MATH MODELING

Digital predictive identification models for operational parameter dynamics of thermal power generation equipment

M. V. Shlyakhov^a, E. O. Petrenko^b, V. E. Pyatetskii^c, N. N. Bakhtadze<sup>a

a</sup> V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, Moscow, Russia
^b Bauman Moscow State Technical University, Moscow, Russia
^c National University of Science and Technology «MISIS», Moscow

Abstract: The paper presents a method for predicting the health of thermal power plant equipment, such as energy boilers coupled with steam turbines. The models are developed, which indicate the condition of steam superheaters of an energy boiler for a specified control action. Based on realtime prediction, a solution is offered to the problem of boiler efficiency maintenance during design operation as well as repair activities planning over a specified time period.

Keywords: power generation equipment, prediction methods, identification models, associative search.

DOI: 10.14357/20718632250310

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