 .

[11]  Alexander Mamishev,et al.  Moisture equilibrium in transformer paper-oil systems , 1999 .

[12]  A. Abu-Siada,et al.  A new technique to measure interfacial tension of transformer oil using UV-Vis spectroscopy , 2015, IEEE Transactions on Dielectrics and Electrical Insulation.

[13]  T.A. Prevost,et al.  Cellulose insulation in oil-filled power transformers: part II maintaining insulation integrity and life , 2006, IEEE Electrical Insulation Magazine.

[15]  Agustín Santisteban,et al.  Transformer health indices calculation considering hot-spot temperature and load index , 2017, IEEE Electrical Insulation Magazine.

[16]  V. Miranda,et al.  Improving the IEC table for transformer failure diagnosis with knowledge extraction from neural networks , 2005, IEEE Transactions on Power Delivery.

[17]  S. M. Islam,et al.  Significance of cellulose power transformer condition assessment , 2011, IEEE Transactions on Dielectrics and Electrical Insulation.

[18]  Ahmed Abu-Siada,et al.  Correlation of furan concentration and spectral response of transformer oil-using expert systems , 2011 .

[19]  A. Abu-Siada,et al.  Remnant life estimation of power transformer based on IFT and acidity number of transformer oil , 2015, 2015 IEEE 11th International Conference on the Properties and Applications of Dielectric Materials (ICPADM).

[20]  A. Abu-Siada,et al.  A review of dissolved gas analysis measurement and interpretation techniques , 2014, IEEE Electrical Insulation Magazine.

[21]  Daniel Martin,et al.  The effect of acid accumulation in power-transformer oil on the aging rate of paper insulation , 2014, IEEE Electrical Insulation Magazine.

[22]  A. H. El-Hag,et al.  Artificial neural networks with stepwise regression for predicting transformer oil furan content , 2012, IEEE Transactions on Dielectrics and Electrical Insulation.

[23]  A. Abu-Siada,et al.  Fuzzy logic approach to identify transformer criticality using dissolved gas analysis , 2010, IEEE PES General Meeting.

[24]  A. Abu-Siada,et al.  A novel method of measuring transformer oil interfacial tension using UV-Vis spectroscopy , 2016, IEEE Electrical Insulation Magazine.