Numerical evaluation of hydrogen production by steam reforming of natural gas

Mingjie Chen, Khalid Al-Subhi, Amira Al-Rajhi, Ali Al-Maktoumi, Azizallah Izady, Amer Al-Hinai

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Abstract


Industry-scale hydrogen is mainly produced by steam methane reforming (SMR), which uses natural gas as the feedstock and fuel and co-produces CO2. This study aims to numerically evaluate hydrogen production by SMR under various reacting conditions. Unlike the previous studies with limited scenarios, the performance of SMR is continuously evaluated in a high-dimensional input-parameter space. The SMR plant including a combustor, a reformer, and a water-gas shifter is modeled in Aspen HYSYS software. The four key parameters, including methane fraction of the feedstock, reformer pressure and temperature, and shifter temperature, are treated uncertain and 50 samples are drawn from a four-dimensional parameter space defined by their ranges. Each sample is input to HYSYS model and mass ratio of each component in product streams is obtained as the output variables. Based on the 50 pairs of input-output data, response surfaces of the outputs are developed to surrogate HYSYS models. The fast response surface models are then used to calculate global sensitivity indices and evaluate SMR processes. Results show the reformer performance is controlled by temperature rather than pressure, and a temperature higher than 900 °C can maximize the reaction rate. The water-gas shifting reaction is inhibited in the reformer but significantly enhanced in the shifter. Hydrogen is mainly produced in the reformer while the major function of the shifter is to convert CO to nontoxic CO2.

Document Type: Original article

Cited as: Chen, M., Al-Subhi, K., Al-Rajhi, A., Al-Maktoumi, A., Izady, A. Al-Hinai, A. Numerical evaluation of hydrogen production by steam reforming of natural gas. Advances in Geo-Energy Research, 2023, 7(3): 141-151. https://doi.org/10.46690/ager.2023.03.01


Keywords


Hydrogen production, combustor, steam methane reforming, shift reactor, Aspen HYSYS, response surface

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DOI: https://doi.org/10.46690/ager.2023.03.01

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