A major aspect of efficient and flexible plant operation is the development of advanced control strategies. Kender et al. 2021  introduced a digital twin of an ASU which contains a pressure-driven detailed dynamic plant model, the virtual ASU, as a core component.
The digital twin allows for the in-silico development of novel control strategies considering the whole operating range of the plant. However, the dynamic plant simulation requires a high computational effort and is therefore not suitable for real-time applications. To address this issue, the adapted edmister model (AEM) presented by Ecker et al. 2019  is used as a basis to develop a model reduction approach for a pressure-driven column model. The resulting dynamic edmister model (DEM) fulfills the high requirements regarding robustness and simulation accuracy while reducing the computational time. In addition, it can be applied for arbitrary column configurations and is incorporated inherently into the virtual ASU to reduce its model granularity utilizing it for applications such as dynamic optimization and nonlinear model predictive control.
 Kender R., Kaufmann F., Rößler F., Wunderlich B., Golubev D., Thomas I., Ecker A. M., Rehfeldt S., Klein H.: Development of a Digital Twin for a Flexible Air Separation Unit Using a Pressure-Driven Simulation Approach. Computers & Chemical Engineering, 151, 107349, 2021
 Ecker A. M., Thomas I., Häfele M., Wunderlich B., Obermeier A., Ferstl J., Klein H., Peschel A.: Development of a new column shortcut model and its application in process optimisation. Chemical Engineering Science, 196, 538-551, 2019
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