Optimal revamp of multi-region carbon capture and storage (CCS) systems by two-step linear optimization

CO\(_{2 }\) capture and storage (CCS) is considered as an important technology which involves capturing CO\(_{2 }\) from sources and injecting it into geological reservoirs for permanent storage. In planning large-scale CCS systems, CO\(_{2 }\) sources need to be matched with geological sinks to maximize the reduction of CO\(_{2 }\) emissions. However, due to the long planning horizons of CCS systems, new information may arise or unexpected events may occur that necessitate network revamp. For example, new sources may come into existence, new sinks may be discovered, or existing sinks may prove to be structurally unsound. In this work, a revamp strategy using two-step linear optimization is developed, in which the trade-off between the cost of network modification and the objective of CO\(_{2}\) emissions reduction by sequestration is balanced. The method is based on three solutions: the original network implemented at the start of the planning horizon; the ideal network if the system were to be totally reconstructed; and the revamped network which results as a compromise between the previous two solutions. Three case studies with different scenarios are used to illustrate this approach.