Steady-state simulation of large-scale pipeline networks for CCUS applications

Carbon capture utilization and storage is crucial for reducing emissions from energy sources and industrial clusters with significant CO 2 emissions. To ensure the appropriate sizing of the pipeline transport infrastructure, hydraulic modeling tools are used, which allow engineers to analyze and predict the performance of transmission systems under design conditions and to assess their efficiency and reliability. In this work we solve a single-phase steady-state, nonisothermal flow model with composition tracking that incorporates the GERG-2008 and Peng–Robinson equations of state using efficient Newton loop-node coupling. The solver enables evaluation of the deliverability of the pipeline system under varying CO 2 stream compositions. We considered pure CO 2 and CO 2 mixtures containing impurities obtained from pre-combustion and post-combustion carbon capture technologies. We investigated the influence of impurities, pipe inclination, and heat transfer between the CO 2 -rich stream and its surroundings. The network model was solved using the Newton loop-node method coupled with the non-pipe element model in matrix notation. The model was benchmarked against a commercially available hydraulic modeling software package using data from a fictitious but plausible multi-source transmission system. The applicability of the model was demonstrated through a case study of a complex meshed network. The results indicated a good agreement between the software tools, but the proposed model showed a two orders of magnitude smaller computational burden. The model also showed superior insensitivity to the topology of the computed network in terms of computational complexity. • Steady-state, nonisothermal, single-phase flow model with composition tracking. • Deliverability of the pipeline system under varying CO 2 stream composition. • Effect of impurities on compressor power input and aftercooler load. • Good agreement between model results and commercial software results as a benchmark. • Low computational complexity; insensitive to the topology of the non-planar network.