TY - JOUR
T1 - Co-Gasification of Plastic Waste Blended with Biomass
T2 - Process Modeling and Multi-Objective Optimization
AU - Aentung, Tanawat
AU - Patcharavorachot, Yaneeporn
AU - Wu, Wei
N1 - Publisher Copyright:
© 2024 by the authors.
PY - 2024/9
Y1 - 2024/9
N2 - Mixed plastic/biomass co-gasification stands out as a promising and environmentally friendly technology, since it reduces wide solid wastes and produces green hydrogen. High-quality syngas can be obtained by virtue of the process design and optimization of a downdraft fixed-bed co-gasifier. The design is based on the actual reaction zones within a real gasifier to ensure accurate results. The methodology shows that (i) the co-gasifier modeling is validated using the adiabatic RGibbs model in Aspen Plus, (ii) the performance of the co-gasifier is evaluated using cold-gas efficiency (CGE) and carbon conversion efficiency (CCE) as indicators, and (iii) the multi-objective optimization (MOO) is employed to optimize these indicators simultaneously, utilizing a standard genetic algorithm (GA) combined with response surface methodology (RSM) to identify the Pareto frontier. The optimal conditions, resulting in a CGE of 91.78% and a CCE of 83.77% at a gasifier temperature of 967.89 °C, a steam-to-feed ratio of 1.40, and a plastic-to-biomass ratio of 74.23%, were identified using the technique for order of preference by similarity to ideal solution (TOPSIS). The inclusion of plastics enhances gasifier performance and syngas quality, leading to significant improvements in CGE and CCE values.
AB - Mixed plastic/biomass co-gasification stands out as a promising and environmentally friendly technology, since it reduces wide solid wastes and produces green hydrogen. High-quality syngas can be obtained by virtue of the process design and optimization of a downdraft fixed-bed co-gasifier. The design is based on the actual reaction zones within a real gasifier to ensure accurate results. The methodology shows that (i) the co-gasifier modeling is validated using the adiabatic RGibbs model in Aspen Plus, (ii) the performance of the co-gasifier is evaluated using cold-gas efficiency (CGE) and carbon conversion efficiency (CCE) as indicators, and (iii) the multi-objective optimization (MOO) is employed to optimize these indicators simultaneously, utilizing a standard genetic algorithm (GA) combined with response surface methodology (RSM) to identify the Pareto frontier. The optimal conditions, resulting in a CGE of 91.78% and a CCE of 83.77% at a gasifier temperature of 967.89 °C, a steam-to-feed ratio of 1.40, and a plastic-to-biomass ratio of 74.23%, were identified using the technique for order of preference by similarity to ideal solution (TOPSIS). The inclusion of plastics enhances gasifier performance and syngas quality, leading to significant improvements in CGE and CCE values.
UR - https://www.scopus.com/pages/publications/85205272105
UR - https://www.scopus.com/pages/publications/85205272105#tab=citedBy
U2 - 10.3390/pr12091906
DO - 10.3390/pr12091906
M3 - Article
AN - SCOPUS:85205272105
SN - 2227-9717
VL - 12
JO - Processes
JF - Processes
IS - 9
M1 - 1906
ER -