Practical deployment of pipelines for the CCS network in critical conditions using MINLP modelling and optimization: A case study of South Korea

In applying Carbon Capture and Storage (CCS) technology, pipelines are an economic choice for transporting CO₂. However, it is difficult to plan the pipeline network in detail since various factors, such as mountain regions and high population density increase the cost of pipeline installation. Also, uncertainty of the reservoir capacity and national policies is important factors in practical pipeline deployment, especially in critical conditions mentioned above. In this study, the development of an optimal CCS pipeline network in critical conditions, and the effect of practical design conditions on the network, are studied using mixed-integer nonlinear programming (MINLP) modeling and optimization. South Korea is selected as a case study and optimal CCS networks are obtained according to four scenarios developed with regard to reservoir capacity and policy options. A rigorous cost model was developed, and subdivided penalty factors were applied to consider the drastic change in geographical conditions. The four scenarios were evaluated and the effect of the considered factors on the timely development of the CCS network was analyzed.