Authors:
Gorka Sorrosal Yarritu, Cristina Martín Andonegui, Cruz Enrique Borges Hernández, Ana María Macarulla Arenaza, Ainhoa Alonso Vicario

Abstract:

This paper presents a strategy for the optimisation of the operational conditions of the catalytic transformation of Bioethanol into Olefins (BTO) process. The variables to optimise are the main operating variables of the process (temperature, space-time and water content in the feed), and the objective function is to maximise the total production of olefins. The proposed strategy is based on evolutionary algorithms guided by surrogate models used to simulate the process behaviour under different experimental conditions. This paper compares the optimisation results of the BTO process obtained using an existing mechanistic model with those obtained with a surrogate model. The results suggest that the proposed methodology achieves similar results than those using mechanistic models but 43 times faster. This is a preliminary study where only constant set points have been tested; further research will include dynamic optimisation of the operational conditions by testing expected dynamic trajectories for each operating variable.



Proceedings:
Citation
Gorka Sorrosal Yarritu, Cristina Martín Andonegui, Cruz Enrique Borges Hernández, Ana María Macarulla Arenaza, Ainhoa Alonso Vicario. "An optimisation strategy for the catalytic transformation of bioethanol into olefins using computational intelligence" In .