Comparative analysis of aspen plus simulation strategies for woody biomass air gasification processes

被引:0
|
作者
Jadoon, Usman Khan [1 ]
Diaz, Ismael [1 ]
Rodriguez, Manuel [1 ]
机构
[1] Univ Politecn Madrid, Escuela Super Ingenieros Ind, Dept Ingn Quim Ind & Medioambiente, C Jose Gutierrez Abascal 2, Madrid 28006, Spain
来源
BIOMASS & BIOENERGY | 2025年 / 194卷
关键词
Biomass air gasification; Kinetic modeling; Thermodynamic modeling; Renewable energy; Syngas; BUBBLING FLUIDIZED-BED; STEAM GASIFICATION; EQUILIBRIUM-MODEL; SHIFT REACTION; PRODUCER GAS; SCALE; PERFORMANCE; HYDROGEN; PLANT; TAR;
D O I
10.1016/j.biombioe.2025.107626
中图分类号
S2 [农业工程];
学科分类号
0828 ;
摘要
Biomass gasification is gaining attention because of its role in transition to a low-carbon chemical industry, providing a cleaner alternative to fossil fuels in energy and chemical production. However, accurate modeling remains challenging due to the variability in syngas composition across varying biomass types, gasifiers, and operating conditions. This study evaluates the performance of thermodynamic equilibrium modeling (TEM), restricted thermodynamic modeling (RTM), and kinetic modeling (KM) by Aspen Plus to model a fluidized bubbling-bed reactor. The novelty of the research lies in the comparative evaluation of these models in diverse woody biomasses and gasification conditions, addressing a significant gap in the field. Experimental data was curated and used to assess the predictive precision of each approach, focusing on syngas components such as H2, CO, CO2, and CH4. Moreover, sensitivity analysis was performed within the RTM framework to identify optimal approach temperatures for selected. On the basis of these approach temperatures, syngas predictions were carried out, which are referred to as the optimal solution (OS). RTM demonstrated the highest accuracy, with an average RMSE of 0.0793, while TEM showed the lowest accuracy with RMSE of 0.1735. KM and OS had intermediate precision, with RMSE values of 0.1593 and 0.1282, respectively. These results demonstrate that RTM is the most accurate and OS is a reliable alternative when kinetic data are unavailable. This study offers valuable information on the selection of effective modeling strategies for biomass gasification and the development of technologies based on syngas.
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页数:13
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