Simulation and Optimization of Chlorella vulgaris Gasification Using Aspen Plus

Microalgal gasification produces synthesis gas (syngas), liquid products (e.g., tar), and solid carbon (e.g., char). However, at the current state, the viability of the process is yet to be established. One of the ways to achieve that is by understanding the fundamental of microalgal gasification. This could be done by optimizing the process conditions via modeling. Therefore, this study models the microalgal gasification process and further optimizes its process conditions. The modeling work was carried out using Aspen Plus V8.8 software, where thermodynamics equilibrium and kinetics approaches were used in the calculations of Chlorella vulgaris gasification. The study was done by modeling the gasifier in three stages: drying, pyrolysis, and gasification. The model was developed using proximate and ultimate analysis data of Chlorella vulgaris. The parameters were temperature (600-1000 degrees C), equivalence ratio (ER) 0.1-0.4, and mass flow rate of biomass (10-100 kg/h). The syngas yields of H-2, CO, CO2, and CH4 were determined and the findings were compared with the literature and some deviations of the predicted syngas compositions were presented. It was found that consistent results of syngas composition and yield were obtained between the model and the experiments. The root mean square error (RMSE) values for the effect of temperature were 0.242, 0.294, 0.228, and 0.062 for H-2, CO, CO2, and CH4, respectively. Meanwhile, for the effect of loading, the values were 0.083, 0.064, 0.362, and 0.479 for H-2, CO, CO2, and CH4, respectively. The optimization of the gasification from sensitivity analysis results showed that the increment of temperature favored the H-2 and CO production, and the increased in biomass loading favored H-2 and CH4 production. Meanwhile, the increment of ER value resulted in increasing the CO2 yield. Based on the findings, a slight deviation in the simulation results was observed compared with the experimental work. This might be resulted from the limitation of the Aspen Plus V8.8 software where some parameters need to be set as a constant value, which in this study was the heating rate.