This work presents a systematic methodology to determine in real-time the optimal durations of the three stages of a new Ca-Cu looping process for H2 production with integrated CO2 capture. Economic and quality criteria are proposed to determine the appropriate time to switch between the stages. These criteria rely on the time-profiles of some key variables, such as product concentrations. Given the delayed nature of hardware sensor measurements, the real-time determination of such variables is based on soft-sensors. For this purpose, Gaussian Process Regression models are employed. The predictive capabilities of these models are tested on several datasets, yielding reliable predictions in most of the cases. The values of the optimal switching times computed with the proposed method differ from the actual values by 4 %, at most.
|Tijdschrift||Computer Aided Chemical Engineering|
|Status||Gepubliceerd - 25 jul 2019|
|Evenement||29th European Symposium on Computer Aided Process Engineering (ESCAPE 29) - Evoluon, Eindhoven, Nederland|
Duur: 16 jun 2019 → 19 jun 2019