Research On The Theory Of Reliability And It’s Application Of Power Transformers

As one of the most important power equipment, researches on reliability theory and application of power transformers have very important significance. Proposal of the concept and application of Condition Based Maintenance (CBM) lays the necessary basis for dynamic reliability studies of the power equipment, and development of Life Cycle Management (LCM) technology provides lifetime data for static reliability prediction of the equipment. This paper will use the data conditions above to research on dynamic reliability model in the short-term maintenance decision of transformers and static reliability model as well as its application in the economic life prediction respectively based on theory of reliability. The researches can then provide guidance for the relevant decision-making.This paper has carried on following works:(1) The paper summarizes the typical reliability models of power transformers and analyzes research direction of reliability models (mainly failure rate models) in the background of developments of Smart Grid and Big Data. The proportional hazards model is highlighted;(2) The paper analyzes the factors which influence the failure rate of transformer by considering DGA (Dissolved Gas Analysis) characterized gas content, velocity of total gas production and enlistment age as main influential factors. Then the paper establishes dynamic reliability model based on least-square SVM to predict dynamic failure rate of transformer. At last, a specific case is studied to prove the rationality of chosen factors and model. The result calculated by proposed method is then compared with the result calculated by Markov method, proving that the enlistment age is important factor of internal latent failure of transformer, and transformer dynamic reliability model based on least-square SVM has advantages of faster calculation and higher recognition of monitoring information;(3) Economic life prediction model of transformer based on minimum equivalent annual cost is established. In order to calculate key indicators for the model, life-cycle data of transformer are sorted and some key data are obtained. Then distribution-free proportional hazard model and Monte-Carlo simulation method are used to calculate the failure rate and proportional distribution of outage duration time. Economic life of transformer is then quantitatively predicted after analyzing economic factors and calculating annual maintenance cost, annual interruption cost and annual operation cost. Definition and quantitative forecasting of economic life is still a relatively new study field. The model established in this paper can provide a reference for the study of the economic life of other electrical equipment or systems.