Digital twin of heat exchange station

Abstract

The article describes the identification of a heat exchanger system using PLC for measurement, followed by system model identification and reconstruction in Matlab Simulink and SIMIT. The root-mean-square error of the identified system was 2.49 % on training data and 5.33 % in the validation scenario. The system model is suitable for predicting and simulating errors and anomalies; it can be used for the optimisation of control processes or system parameters. Therefore, the model can serve as an educational tool, allowing training of students, operators and other experts. They can experiment without fear of damaging components and without having to wait for the long-time transients of a real system.The article describes the identification of a heat exchanger system using PLC for measurement, followed by system model identification and reconstruction in Matlab Simulink and SIMIT. The root-mean-square error of the identified system was 2.49 % on training data and 5.33 % in the validation scenario. The system model is suitable for predicting and simulating errors and anomalies; it can be used for the optimisation of control processes or system parameters. Therefore, the model can serve as an educational tool, allowing training of students, operators and other experts. They can experiment without fear of damaging components and without having to wait for the long-time transients of a real system.