A novel multi-objective optimization model of solar-driven methanol steam reforming system combining response surface methodology and three-dimensional numerical simulation

Abstract

Solar-driven methanol steam reforming (MSR) to produce hydrogen is a pivotal thermochemical process for enhancing green energy utilization with low-carbon emissions. While this process has been explored in the thermochemical reforming literature, with valuable studies on fuel to hydrogen, this study marks the first comprehensive examination and multi-objective optimization of the MSR process within a solar-driven catalyst-filled reactor. The study begins by modeling and validating the MSR’s reaction kinetic. Subsequently, the effects of the reactor surface energy flux density and key operating characteristics, such as steam-to-methanol ratio (SMR) and space velocity, on the gas composition and conversion efficiency as well as H2 yield are comprehensively analyzed. In order to effectively optimize the operating parameters, the interactions between the various factors were elucidated and an optimization procedure was established to scrutinize the impact of these factors on hydrogen production. The model accuracy is assessed using Analysis of Variance (ANOVA), which also identifies optimal operating parameters under varying conditions. Predictions from the Response surface methodology (RSM) indicate optimal conditions with a SMR of 1.13, a gas hourly space velocity of 45.24, and an inlet temperature of 507.4 K. Numerical calculations confirm the practicality of these conditions, yielding an actual methanol conversion of 0.9998, deviating only by 0.17 % from the predicted value. This work underscores the feasibility and efficacy of studying MSR performance based on response surface method. The analysis of factor significance and interactions provides valuable guidance for practical operations.