Study On The Condition Evaluation And Reliability Analysis For Transmission And Transformation Equipment

As the development of smart grid and digital substation, the number of power transmission and transformation equipment is increasing dramatically, and the equipment became more intelligent. The traditional maintenance system which is time based maintenance associated with corrective maintenance, has not met the demand of power grid. Condition based maintenance, which works through equipment condition evaluation, reliability analysis, risk assessment and decision-making, is well-directed and effective, and is a kind of economical and reasonable maintenance that worth to be promoted. While equipment condition evaluation and reliability analysis are the basis for is the risk assessment and maintenance decision-making, they are the basic work of condition based maintenance, which is of great importance for today's power industry.This article studied on the following three parts:(1)The electronic instrument transformer condition evaluation level-model, evaluation methods and processes were studied firstly, by learning from the results of condition evaluation research which was taken by state grid corporation of China on power transmission and transformation equipment. Then the quantitative reliability of electronic instrument transformer was calculated which would be made reference for the enterprise in the equipment selection and reliability analysis; (2)Secondly, the failure rate model which based on time and condition was proposed, that meant both of equipment recession information and failure information should be considered. By introducing a time label, an improvement of condition failure rate model was presented, which considered model parameters changing with time; (3) Lastly, all-state integration (ASI) method was proposed to calculate the proportion parameters and the curvature parameter of improved model. ASI is used to study on an integral health process which is with time tag of each device, and follows condition information of integral process. So model parameters are marked with service age. Some of the examples were analyzed and compared using the research result above-mentioned, and the examples results well verified the feasibility and effectiveness of the method presented above.