Title: Self-Adaptive Digital Twins for Real-Time Optimization of Thermal Power Systems
Primary area: applications to physical sciences (physics, chemistry, biology, etc.)
Keywords: Keywords: digital twins, self-adaptive systems, intelligently updated energy characteristics, real- time monitoring, combined heat and power plants, optimization

Abstract: The advancement of modern energy systems increasingly depends on the development of self-adaptive 
Digital Twins (DTs) that integrate real-time monitoring data for dynamic model updating. Traditional 
reliance on static Regulatory Technical Documentation (RTD) introduces significant inaccuracies, as 
it does not reflect actual operating states or gradual equipment degradation. To address this, we 
propose a framework for constructing intelligent, self-adaptive digital twins that continuously 
update energy reference performance characteristics (RPCs) based on live data. The presented 
approach enables the creation of DTs that evolve in parallel with the physical system, ensuring high 
fidelity between the virtual and real assets. By implementing algorithms for intelligent 
parameterization, the digital model captures changes in equipment condition and operational 
constraints, providing an accurate and continuously updated representation of combined heat and 
power plants (CHPPs) assets. Experimental validation on industrial data shows that this self-
adaptive modeling process drastically improves accuracy, reducing deviations between calculated and 
actual parameters from 17.4\% to 0.7\% for turbine technological minimum, and from 7.9\% to 1\% for 
unit fuel consumption. This work demonstrates that self-adaptive DTs, capable of monitoring-based 
updating of performance characteristics, are a promising direction for developing digital models 
that remain aligned with real-world conditions. Such DTs provide a robust foundation for advanced 
forecasting, reliable decision support, and sustainable operation of complex energy systems.\\
Keywords: digital twins, self-adaptive systems, intelligently updated energy characteristics, real-
time monitoring, combined heat and power plants, optimization

TL;DR: The article describes an algorithm of a self-parameterizing model for a CHP plant based on real-time process control system parameters