Railway Power Transformer Reliability Evaluation Model Based on Operating Conditions

  • Juan Zhang
  • Zhensheng Wu
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 287)


Evaluating the railway power supply system reliability needs accurate failure rate models of equipment. However, the existing failure rate model can’t reflect the effect of the operating conditions and maintenance conditions of equipment. In this paper, a time-varying failure rate model of railway (35)10kV power transformer is proposed according to the Weibull distribution, considering the factors of altitude, ambient temperature, and maintenance conditions. The model also considers the manufactory correction factor obtained from the historical data. The results show that for different combinations of factors, the failure rate curves of transformers are different. The model proposed can present the relationship between the failure rate of transformers and the parameters of operating conditions and the maintenance situation. Hence, it is more applicable for reliability evaluation of the whole railway power supply system, which can provide support for formulating maintenance plan and scheduling field operation.


Altitude Ambient temperature Maintenance situation Equivalent operating time Failure rate model Manufacturer’s correction factor 



This work is supported by basic scientific research funded projects of Beijing Jiao tong University (No. 2012JBM100).


  1. 1.
    Han BJ, Fan XM, Ma DZ (2003) Optimal policy research of preventive maintenance in finite time horizon. J Shanghai Jiaotong University 37(05):679–680 (in Chinese)Google Scholar
  2. 2.
    Liu HT, Cheng L, Sun YZ, Wang P (2007) Outage factors analysis and outage rate model of components based on operating conditions. Autom Electr Power Syst. 31(7):8Google Scholar
  3. 3.
    He J, Sun YZ, Wang P et al (2009) A hybrid conditions-dependent outage model of a transformer in reliability evaluation. IEEE Trans Power Deliv 24(4):2025–2033CrossRefMathSciNetGoogle Scholar
  4. 4.
    Li QY, Xie ZC (2006) Analysis on the characteristics of the vertical lapse rates of temperature-taking Tibetan plateau and its adjacent area as an example. J Shihezi University (Nat Sci) 24(6):719–723 (in Chinese)Google Scholar
  5. 5.
    Li CS, Li XY, Liu ZH et al (2012) Analysis of influence of altitude to temperature of transformer oil. Transformer 49(4):26–27 (in Chinese)Google Scholar
  6. 6.
    Du L, Yuan L, Xiong H et al (2010) Insulation life assessment of power transformer thermal characteristics using Monte Carlo simulation. High Voltage Eng 36(4):007 (in Chinese)Google Scholar
  7. 7.
    Liao RJ, Sun HG, Gong J et al (2011) Aging kinetic model and life time model of oil-paper insulation in transformers. High Voltage Eng 37(7):004 (in Chinese)Google Scholar
  8. 8.
    Li J, Dong LW, Zhao H (2007) Assessment of ageing and life time of oil-immersed transformers. High Voltage Eng 33(3):186–187 (in Chinese)Google Scholar
  9. 9.
    Abu-Elanien AEB, Salama MMA, Bartnikas RA (2011) Techno-economic method for replacing transformers. IEEE Trans Power Deliv 26(2):817–829CrossRefGoogle Scholar
  10. 10.
    Guo YJ (2001) New methodology for life time evaluation of medium and small sized power transformer. Autom Electr Power Syst 25(21):38–41 (in Chinese)Google Scholar
  11. 11.
    Pan LZ, Zhang Y, Yu GQ (2010) Prediction of electrical equipment failure rate for condition-based maintenance decision-making. Electr Power Autom Equip 30(2):91–94 (in Chinese)Google Scholar
  12. 12.
    Zhao Y, Yang J, Ma XB (2009) Tutorials of reliability data analysis. Beijing University of Aeronautics and Astronautics Press, Beijing, pp 8–12Google Scholar
  13. 13.
    Ren LM (2009) Essential knowledge guideline of reliability engineering. China Standards Press, Beijing, pp 106–120Google Scholar
  14. 14.
    Ding M, Luo CT (1991) Calculation of the reliability indices for operation reserve. Proc CSEE 11(3):51–58 (in Chinese)Google Scholar
  15. 15.
    Zhao Y, Zhou JQ, Zhou NC et al (2006) Analytical approach for bulk power systems reliability assessment. Proc CSEE 26(5):19–25 (in Chinese)Google Scholar
  16. 16.
    Guo YJ (2003) Power system reliability analysis. Tsinghua University Press, Beijing, pp 169–171 (in Chinese)Google Scholar
  17. 17.
    Gulachenski EM, Besuner PM (1990) Transformer failure prediction using Bayesian analysis. IEEE Trans Power Syst 5(4):1355–1363CrossRefGoogle Scholar
  18. 18.
    Wan H, MccaHey JD, Vittal V (1999) Increasing thermal rating by risk analysis. IEEE Trans Power Syst 14(3):815–828CrossRefGoogle Scholar
  19. 19.
    Sun YZ, Cheng L, Liu HT (2005) Power system operating reliability evaluation based on real-time operating state. Power Syst Technol 29(15):7–8 (in Chinese)Google Scholar
  20. 20.
    Ji GQ, Zhang BM, Wu WC et al (2013) A time-varying component outage model for power system reliability analysis. Proc CSEE 33(1):57–58 (in Chinese) Google Scholar
  21. 21.
    Sun YZ, Zhou JQ (2012) Basic theory of online running reliability of large interconnected power grid. Tsinghua University Press, Beijing, pp 48–51(in Chinese) Google Scholar
  22. 22.
    Sun P, Chen SH, Zhang CQ (2012) Assessment of failure rate for substation equipment life cycle based on Marquardt parameter estimation method. Power Syst Prot Control 40(1):85–90 (in Chinese)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.School of Electrical EngineeringBeijing Jiaotong UniversityBeijingChina

Personalised recommendations