Modelling of gas network transient flows with multiple hydrogen injections and gas composition tracking

Blending hydrogen into the natural gas (NG) network could provide an efficient pathway for decarbonising the NG system through power-to-gas technologies. However, due to the presence of potentially multiple and intermittent hydrogen injection sources, the gas blended throughout the network would be neither homogenous nor at a constant mole fraction. The above features are not captured by the current transient modelling techniques. To bridge this gap, this work presents a transient analysis model that enables the tracking of gas compositions and particularly hydrogen fractions in real-world meshed networks with multiple NG sources, non-pipe elements, and multiple and intermittent hydrogen injection sources. A time-varying compressibility factor is also introduced to account for the variable gas composition across the network. Moreover, numerical techniques are adopted for improving the stability of the Eulerian numerical calculation, and a specific grid size threshold Dxmaxis introduced for selecting the stable mesh grid to alleviate convection-dominated oscillations caused by the hydrogen fraction tracking. The case study based on the well-known 20-node Belgian gas network validates the effectiveness of the method in solving practical-scale problems, whereas the unsuitability of steady-state models is also discussed and highlighted. The results clearly demonstrate the effect and importance of introducing variable compressibility factor, hydrogen fraction tracking, and variable gas demand. The impacts of hydrogen blending on pressures and linepack of the network are further investigated. (c) 2021 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

Automated summary

The study presents a transient analysis model for tracking gas compositions and hydrogen fractions in meshed networks with multiple NG and intermittent hydrogen sources. By introducing a time-varying compressibility factor and numerical techniques, the method effectively addresses the decarbonization challenges in natural gas systems with hydrogen blending.