An optimization‐based CCUS source‐sink matching model for dynamic planning of CCUS clusters

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.