72941

Автор(ы): 

Автор(ов): 

2

Параметры публикации

Тип публикации: 

Доклад

Название: 

Digital Twins: Forecasting and Formation of Optimal Control Programs for NPP Power Units

Электронная публикация: 

Да

ISBN/ISSN: 

978-1-6654-6429-1

DOI: 

10.1109/SmartIndustryCon57312.2023.10110766

Наименование конференции: 

  • 2023 International Russian Smart Industry Conference (SmartIndustryCon)

Наименование источника: 

  • Proceedings of the 2023 International Russian Smart Industry Conference (SmartIndustryCon)

Город: 

  • Piscataway

Издательство: 

  • IEEE

Год издания: 

2023

Страницы: 

158-163, https://ieeexplore.ieee.org/document/10110766
Аннотация
Industries, especially in the energy sector, are using digital twins to improve work efficiency and optimize operating modes. Digital twins have based on models that accurately describe the geometry, physical properties, behavior, and rules that characterize an object. The article presents an example of functional decentralization of digital twin models as a decomposition of an NPP power unit (PU) with a VVER-1000 reactor as a control object into a set of technological subsystems of functional groups. Approaches to the digital twins’ creation of NPP PU and the main directions for using digital twins based on dynamic models of a PU in advanced control systems for NPP power units are presented. Within the framework of the intelligent operator support system, a "three-stage" approach to the problem of forecasting the state of the NPP PU, based on digital twins, and the principles of forming the PU optimal control are proposed. The proposed approaches to creating digital twins are used to create intelligent support systems for operators.

Библиографическая ссылка: 

Жарко Е.Ф., Чернышев К.Р. Digital Twins: Forecasting and Formation of Optimal Control Programs for NPP Power Units / Proceedings of the 2023 International Russian Smart Industry Conference (SmartIndustryCon). Piscataway: IEEE, 2023. С. 158-163, https://ieeexplore.ieee.org/document/10110766.