Generalized Method of Mathematical Prototyping of Energy Processes for Digital Twins Development

Sergey Khalyutin (), Igor Starostin and Irina Agafonkina
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Sergey Khalyutin: Department of Electrical Engineering and Aviation Electrical Equipment, Moscow State Technical University of Civil Aviation (MSTU CA), 125993 Moscow, Russia
Igor Starostin: Department of Electrical Engineering and Aviation Electrical Equipment, Moscow State Technical University of Civil Aviation (MSTU CA), 125993 Moscow, Russia
Irina Agafonkina: Department of Chemical Engineering, Ariel University, Ariel 4070000, Israel

Energies, 2023, vol. 16, issue 4, 1-24

Abstract: The use of digital twins in smart power systems at the stages of the life cycle is promising. The dynamics of such systems (smart energy renewable sources, smart energy hydrogen systems, etc.), are determined mainly by the physical and chemical processes occurring inside the systems. The basis for developing digital twins is reliable mathematical models of the systems. In the present paper, the authors present a method of energy processes mathematical prototyping—an overall approach to modeling processes of various physical and chemical natures based on modern non-equilibrium thermodynamics, mechanics, and electrodynamics. Controlled parameters are connected with measured ones by developing a theoretically correct system of process dynamics equations with accuracy up to the experimentally studied properties of substances and processes. Subsequent transformation into particular mathematical models of a specific class of systems makes this approach widely applicable. The properties of substances and processes are given in the form of functional dependencies on the state of the system up to experimentally determined constant coefficients. The authors consider algorithms for identifying the constant coefficients of the functions of substances and processes properties, which complement the proposed unified approach of designing models of various physical and chemical nature systems.

Keywords: mathematical prototyping method; energy processes; systems identification; symbolic regression; digital twins (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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