Mathematical Programming Techniques for Designing Minimum Cost Pipeline Networks for Co2 Sequestration

It has been proposed that the CO2 produced at sources such as fossil energy conversion facilities and industrial process plants could be captured, compressed to supercritical pressures, transported via pipelines and stored in underground geologic formations such as depleted oil and natural gas reservoirs and deep saline aquifers. In this paper, we describe the initial phases of a project using mathematical programming techniques to find the minimum cost network for transporting the CO2 from the sources to the sinks. A nonlinear model of the CO2 pipeline system is described, with appropriate constraints, and the lowest cost system is found using a state-of-the-art nonlinear optimization software called LOQO. We also present ways to model the behavior of the system over time, and to model the impact of uncertainties. In future work, we plan to extend these methods to look at the larger system of fossil energy complexes with CO2 capture and sequestration and distribution of hydrogen.