A Superstructure-Based Mixed-Integer Programming Approach to Optimal Design of Pipeline Network for Large-Scale CO2 Transport

摘要

Pipeline transport is the major means for large-scale and long-distance CO2 transport in a CO2 capture and sequestration (CCS) project. But optimal design of the pipeline network remains a challenging problem, especially when considering allocation of intermediate sites, like pump stations, and selection of pipeline routes. A superstructure-based mixed-integer programming approach for optimal design of the pipeline network, targeting on minimizing the overall cost in a CCS project is presented. A decomposition algorithm to solve the computational difficulty caused by the large size- and nonlinear nature of a real-life design problem is also presented. To illustrate the capability of our models. A real-life case study in North China, with 45 emissions sources and four storage sinks, is provided. The result shows that our model and decomposition algorithm is a practical and cost-effective method for pipeline networks design.