Solar biomass steam gasification using concentrated sunlight offers an efficient means of storing intermittent solar energy into renewable solar fuels while upgrading the carbonaceous feedstock. Such solar-driven (allothermal) processes have demonstrated the ability and the effectiveness for the production of high quality hydrogen-rich syngas, but they suffer from inherent barriers related to the variability of solar energy caused by cloud passages and shut off at night. The concept of hybrid solar/autothermal gasification appears promising to meet the requirement for stable and continuous operation under fluctuating or intermittent solar irradiation. To date, dynamic modelling to simulate coupled solar/combustion heating and steam gasification using real solar irradiation data has never been proposed and could be used to predict the annual performance of large-scale solar gasification plants. In this study, a dynamic mathematical model of a scaled-up solar gasification reactor was developed. The model was composed of a system of differential equations that were derived from unsteady mass and energy conservation equations. After an experimental validation step with the results from a lab-scale solar reactor, the dynamic model was applied at large scale to determine the reactor temperature and syngas production evolution during continuous day and night operation in both solar-only (allothermal) and hybrid solar/autothermal modes. Different reactants feeding management strategies were proposed and compared with the aim of achieving enhanced syngas productivity and optimized use of solar energy during solar-aided steam gasification. It was shown that the hybrid mode with partial oxy-combustion of the feedstock and dynamic feeding control results in the most stable process operation upon fluctuating solar power input, while ensuring continuous production of H2 and CO at night and during cloudy periods.
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