Unveiling cost reduction potential of carbon capture and storage clusters in China under multiple uncertainties

Carbon capture and storage (CCS) plays a pivotal role in China's low-carbon power transition but faces high costs and multiple uncertainties related to technology, policy, and economics. CCS clusters, along with the associated hubs, offer an opportunity to tackle this issue. Therefore, a CCS cluster source-sink matching model was developed based on fuzzy possibility programming and interval linear programming methods under multiple uncertainties. The cluster layout, shared pipeline network, and cost reduction potential were explored. Results show that the North China, Northwest China, East China, and South China regions will be prioritized for the development of CCS cluster projects. Compared to "point-to-point" projects, CCS clusters have great potential to reduce pipeline lengths by [81.5%, 81.8%], and lower the plant-level levelized cost of CCS by [35.7%, 86.9%]. This study provides a system-wide insight for CCS cluster development and cost reduction assessment under multiple uncertainties.