An MINLP model for the optimal design of CO2 transportation infrastructure in industrial clusters

• Published in: Computer Aided Chemical Engineering Vol. 52; pp. 3085 - 3090
• Main Authors: Ejeh, Jude O., Martynov, Sergey B., Brown, Solomon F.
• Format: Book Chapter
• Language: English
• Published: 2023
• Subjects: CCUS industrial clusters; CO2 transport infrastructure; MINLP; Optimisation; MINLP; Optimisation; CO2 transport infrastructure; CCUS industrial clusters
• ISBN: 9780443152740; 0443152748
• ISSN: 1570-7946
• DOI: 10.1016/B978-0-443-15274-0.50492-3

Carbon capture, utilisation and storage (CCUS) is still the most promising decarbonisation route for carbon-intensive sectors. In the context of industrial clusters, although benefits exist from economies of scale and shared transportation infrastructure, challenges remain relating to planning and investing in large-scale implementations. This involves the optimal sizing of the transportation infrastructure to avoid underestimating the transported amounts that could lead to stranded emitters or overestimating the capacity that would translate to financial losses due to unjustified capital expenditures. In this work, a mixed integer non-linear programming (MINLP) model for the design of carbon dioxide (CO2) transportation infrastructure in industrial clusters is proposed. The optimisation model considers a set of CO2 emitters, available potential CO2 transport and storage/utilisation options, etc. to obtain the detailed infrastructure design. The model assumes a transportation mode solely by pipelines, with steady-state fluid flow throughout the period of consideration. With an overall (capital and operating) cost minimisation objective, globally optimal network design results are obtained for candidate emitters and network routes within industrial clusters subject to constraints relating to storage balances, nominal pipe selection, and pipeline/fluid flow equations.