期刊
ENERGY
卷 263, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2022.125839
关键词
Tri -generation; Waste-to-energy; Exergy analysis; Biomass-waste; Artificial intelligence
This research investigated a novel configuration of a tri-generation process for poultry litter valorization, which includes gasification, solid oxide fuel cell (SOFC), and combined heat and power system. Multi-level factorial design of experiments was used to extract simulation data and extreme gradient boosting was applied to predict and optimize the parametric yield of the model. The results showed that pressure has no significant effect on output yield, but it negatively affects SOFC voltage. The optimal hydrogen yield in syngas can be generated at a gasification temperature of around 600 degrees C and a biomass to air ratio (BMR) of 0.25-0.33. The exergy efficiency of this tri-generation process is 34.6% higher than the gasification process. Based on these findings, it is concluded that this tri-generation process could be a better solution for poultry litter valorization.
A novel configuration of a tri-generation process for poultry litter valorization, including gasification, solid oxide fuel cell (SOFC), and combined heat and power system was examined in this research. Multi-level factorial, design of experiment methodology has been adopted to extract the simulation data from Aspen Plus simulation model by changing one parameter at a time. Extreme gradient boosting has been applied on the factorial design data to predict and optimize the parametric yield of this model. Results of gasification process sensitivity analysis show that pressure has no significant effect on output yield, but it has a negative effect on SOFC voltage. While gasification process temperature operating condition around 600 degrees C and 0.25-0.33 biomass to air ratio (BMR) can generate optimum hydrogen yield in syngas. Coefficient of determinant (R2) for Extreme Gradient Booster (XGB) model is greater than 0.97 for all dependent variables. According to XGB results, BMR is the most contributing factor which affects the output of this study. Exergy efficiency of this tri-generation process is 34.6% more than the gasification process. Therefore, based on the findings of this model, it is concluded that this trigeneration process could be the better possible solution for poultry litter valorization.
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