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Prediction and optimization of syngas production from a kinetic-based biomass gasification process model
Fuel Processing Technology ( IF 7.5 ) Pub Date : 2021-02-01 , DOI: 10.1016/j.fuproc.2020.106604
Qi Dang , Xiaoqi Zhang , Yuling Zhou , Xiaotong Jia

Abstract This work presents a robust method for prediction and optimization of syngas production by taking advantage of the established kinetic-based process model and data analysis techniques for constructing a surrogate model. Compared with the widely-used equilibrium model, herein, we first develop a process model of biomass gasification by incorporating updated biomass reaction kinetics and dense bed hydrodynamics. A parallel comparison of model predictions and experimental results illustrates a good agreement under a wide range of operating conditions. The sensitivity results indicate that the initial volatile composition from the pyrolysis step is crucial for final gas product distribution and the gasification temperature is most sensitive to the syngas composition and yield, followed by the equivalence ratio (ER), steam-to-biomass ratio (S/B ratio), and biomass moisture content (MC). More importantly, a multivariable analysis is further carried out by running the model for 864 combinations of four input parameters. A surrogate model is established for predicting and optimizing the syngas yield under various operating conditions. A selective set of response surfaces illustrates the mutual effects of two parameters simultaneously and reveals optimal syngas yields ranging from 61.4 vol% to 78.5 vol% on a dry N2-free basis. The global optimization model demonstrates a maximum syngas yield of 78.6 vol% at a temperature of 900 °C, ER of 0.23, S/B ratio of 0.21, and MC of 30 wt%.

中文翻译:

基于动力学的生物质气化过程模型预测和优化合成气产量

摘要 这项工作通过利用已建立的基于动力学的过程模型和构建替代模型的数据分析技术,提出了一种预测和优化合成气生产的稳健方法。与广泛使用的平衡模型相比,本文首先通过结合更新的生物质反应动力学和密床流体动力学开发了生物质气化过程模型。模型预测和实验结果的平行比较表明在广泛的操作条件下具有良好的一致性。敏感性结果表明,热解步骤的初始挥发性成分对最终气体产品的分布至关重要,气化温度对合成气成分和收率最敏感,其次是当量比 (ER),蒸汽与生物质比(S/B 比)和生物质水分含量 (MC)。更重要的是,通过对四个输入参数的 864 种组合运行模型,进一步执行多变量分析。建立了一种替代模型,用于预测和优化各种操作条件下的合成气产量。一组选择性的响应面同时说明了两个参数的相互影响,并揭示了在干燥无 N2 基础上的最佳合成气产量范围为 61.4 vol% 至 78.5 vol%。全局优化模型表明,在 900 °C 的温度下,最大合成气产率为 78.6 vol%,ER 为 0.23,S/B 比为 0.21,MC 为 30 wt%。建立替代模型以预测和优化各种操作条件下的合成气产率。一组选择性的响应面同时说明了两个参数的相互影响,并揭示了在干燥无 N2 基础上的最佳合成气产量范围为 61.4 vol% 至 78.5 vol%。全局优化模型表明,在 900 °C 的温度下,最大合成气产率为 78.6 vol%,ER 为 0.23,S/B 比为 0.21,MC 为 30 wt%。建立了一种替代模型,用于预测和优化各种操作条件下的合成气产量。一组选择性的响应面同时说明了两个参数的相互影响,并揭示了在干燥无 N2 基础上的最佳合成气产量范围为 61.4 vol% 至 78.5 vol%。全局优化模型表明,在 900 °C 的温度下,最大合成气产率为 78.6 vol%,ER 为 0.23,S/B 比为 0.21,MC 为 30 wt%。
更新日期:2021-02-01
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