Continuous-time optimization model for source-sink matching in carbon capture and storage systems

Carbon capture and storage (CCS) is widely considered to be an essential technology for reducing carbon dioxide (CO ₂) emissions from sources such as power plants. It involves isolating CO ₂ from exhaust gases and then storing it in an appropriate natural reservoir that acts as a sink. Therefore, CCS is able to prevent CO ₂ from entering the atmosphere. In this work, a continuous-time mixed integer nonlinear programming (MINLP) model for CO ₂ source-sink matching in CCS systems is developed; the initial model is then converted into an equivalent mixed integer linear program (MILP). It is assumed that in CCS systems, CO ₂ sources have fixed flow rates and operating lives, while CO ₂ sinks have an earliest time of availability and a maximum CO ₂ storage capacity. Thus, the resulting optimization model focuses on important physical and temporal aspects of planning CCS. The usefulness of the model is illustrated using two case studies.