(245g) A Thermodynamic, Technical, and Economic Evaluation of Hydrogen Blending in Natural Gas Pipelines
AIChE Annual Meeting
Tuesday, November 15, 2022 - 10:00am to 10:15am
Blending hydrogen with natural gas has been proposed as an interim solution for the gradual integration of hydrogen into the current energy mix. On one front, the combustion of H2 + NG mixtures can enhance the carbon footprint associated with natural gas combustion, as water is the only byproduct from H2 combustion . On another front, H2 can be transported to end-users without the incurred costs of building dedicated H2 transmission networks, relying on the already existing natural gas transmission pipelines, with downstream H2 separation units permitting end users to recover H2 for intended industrial application . However, much remains to be unknown regarding the impact of H2 composition on the change in the thermodynamic properties and pipelines integrity of transported natural gas, mainly composed of methane, and hence the practicality of H2 blending in natural gas pipelines. The required breadth of thermodynamic property data, at different operating conditions and H2 content is very demanding in terms of resources and time from the experimental point of view. Thus, thermodynamic modeling tools are required to provide accurate, reliable, and rapid predictions of the effect of H2 content on the thermophysical and transport properties of natural gas of interest for pipeline transmissions.
In this work, the polar soft-Statistical Associating Fluid Theory (soft-SAFT) equation of state (EoS)  have been employed to systematically investigate the effect of H2 composition on the change in the thermodynamic properties of natural gas, at conditions relevant to pipeline transmission. The thermodynamic modeling of pure fluids within the framework of polar soft-SAFT is done in a coarse-grain manner by representing fluids by a set of molecular parameters characterizing key structural and energetic features spanning across non-association and non-polar fluids such as H2, CH4, C2H6, and n-C3H8, and quadrupolar fluids such as CO2 and N2. The evaluation of the accuracy and robustness of the thermodynamic model was performed in a systematic manner by examining a range of properties such as phase equilibria, critical loci, single-phase density, heat capacity, speed of sound, Joule-Thomson coefficient, compressibility factor, and viscosity, compared to available experimental data for binary mixtures containing H2 and multicomponent systems with H2 + CH4 + other major NG components. Additionally, the accuracy of polar soft-SAFT was also benchmarked to widely used thermodynamic models in oil & gas industry, namely, Peng-Robinson EoS, and the multiparameter semiempirical GERG-2008 model. The results of the systematic validation established a higher overall predictive accuracy of the molecular theory compared to the other models, particularly for modeling phase equilibria, critical loci, compressibility factor, and viscosity . Consequently, the polar soft-SAFT was used to quantify the change in H2 + CH4 properties as a function of H2 content relative to CH4, i.e., NG in this case, at conditions typical for pipeline transmission. The predictive analysis revealed major changes in density, and speed of sound associated with increasing H2 content, while viscosity was the least affected property .
The thermodynamic model was subsequently integrated with techno-economic evaluation to assess the impact of H2 content on key operational parameters for NG transmission inclusive of pressure drop, temperature profile, change in compression requirements, energy delivery rate, and their relation to changes in the operational cost of the pipeline transmissions.
This framework with a molecular-based EoS at its center permits the precise determination of allowable threshold for the addition of hydrogen into natural gas pipelines without jeopardizing the safety margin, and the operational integrity of existing pipeline transmissions grids, while permitting the gradual decarbonization of the current energy mix.
This work is funded by Khalifa University of Science and Technology (RC2-2019-007). Computational resources from the Research and Innovation Center on CO2 and Hydrogen (RICH Center) are gratefully acknowledged.
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