A Novel Source–Sink Matching Optimization Model for Carbon Capture and Storage

In carbon capture and storage system (CCS), the task of the CO₂ source–sink matching involves optimising source–sink cluster deployment, transportation path, and pipe network layouts. This task is an integral aspect of the CCS commercialization process and constitutes a combinatorial optimization problem aimed at achieving low cost and maximum storage capacity within the system. Here, a novel mathematical model of source–sink matching combinatorial optimization is established. (1) The model can account for various factors, including the lifespan of the source–sink, the capture (injection) rate of CO₂ sources (sinks), and the duration of the CCS system. The objective aimed to maximise CO₂ storage capacity while minimising transportation costs over the entire operational period. Additionally, based on genetic algorithm, a rapid solution approach was introduced to address the objective. (2) A comparative study was conducted through existing cases. The results show that, compared to the Pinch analysis method, the newly constructed optimization model in Case 1 can increase the total storage of the system by 4.6%. Similarly, the results of Case 2 demonstrate that the matching results of the new model can increase the total storage by 13.3%. (3) Through Case 3, the model provides a preferred but not unique matching scheme, which meets the criteria of maximising storage while minimising transportation costs at any given time. Finally, the practicability and reliability of the novel model were verified through the cases. The model can provide a framework for the development of source–sink matching decision system and CCS planning.