Hydrogen production from coke oven gas using pressure swing adsorption process − a mathematical modelling approach

Journal Article (2023)
Author(s)

Balan Ramani (Tata Steel)

Jan Van Der Van Der Stel (Tata Steel)

Gerard Jagers (Tata Steel)

Willem Buijs (TU Delft - Energy Technology)

Research Group
Energy Technology
Copyright
© 2023 Balan Ramani, Jan Van Der Stel, Gerard Jagers, W. Buijs
DOI related publication
https://doi.org/10.1051/mattech/2023027
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 Balan Ramani, Jan Van Der Stel, Gerard Jagers, W. Buijs
Research Group
Energy Technology
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Issue number
2
Volume number
111
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Abstract

Coal is playing a major role as a reductant and as an energy source in the present world steel production due to its low cost and widespread distribution around the world. At the same time, being the largest contributor to global CO2 emissions, coal faces significant environmental challenges in terms of air pollution and global warming. Hydrogen is a promising alternative for coal in lowering the steel industry's CO2 footprint, but the availability of green hydrogen is currently limited by its high production cost. This research study focuses on developing a pressure swing adsorption (PSA) technology that will allow for continued use of coal for a smooth transition towards green hydrogen-based steel production, by better utilisation of its by-product coke oven gas to produce high purity hydrogen. A generic, fast and robust simulation tool for simulating a variety of PSA processes considering both equilibrium and kinetic effects using a detailed non-isothermal and non-isobaric model is developed in the study. The adsorption equilibrium data required for the model are calculated from experimental results using the non-linear regression data fitting method. A series of rigorous parametric studies and breakthrough tests are performed using the developed mathematical model for better understanding of the effects of different factors on the PSA process performance. With the better understanding obtained from the above-mentioned parametric studies, the model is optimised by performing several simulation tests to achieve a high process performance in terms of purity and recovery of the H2 product, productivity of the adsorbents and energy consumption for compression of gases. The optimised 14-step multi-bed PSA cycle developed in this study allows for an improved energy efficiency of coal usage by better utilisation of its by-product coke oven gas by converting it into valuable high purity (>99.999%) hydrogen product with a recovery of over 75%.

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