Mean Life Assessment and Prediction of the Failure Probability of Combustion Turbine Generating Unit with Data Analytic Method Based on Aging Failure Data

통계적 분석방법을 이용한 복합화력 발전설비의 평균수명 계산 및 고장확률 예측

  • Published : 2005.10.01

Abstract

This paper proposes a method to consider an aging failure probability and survival probability of power system components, though only aging failure probability has been considered in existing mean life calculation. The estimates of the mean and its standard deviation is calculated by using Weibull distribution, and each estimated parameters is obtained from Data Analytic Method (Type H Censoring). The parameter estimation using Data Analytic Method is simpler and faster than the traditional calculation method using gradient descent algorithm. This paper shows calculation procedure of the mean life and its standard deviation by the proposed method and illustrates that the estimated results are close enough to real historical data of combustion turbine generating units in Korean systems. Also, this paper shows the calculation procedures of a probabilistic failure prediction through a stochastic data analysis. Consequently, the proposed methods would be likely to permit that the new deregulated environment forces utilities to reduce overall costs while maintaining an are-related reliability index.

Keywords

References

  1. Wenyuan Li, 'Incoporating aging failures in power system reliability evaluation', IEEE Trans. on Power System, Vol.17, pp.918-923, August. 2002 https://doi.org/10.1109/TPWRS.2002.800989
  2. Wenyuan Li, 'Evaluating mean life of power system equipment with limited end-of-life failure data', IEEE Trans. on Power System, Vol.19, No.1, February 2004 https://doi.org/10.1109/TPWRS.2003.821434
  3. R. Billinton and R. N. Allan, 'Reliability evaluating of engineering system', Plenum Press, 1992
  4. S. S. Rao, 'Engineering optimization', A Wiley-Intersection Publication, 1995
  5. M. J. Crowder, A. C. Kimber, R. L. Smith and T. J. Sweeting, 'Statistical analysis of reliability data', Chapman and Hall, 1991
  6. R. M. Bucci, R. Y. Rebbapragada, A. J. McElroy, E . A. Chebli and S. Driller, 'Failure prediction of underground distribution feeder cables', IEEE Transactions on Power Delivery, vol.9, No.4, October 1994 https://doi.org/10.1109/61.329501