Simulation and optimization of reforming reactors for carbon dioxide utilization using both rigorous and reduced models

CO2 is a major greenhouse gas emitted at the global scale from burning fossil fuels. Converting CO2 to chemicals such as syngas is a promising way to reduce CO2 emissions from stationary sources. In this work, we explore technologies for the thermochemical conversion of CO2 to syngas using both rigorous and reduced order reactor models. Specifically, we study the CO2 utilization potentials of primary reforming such as dry reforming (DR), steam methane reforming (SMR) and partial oxidation (POX), and combined reforming such as combined dry and steam methane reforming (CDSMR), auto-thermal reforming (ATR), combined partial oxidation and dry reforming (PODR) and tri-reforming (TR). Through detailed simulation and analysis, we show the importance of considering rigorous models for accurate prediction. We also develop algebraic surrogate models for reactor outlets as functions of reactor design and operating conditions. The replacement of the high-fidelity models with their simpler algebraic surrogates provides an efficient way for superstructure-based reactor synthesis. Using a mixed-integer nonlinear optimization (MINLP)-based reactor synthesis model, the reactors are further optimized for maximizing CO2 utilization and syngas selectivity. PODR has been found to have the highest potential for converting CO2 for the range of syngas ratios (H2/CO) between 1 and 1.7, achieving almost 100% CO2 conversion with a syngas selectivity ranging 80-93%. We further improve the conversion and syngas selectivity by distributing the feeds to multiple reformers. A combination of DR, CDSMR and TR achieves the best CO2 conversion for syngas ratios up to 2.4. For higher syngas ratios, a combination of SMR, TR and RWGS are found to be optimal. These are non-intuitive results that need further attention.