DOI:10.1007/s40565-017-0322-z |
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Applications of survival functions to continuous semi-Markov processes for measuring reliability of power transformers |
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Net amount: 864 |
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Author:
Yifei WANG1, Mohammad SHAHIDEHPOUR2, Chuangxin GUO3
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Author Affiliation:
1 School of Automation, Guangdong University of Technology, Guangzhou 510006, China 2 Galvin Center for Electricity Innovation, Illinois Institute of Technology, Chicago, IL 60616, USA 3 College of Electrical Engineering, Zhejiang University, Hangzhou 310058, China
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Abstract: |
The reliability of power transformers is subject to service age and health condition. This paper proposes a practical model for the evaluation of two reliability indices: survival function (SF) and mean residual life (MRL). In the proposed model, the periodical modeling of power transformers are considered for collecting the information on health conditions. The corresponding health condition is assumed to follow a continuous semi-Markov process for representing a state transition. The proportional hazard model (PHM) is introduced to incorporate service age and health condition into hazard rate. In addition, the proposed model derives the analytical formulas for and offers the analytical evaluation of SF and MRL. SF and MRL are calculated for new components and old components, respectively. In both cases, the proposed model offers rational results which are compared with those obtained from comparative models. The results obtained by the contrast of the proposed analytical method and the Monte Carlo method. The impact of different model parameters and the coefficient of variation (CV) on reliability indices are discussed in the case studies. |
Keywords: |
Power system reliability, Transformers, Proportional hazard model, Survival function, Mean residual life, Semi-Markov process |
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Online Time:2017/11/27 |
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