Improving a qualimetric method for assessing the operational quality of energy facilities by using digital twins
Year: 2026
Type: article
Abstract: This study reports a qualimetric assessment of the performance quality of energy facilities based on the improved information-measurement systems using digital twins. The task addressed relates to the fact that the existing information-measurement system of a power unit at the power plant allows only for the operational control over the current state of the technological process but does not enable preventive assessment and forecasting of critical deviations in technological parameters. A method has been proposed in this work for the qualimetric assessment of energy facilities performance quality by using digital twins, which makes it possible to detect deterioration in the technical condition of energy equipment even before reaching critical parameter values. To implement the qualimetric method for assessing operational quality of an energy object, predictive algorithm stages have been proposed, which make it possible, based on a digital twin, to implement the transition from current reactive control to preventive management. A system of criteria and indicators of qualimetric assessment of operational quality of energy facilities has been compiled, which makes it possible to calculate the integrated predictive index. It has been shown that using a digital twin as part of the TP ACS, the pre-accident state of the turbine is predicted in 1 hour 53 minutes, and the emergency state in 3 hours 26 minutes. This makes it possible to make a timely preventive management decision and prevent the occurrence of an emergency. The results of validating the qualimetric method for assessing the operational quality of a power unit involving simulation models of digital twins under typical operating scenarios showed the correspondence of the quality of turbine operation for different modes of operation of the power unit
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $242
OpenAlex ID: W7204997017