Using multi-criteria and thermodynamic analysis to optimize process parameters for mixed reforming of biogas

Syngas is a gas mixture that can be obtained from a variety of raw materials and used as source of hydrogen. Biogas is an interesting raw material from which to produce syngas via thermo-catalytic reforming because it is abundant, can be obtained from low-cost feedstock, and is potentially carbon-neutral. However, difficulties arise because biogas composition changes from source to source, the reforming process can be quite energy-intensive and there is associated catalyst deactivation through carbon deposition. Mixed reforming of biogas with steam and/or air shows benefits in terms of carbon deposition and energy requirements, but the reaction network is complicated and finding the optimal operating conditions is not trivial. Although several analytical techniques have been used in the literature to find the optimal process conditions, a direct comparison is difficult due to the different criteria and/or boundaries considered. This paper aims to develop a novel and comprehensive methodology for identifying the optimal thermodynamic operating conditions (temperature and feed ratios) for mixed reforming of biogas with air and steam, based on equilibrium data manipulated via two multi-criteria decision making (MCDM) techniques in series, namely the entropy and the TOPSIS methods. The optimal scenario is when biogas made of 50-60% CH4 in CO2 is reacted in the reforming reactor at CH4/CO2/O2/H2O = 1/1-0.67/0-0.1/3-2.4 and 790-735 °C, resulting in a product stream composed of 66-65% H2, 0.8-1% CO and 33-28% CO2 on a dry basis after the water-gas shift section. At these conditions the hydrogen yield and the conversion of methane in the biogas can be simultaneously maximized, while the yield of solid carbon and the net energy requirement of the overall process can be minimized. In conjunction with the numerical results, the main outcome of this paper is the development of a novel method based on MCDM techniques for the optimization of the operating conditions in a network of reactions.