A method for Generating a Digital Twin Structure for a System for Organizing Preventive Maintenance in the Electricity Sector

In order to detect equipment faults at an earlier stage, when the very beginning of fault development occurs, it is necessary to perform diagnostic inspections of equipment units. Diagnostic control includes both proactive and predictive maintenance. The article considers the improvement of energy saving control system of a production enterprise for effective implementation of energy saving policy. A model for control of energy saving management and energy efficiency improvement is developed. The article builds the abstract model of the neural network node of scheduling preventive maintenance, which can also be applied to automate other business processes in the electric power industry. A model of digital twin system of organization of preventive maintenance in the electric power industry, which will make it possible to analyze the criticality of the equipment. This analysis is based on assessing the impact of each individual piece of equipment on business results, which will ensure that the impact on safety; on the environment; on product quality; on suppliers; on the process.