Prognostic assessment of the electric networks functional state using the example of the PJSC Rossetti Volga - Samara distribution networks branch

The analysis of the electric energy transport through the electric networks of the PJSC Rosseti Volga - Samara Distribution Networks branch for the period 2018-2022 was carried out. The structure of the company is considered, the characteristics of the studied electric networks main elements are given, the balance of electric energy transmission in and out of the company’s networks is estimated. Based on the use of statistical forecasting methods, autoregression equations are obtained and preventive values of electricity losses for 2023 for electric networks of various voltage classes are established. Based on the information published in the open press on the accidents in the company’s electrical networks level, an assessment was made of the number of emergencies that occurred during the study period, as well as the amount of under-discharge of the electric energy caused by these interruptions. The influence of the seasonal component on the number of emergencies during the study period is considered. Based on the data for 2022, the analysis of the main causes of damage to the elements of electrical networks and the classification of failures were carried out, their main characteristics for this period were considered. The possibility of using various forecasting methods to assess the preventive values of emergency shutdowns has been evaluated. It is established that the most appropriate method of preventive assessment of emergency shutdowns is the use of a probabilistic method based on the use of a three-parameter power-law gamma distribution. The research uses general scientific methods, numerical methods of analysis, methods of forecasting theory. MATLAB graphics editor technologies were used to visualize the obtained analysis results. The results obtained may be of interest to the heads of power grid companies, as well as researchers and engineers engaged in research in the field of reliability of power supply.