Remote monitoring and control of the status of transformers in distribution electrical networks

Abstract

   RELEVANCE. One of the most important expected effects of digitalization of objects of the power grid complex of the Russian Federation is to increase the level of reliability of its functioning. In this regard, research and development in this direction is undoubtedly relevant.   THE PURPOSE. To propose a mathematical model for monitoring dangerous developing defects in power oil-filled transformers, this would meet the properties of predictability and adaptability. Based on the model, to develop a decision-making algorithm for long-term reliable operation oftransformers.   METHODS: Methods of statistical pattern recognition theory, correlation analysis and Bayesian classification will be used to solve the problems to ensure high reliability of diagnostic assessments, validity and effectiveness of operational solutions.   RESULTS. A predictive model was obtained and verified in the form of a correlation function of a sign of a faulty state of a transformer from the values of its electrical load. An event tree has been formed that restores the causal relationship between the result of monitoring the transformer, the defect sign and the operational decision being made. Based on the event tree and diagnostic evaluation criteria, a control algorithm is implemented, with the help of which calculations are performed confirming the effectiveness of the proposed approach.   CONCLUSION. The possibility of effective application of the developed defect recognition model and operational control algorithm as tools of industrial technology of the Internet of Things is illustrated, in particular, when organizing remote diagnostic monitoring of oil-filled transformer equipment at substations of the distribution grid area.