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

Abstract

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.</p