Transformer aging failure rate evaluation method based on evidence theory for operational risk assessment

Author(s):  
Guoqiang Ji ◽  
Wenchuan Wu ◽  
Boming Zhang
2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Cunbin Li ◽  
Gefu Qing ◽  
Peng Li ◽  
Tingting Yin

With the increasing complication, compaction, and automation of distribution network equipment, a small failure will cause an outbreak chain reaction and lead to operational risk in the power distribution system, even in the whole power system. Therefore, scientific assessment of power distribution equipment operation risk is significant to the security of power distribution system. In order to get the satisfactory assessment conclusions from the complete and incomplete information and improve the assessment level, an operational risk assessment model of distribution network equipment based on rough set and D-S evidence theory was built. In this model, the rough set theory was used to simplify and optimize the operation risk assessment indexes of distribution network equipment and the evidence D-S theory was adopted to combine the optimal indexes. At last, the equipment operational risk level was obtained from the basic probability distribution decision. Taking the transformer as an example, this paper compared the assessment result obtained from the method proposed in this paper with that from the ordinary Rogers ratio method and discussed the application of the proposed method. It proved that the method proposed in this paper is feasible, efficient, and provides a new way to assess the distribution network equipment operational risk.


2013 ◽  
Vol 732-733 ◽  
pp. 993-998
Author(s):  
Ke Tian ◽  
Da Hai You ◽  
Yi Long Li ◽  
Kai Pan ◽  
Ke Wang

Firstly, the operating mechanism in developing process of transformer internal latent fault and external accessory fault is analyzed. Then, dissolved gas analysis (DGA) outcome and average degree of polymerization (DP) are used as an indicator to classify transformers operating condition, the multi-state Markov process model based transformers operating condition is proposed to estimate the internal failure rate. According to the method of weather condition classification, the external accessory failure rate model is proposed by considering the influence of weather change. A time-varying transformer outage model for operational risk assessment is proposed by using the multi-state Markov process to estimate the time-varying failure probability. Finally, a numerical is presented.


Author(s):  
Vladislav N. Slepnev ◽  
◽  
Alexander F. Maksimenko ◽  
Elena V. Glebova ◽  
Alla Т. Volokhina ◽  
...  

The choice of risk assessment procedure is one of the essential stages of efficient structuring of processes on prevention, localization and elimination of the consequences of accidents at main pipeline transport facilities. The authors analyzed themed publications and regulatory documents, governing procedures of risk assessment and forecasting of the consequences of possible accidents, and defined main problems in this area. Procedure for the risk assessment of accidents at main pipeline facilities was developed, the basis of which is the expert evaluation method. The procedure includes the determination of the main criteria for the assessment the probability of accident initiation and development and the evaluation of the severity of its consequences, an expert evaluation of criteria significance, their classification, and creation of a rating for hazardous pipeline sections. The application of the procedure application allows to specify the list of facilities that require high priority forecasting of accidents consequences, thus to optimize the distribution of resources and the overall increase of efficiency in planning while defining forces and special technical devices, necessary for containment and rectification of emergencies. Expert evaluation method application allows considering the specifics of certain enterprises, their technical and technological peculiarities, thereby increasing forecasting accuracy.


Author(s):  
Andrea Giacchero ◽  
Jacopo Moretti ◽  
Francesco Cesarone ◽  
Fabio Tardella

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