An inexact optimization model for planning regional carbon capture, transportation and storage systems under uncertainty

Abstract

CO2 capture and storage (CCS) is widely recognized as a climate-change mitigation technology that can significantly sequestrate human-induced CO2 emission. However, there are two main issues that affect the development and deployment of CCS in a region/country: one is the shortage of planning tool for supporting effective decision making regarding timing, sitting and scaling of CCS capture, transport and storage facilities as well as dynamic sink-source matching between capture and storage. The other is uncertainty in technical, economic, political and other dimensions of CCS as the technology is still in early stage of commercialization. Therefore, the objective of this study is to develop an inexact CCS optimization model (ICCSM) for supporting regional carbon capture, transportation and storage planning under interval-format uncertainty with a least-cost strategy. It could address issues related to optimal sink-source matching in a region with multiple capture and storage options. The developed model was then applied to a case study of long term regional CCS planning under uncertainty. To demonstrate its applicability and capability, further scenario analysis indicated that high concentration CO2 from coal-to-chemical/liquids/gas for EOR storage would be early opportunity for CCS in China. In addition, carbon price would be an effective policy instrument for encouraging deployment of CCS. Without sufficient carbon price, it could be difficult for moving CCS from demonstration stage to deployment stage in a short term.