Process design and muti-objective optimization of solid waste/biomass co-gasification considering tar formation

Abstract

Background: The co-gasification of solid waste and biomass to produce syngas is an environmentally friendly technology. Unfortunately, the tar formation in the solid waste/biomass co-gasification process would degrade the product gas quality and the overall process efficiency. Methods: In this study, the kinetics of the solid waste/biomass co-gasification is shown by the Aspen Plus simulation. Through the model validation and sensitivity analysis, it is validated that tar yield, syngas composition, and syngas yield are sensitive to gasifier temperature, steam-to-feed ratio (S/F), and blending weight ratio (B/W). It shows that the increase of the product gas yield (GY) increases CO2 concentration in the product gas, but the tar yield is reduced. To address the sustainable solid waste/biomass co-gasifier, the multi-objective optimization (MOO) algorithm is implemented to maximize GY and minimize CO2 concentration. For solving the MOO problem, the standard genetic algorithm (GA) coupled with response surface methodology (RSM) is performed to find the Pareto frontier plot, and the technique for order of preference by similarity to the ideal solution (TOPSIS) is used to determine optimal operating conditions. Significant Findings: Under the Pareto frontier plot and TOPSIS, a GY of 2.672 Nm³/kg, CO2 concentration of 8.045 vol.%, and tar yield of 17.0617 g/Nm³ can be achieved under the optimal conditions of T = 1099.95 °C, S/F ratio = 0.79, and B/W ratio = 10.02. In addition, the CO2 absorption using CaO is added to purify CO2 up to 99.999 % of purity.