An optimization‐based CCUS source‐sink matching model for dynamic planning of CCUS clusters
Qian Wu, Qianguo Lin, Qiang Yang, Yang Li
Abstract
Abstract Carbon capture, utilization and storage (CCUS) is a critical technology option in achieving large‐scale CO 2 mitigation for power and industrial sectors. A full‐chain CCUS cluster could be formed based on numerous scattered capture sources and one or more storage sites connected by a pipeline network. Reasonable source‐sink matching planning for a full‐chain CCUS cluster could substantially reduce the system overhead. However, most of the previous studies could hardly address the dynamic source‐sink matching planning problem of a full‐chain CCUS cluster with multiple types of emission sources and sinks during multiple periods. Therefore, the objective of this study is to investigate an optimized source‐sink matching scheme within a CCUS cluster through developing an optimization‐based CCUS source‐sink matching model. The proposed model is based on multistage mixed integer linear programming techniques with the objective of least‐cost strategy; thus, it can deal with dynamics of capacity expansion associated with CCUS activities. The developed method is then applied to a CCUS cluster facing long‐term dynamic planning issues. The modeling results suggest that the optimization‐based CCUS source‐sink matching model is applicable in reflecting dynamics of time, scale and location of CO 2 capture, transportation and storage within a CCUS cluster. The obtained solutions can provide decision bases for formulating an optimal planning scheme of a full‐chain CCUS cluster under evolving reduction targets or constraints. © 2022 Society of Chemical Industry and John Wiley & Sons, Ltd.