Levelized-cost optimal design of long-distance CO₂ transportation facilities

With the need to develop carbon-neutral technologies and reduce greenhouse gas emissions to avert climate change, carbon capture, storage and utilization (CCS/CCUS) techniques have emerged as effective pathways to achieve these targets. Despite being a critical aspect of CCS/CCUS chains, carbon dioxide transport is an astonishingly under-researched domain. This study presents an efficient and robust computational model to cost-optimally design of long distance carbon dioxide transport pipelines (trunk) connecting a source-sink pair. Several physical and topographical conditions have been accounted for to propose optimal design solutions for different case studies. This involves right-sizing of pipes and booster stations and placing the latter at the right locations. The implications of uncertainties in modelling of the costs have also been studied. The model is very flexible and general in the sense that it can work with a variety of cost models and design constraints. Further, unlike most studies, an appropriate hydrodynamic model for pressure and density calculations has been incorporated. Genetic algorithm and interior point methods have been employed to find optimal design parameters that minimize the “per ton levelized transportation cost”, and their performances have been compared. Results demonstrate that pipe diameters and elevation changes have the most significant impact on the pressure drop, optimal design parameters and the cost. Lastly, several improvements have been made over our previous study in this domain.