A dynamic model for optimally phasing in CO ₂ capture and storage infrastructure

CO ₂ capture and storage (CCS) is a climate-change mitigation strategy that requires an investment of many billions of dollars and tens of thousands of miles of dedicated CO ₂ pipelines. To be effective, scientists, stakeholders, and policy makers will have to understand how as well as when to deploy large-scale CCS infrastructure. This will require comprehensive modeling that takes into account detailed costs, engineering, and environmental concerns. We introduce a new and comprehensive model, SimCCS ^TIME, that is capable of spatially and temporally optimizing CO ₂ management-capture, transport, and storage of large quantities of CO ₂. The model minimizes CCS infrastructure costs while simultaneously deciding where, how much, and when to capture, transport, and store CO ₂. We demonstrate the SimCCS ^TIME model using real data from the Texas panhandle. Results show that the model minimizes CCS costs, while meeting rising demand to capture and store CO ₂, by gradually expanding the CCS network. The model identifies non-intuitive cost savings by overbuilding infrastructure in early time periods, and then fully utilizing this infrastructure in later years. Further, results show that there is significant benefit for planning a cooperative and integrated CCS system. Finally, we show how SimCCS ^TIME offers significant advantages over myopic models that cannot integrate infrastructure through time.