Probing into the interactions among operating variables in blue hydrogen production: A new approach via design of experiments (DoE)

Abstract

Copyright © 2023 The Authors. Anthropogenic CO2 emission is a key driver in global warming and climate change. Worldwide, H2 production accounts for 2.5% of this CO2 emission. A shift to clean methods of hydrogen production is required to reduce CO2 emissions, and to mitigate the effects of climate change. Developing optimised process models of H2 production processes is required in order to investigate the effects of operational variables of the process and their impacts on key performance indicators (KPIs). Within this study, a detailed rate-based model was implemented to simulate the reformer in Sorption Enhanced Steam Methane Reforming (SE-SMR), as well as Sorption-Enhanced Auto-Thermal Reforming (SE-ATR) processes. The results indicate that the SE-ATR/ATR corresponds to a significantly improved performance over the SMR with the optimal operating conditions for achieving the desired KPIs, including hydrogen purity (86%), hydrogen yield (36%), methane conversion (99%), and carbon capture rate (50%) at a temperature of 720 °C, a pressure of 20 bara, and an S/C ratio of 6. Whereas with SMR, the temperature, pressure, and S/C ratio should be adjusted to 975 °C, 20 bara, and 6, respectively, to achieve a hydrogen purity of 84%, a hydrogen yield of 42%, a methane conversion of 96%, and a carbon capture rate of 48%. The study provides insights into the optimal operating conditions to achieve maximum efficiency in the reformer, and demonstrates the effectiveness of incorporating DoE within process modelling as a tool for optimisation.