Abstract
The urgent need for sustainable energy drives the exploration of biomass and plastic waste co-gasification, a promising route for producing clean fuels and chemicals, reducing greenhouse gas emissions, and minimizing fossil fuel dependence. Modeling and simulation are vital for optimizing this process, particularly syngas yield, yet comparative studies on Aspen Plus modeling techniques for steam co-gasification are limited. This research addresses this gap by comparing three Aspen Plus strategies: thermodynamic equilibrium modeling (TEM), restricted thermodynamic modeling (RTM), and kinetic modeling (KM), for simulating the co-gasification of pine sawdust and polyethene (PE) with steam in bubbling fluidized bed gasifier (BFBG). The primary objective is to evaluate the effectiveness of each strategy in predicting the syngas composition under varying conditions. Three models were developed in Aspen Plus on the basis of each strategy, and their predicted syngas compositions were compared with published experimental data. A detailed sensitivity analysis was performed within the RTM framework to obtain optimized values of the approach temperatures to enhance predictive accuracy. The results showed that RTM provided the highest precision, with an average root mean square error (RMSE) of 0.0296, while TEM showed the lowest precision with RMSE of 0.1234. KM performed moderately with an RMSE of 0.0929. These findings demonstrate that RTM is superior for predicting the syngas composition for this co-gasification process, and its optimized solution presents a viable alternative when detailed kinetic data are lacking, thus reducing computational expense.