High-Ash Low-Rank Coal Gasification: Process Modeling and Multiobjective Optimization

IF 4.3 Q2 ENGINEERING, CHEMICAL
Shailesh Pandey, Vimal Chandra Srivastava* and Vimal Kumar, 
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引用次数: 1

Abstract

The diversification of coal for its sustainable utilization in producing liquid transportation fuel is inevitable in countries with huge coal reserves. Gasification has been contemplated as one of the most promising thermochemical routes to convert coal into high-quality syngas, which can be utilized to produce liquid hydrocarbons through catalytic Fischer–Tropsch (F-T) synthesis. Liquid transportation fuel production through coal gasification could help deal with environmental challenges and renewable energy development. The present study aims to develop an equilibrium model of a downdraft fixed-bed gasifier using Aspen Plus simulator to predict the syngas compositions obtained from the gasification of high-ash low-rank coal at different operating conditions. Air is used as a gasifying agent in the present study. The model validation is done using published experimental and simulation results from previous investigations. The sensitivity analysis is done to observe the influence of the major operating parameters, such as equivalence ratio (ER), gasification temperature, and moisture content (MC), on the performance of the CL-RMC concerning syngas generation. The gasification performance of CL-RMC is analyzed by defining various performance parameters such as syngas composition, hydrogen-to-carbon monoxide (H2/CO), molar ratio, syngas yield (YSyngas), the lower heating value of syngas (LHVSyngas), cold gas efficiency (CGE), and carbon conversion efficiency (CCE). The combined effects of the major operating parameters are studied through the response surface methodology (RSM) using the design of experiments. The optimized condition of the major operational parameters is determined for a target value of a H2/CO molar ratio of 1 and the maximum CGE and CCE using the multiobjective optimization approach. The high-degree accurate regression model equations were generated for the H2/CO molar ratio, CGE, and CCE using the variance analysis (ANOVA) tool. The optimal conditions of the major operating parameters, i.e., ER, gasification temperature, MC for the H2/CO molar ratio of 1, and the maximum CGE and CCE, are found to be 0.5, 655 °C, and 16.36 wt %, respectively. The corresponding optimal values of CGE and CCE are obtained as 22 and 16.36%, respectively, with a cumulative composite desirability value of 0.7348. The findings of the present investigation can be decisive for future developmental projects in countries concerning the utilization of high-ash low-rank coal in liquid fuel production through the gasification route.

Abstract Image

高灰低煤阶气化:过程建模与多目标优化
在煤炭储量巨大的国家,煤炭的多样化是生产液体运输燃料的可持续利用的必然选择。气化被认为是将煤转化为高质量合成气的最有前途的热化学途径之一,这种合成气可以通过催化费托合成(F-T)来生产液态烃。通过煤气化生产液体运输燃料有助于应对环境挑战和可再生能源的发展。本研究旨在利用Aspen Plus模拟器建立下气流固定床气化炉的平衡模型,以预测不同操作条件下高灰低阶煤气化所得合成气的组成。在本研究中,空气被用作气化剂。模型验证是使用先前研究的已发表的实验和仿真结果完成的。通过灵敏度分析,观察等效比(ER)、气化温度、含水率(MC)等主要运行参数对CL-RMC合成气产气性能的影响。通过定义合成气组分、氢/一氧化碳(H2/CO)、摩尔比、合成气产率(YSyngas)、合成气低热值(LHVSyngas)、冷气效率(CGE)和碳转化效率(CCE)等性能参数,分析了CL-RMC的气化性能。通过实验设计,采用响应面法研究了各主要工作参数的综合影响。采用多目标优化方法,确定了以H2/CO摩尔比为1、CGE和CCE最大值为目标的主要操作参数的优化条件。利用方差分析(ANOVA)工具建立H2/CO摩尔比、CGE和CCE的高精度回归模型方程。在H2/CO摩尔比为1时,主要操作参数的最佳条件为ER、气化温度、MC,最大CGE和CCE分别为0.5、655℃和16.36 wt %。CGE和CCE对应的最优值分别为22%和16.36%,累积综合理想值为0.7348。本调查的结果对各国今后关于通过气化途径在液体燃料生产中利用高灰低阶煤的发展项目具有决定性意义。
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来源期刊
ACS Engineering Au
ACS Engineering Au 化学工程技术-
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期刊介绍: )ACS Engineering Au is an open access journal that reports significant advances in chemical engineering applied chemistry and energy covering fundamentals processes and products. The journal's broad scope includes experimental theoretical mathematical computational chemical and physical research from academic and industrial settings. Short letters comprehensive articles reviews and perspectives are welcome on topics that include:Fundamental research in such areas as thermodynamics transport phenomena (flow mixing mass & heat transfer) chemical reaction kinetics and engineering catalysis separations interfacial phenomena and materialsProcess design development and intensification (e.g. process technologies for chemicals and materials synthesis and design methods process intensification multiphase reactors scale-up systems analysis process control data correlation schemes modeling machine learning Artificial Intelligence)Product research and development involving chemical and engineering aspects (e.g. catalysts plastics elastomers fibers adhesives coatings paper membranes lubricants ceramics aerosols fluidic devices intensified process equipment)Energy and fuels (e.g. pre-treatment processing and utilization of renewable energy resources; processing and utilization of fuels; properties and structure or molecular composition of both raw fuels and refined products; fuel cells hydrogen batteries; photochemical fuel and energy production; decarbonization; electrification; microwave; cavitation)Measurement techniques computational models and data on thermo-physical thermodynamic and transport properties of materials and phase equilibrium behaviorNew methods models and tools (e.g. real-time data analytics multi-scale models physics informed machine learning models machine learning enhanced physics-based models soft sensors high-performance computing)
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