The Influence of Modeling Transformer Age Related Failures on System Reliability

The paper investigates the effect of age related failure of power transformers on the identification of most critical transformer sites for system reliability. The end-of-life failure model of power transformers is modified first to integrate loading conditions effect. The adopted Arrhenius-Weibull probability distribution, which represents the effect of thermal stress on the transformer's end-of-life failure, was compared with the commonly used Gaussian probability distribution model. The sensitivity of results to the uncertainty in model parameters is thoroughly assessed, and acceptable level of uncertainty is determined. The results demonstrated the importance of integration of loading conditions into the failure model. The sensitivity analysis revealed that the identification of critical transformer sites is not significantly affected by the uncertainty in the failure model parameters and that approximate ranges of parameters can be used instead of accurate values without significant, if any, loss in accuracy. The case studies were performed on a realistic transmission test system with 154 power transformers.

[1]  Jovica V. Milanovic,et al.  Reliability Based Framework for Cost-Effective Replacement of Power Transmission Equipment , 2014, IEEE Transactions on Power Systems.

[2]  Lin Cheng,et al.  A Hybrid Conditions-Dependent Outage Model of a Transformer in Reliability Evaluation , 2009, IEEE Transactions on Power Delivery.

[3]  S. Skuletic,et al.  Reliability assessment of composite power systems , 2005, Canadian Conference on Electrical and Computer Engineering, 2005..

[4]  Jovica V. Milanovic,et al.  Probabilistic Indicators for Assessing Age- and Loading-Based Criticality of Transformers to Cascading Failure Events , 2014, IEEE Transactions on Power Systems.

[5]  G. Mazzanti,et al.  Bayesian reliability estimation based on a weibull stress-strength model for aged power system components subjected to voltage surges , 2006, IEEE Transactions on Dielectrics and Electrical Insulation.

[6]  Jaime Román Úbeda,et al.  Sequential simulation applied to composite system reliability evaluation , 1992 .

[7]  E. Gockenbach,et al.  LIFE ESTIMATION OF HIGH VOLTAGE POWER TRANSFORMERS , 2011 .

[8]  V. Vittal,et al.  Risk Assessment for Transformer Loading , 2001, IEEE Power Engineering Review.

[9]  Ilaria Losa,et al.  Regulation of continuity of supply in the electricity sector and cost of energy not supplied , 2009 .

[10]  Wenyuan Li,et al.  Risk Assessment Of Power Systems: Models, Methods, and Applications , 2004 .

[11]  V. I. Kogan,et al.  Failure analysis of EHV transformers , 1988 .

[12]  Wenyuan Li Evaluating mean life of power system equipment with limited end-of-life failure data , 2004, IEEE Transactions on Power Systems.

[13]  W. J. McNutt,et al.  Insulation thermal life considerations for transformer loading guides , 1992 .

[14]  Yili Hong,et al.  Prediction of remaining life of power transformers based on left truncated and right censored lifetime data , 2009, 0908.2901.

[15]  Roy Billinton,et al.  Reliability Evaluation of Engineering Systems , 1983 .

[16]  Wenyuan Li,et al.  A Probabilistic Analysis Approach to Making Decision on Retirement of Aged Equipment in Transmission Systems , 2007, 2007 IEEE Power Engineering Society General Meeting.

[17]  Wenyuan Li,et al.  Reliability Assessment of Electric Power Systems Using Monte Carlo Methods , 1994 .

[18]  Chengrong Li,et al.  Data Requisites for Transformer Statistical Lifetime Modelling—Part I: Aging-Related Failures , 2013, IEEE Transactions on Power Delivery.

[19]  F. Rivas-Davalos,et al.  An alternative method for estimating mean life of power system equipment with limited end-of-life failure data , 2009, 2009 IEEE Bucharest PowerTech.

[20]  Peng Wang,et al.  Operational reliability assessment of power systems considering condition-dependent failure rate , 2010 .