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Modelling of Sorption Enhanced Chemical Looping Steam Reforming (SE-CLSR) of Methane in a Packed Bed Reactor

机译:填充床反应器中甲烷的吸附增强化学循环蒸汽重整(SE-CLSR)建模

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摘要

In the sorption enhanced steam methane reforming (SE-SMR) process, hydrogen (H2) can be produced in concentration up to 98 vol. % (dry basis) in a single reactor packed with a mixture of reforming catalyst and carbon dioxide (CO2) sorbent. This is defined as pre-combustion capturing of CO2 and the high purity H2 produced can be used as a fuel for electricity generation, synthesis of ammonia-derived fertilisers, or hydrotreating of naphtha and other heavy gas oil in petroleum refinery. A cyclic operation between the production of H2 and regeneration of CO2 sorbent is required, but the energy demand for the sorbent regeneration is high. A proposed method to decrease this energy demand is to couple SE-SMR with chemical looping (CL), which naturally separates the nitrogen (N2) from the syngas via the highly exothermic cyclic oxidation with air of a metallic material, which acts as the reforming catalyst when reduced (oxygen transfer material or ‘OTM’). The combination of SE-SMR and CL makes the process energy efficient and eliminates the need for (i) high temperature as compared to the conventional steam methane reforming (SMR) process (typical temperature range is 750- 950°C), (ii) the water gas shift (WGS) reactors downstream of the reformer, and (iii) external heating using the natural gas fuel in the reformer. However the H2 generation of a high purity from one reactor operation is intermittent, as part of a cyclic operation, with the reactor alternately operating in Fuel Reactor mode (FR), with fuel and steam feed or Air Reactor mode (AR), with air feed. Adsorption of CO2 shifts the equilibrium of reaction towards more H2 production and ultimately increases the efficiency of the process towards H2 production. Production of H2, CH4 conversion and overall efficiency of the process depend upon many operating parameters. The effects of inlet temperature, reactor pressure, molar steam to carbon ratio (S/C) in the feed, and gas mass velocity on the SE-SMR and the sorption enhanced chemical looping steam reforming (SE-CLSR) of methane processes is reported in this thesis.udThe formulation of the SE-CLSR process model requires the modelling of packed bed reactors. This mathematical modelling covers various individual models (sub-models) for; SMR, SE-SMR, OTM reduction and oxidation of reduced OTM. The gPROMS model builder 4.1.0® is used to solve the model equations. In this work, an experimentaludIVudkinetics study and model of SMR process over 18 wt. % NiO/α-Al2O3 catalyst are presented for an adiabatic fixed bed reactor in the temperature range of 300-700°C at 1 bar pressure. The model is validated by comparing the results with the experimental data obtained as part of this work. The simulation results are in excellent agreement with the experimental results. The equilibrium results are generated using Chemical Equilibrium with Applications (CEA) software. The effect of various operating parameters (temperature, pressure and S/C) on the CH4 and water conversion (%) is modelled and compared with the equilibrium values. The mathematical model of SE-SMR was developed based on the industrial operating conditions of temperature and pressure. The 873-973 K was found to be the optimum range of temperature, under the high pressure (30 bar) conditions, for the production of H2 of purity exceeding 85%. The developed model of SE-SMR was validated against the literature data.udThe mathematical model of SE-CLSR process was developed under adiabatic conditions. This model is the combination of reduction of catalyst followed by oxidation of the reduced catalyst. The individual models of reduction and oxidation are developed by using kinetic data available in the literature and later on validated with experimental results proposed in the literature. The already developed model of SE-SMR process is combined with the OTM reduction model to mimic the dynamic process occurring in the fuel reactor (FR) system. This FR is combined with air reactor (AR) and the combined model is run for 10 cycles. The sensitivity of the process is studied under the various operating conditions of temperature (873-1023 K), pressure (1-30 bar), molar S/C (2-6) and mass flux of the gas phase (Gs = 2-7 kg m-2 s-1). In this work, the operating conditions used for the production of H2 represent realistic industrial production conditions. The sensitivity analysis demonstrates that the developed model of SE-CLSR process has the flexibility to simulate a wide range of operating conditions of temperature, pressure, S/C and Gs.
机译:在吸附增强蒸汽甲烷重整(SE-SMR)过程中,氢气(H2)的浓度最高可达到98 vol。在装有重整催化剂和二氧化碳(CO2)吸附剂混合物的单个反应器中,以%(干基)为单位。这被定义为燃烧前捕获CO2,所产生的高纯度H2可用作发电,合成氨衍生的肥料或对石油精炼厂中石脑油和其他重瓦斯油进行加氢处理的燃料。需要在H2的产生和CO2吸附剂的再生之间进行循环操作,但是吸附剂再生的能量需求很高。减少能源需求的一种建议方法是将SE-SMR与化学循环(CL)耦合,该化学循环通过高放热循环氧化与金属材料的空气自然地将合成气中的氮(N2)分离出来,从而起到重整作用还原时的催化剂(氧气转移材料或“ OTM”)。 SE-SMR和CL的结合使过程更加节能,并且与传统的蒸汽甲烷重整(SMR)过程(典型温度范围为750- 950°C)相比,无需(i)高温;(ii)重整器下游的水煤气变换(WGS)反应器,以及(iii)使用重整器中的天然气燃料进行外部加热。但是,作为循环操作的一部分,一次反应堆运行会间歇性地产生高纯度的氢气,反应堆交替运行在燃料反应堆模式(FR),燃料和蒸汽进料或空气反应堆模式(AR),空气饲料。 CO 2的吸附使反应的平衡向更多的H 2产生转移,并最终提高了向H 2产生的反应效率。氢气的产生,甲烷的转化和工艺的整体效率取决于许多操作参数。报告了进料温度,反应器压力,进料中蒸汽与碳的摩尔比(S / C)和气体质量速度对甲烷工艺的SE-SMR和吸附增强的化学循环蒸汽重整(SE-CLSR)的影响在本文中。 udSE-CLSR过程模型的制定需要对填充床反应器进行建模。该数学建模涵盖了以下各个单独的模型(子模型): SMR,SE-SMR,OTM还原和还原OTM的氧化。 gPROMS模型构建器4.1.0®用于求解模型方程。在这项工作中,对18 wt。%的SMR过程进行了实验性 udIV udkinetics研究和模型。在300巴至700℃的温度范围内,在1巴压力下,将%NiO /α-Al2 O 3催化剂用于绝热固定床反应器。通过将结果与作为该工作一部分而获得的实验数据进行比较,可以验证模型的有效性。仿真结果与实验结果吻合良好。使用带有应用程序的化学平衡(CEA)软件生成平衡结果。对各种操作参数(温度,压力和S / C)对CH4和水转化率(%)的影响进行了建模,并与平衡值进行了比较。根据温度和压力的工业​​运行条件,开发了SE-SMR的数学模型。发现873-973 K是在高压(30 bar)条件下生产纯度超过85%的H2的最佳温度范围。根据文献数据验证了所建立的SE-SMR模型。 ud在绝热条件下建立了SE-CLSR过程的数学模型。该模型是催化剂还原然后氧化还原催化剂的组合。还原和氧化的单个模型是通过使用文献中提供的动力学数据开发的,随后通过文献中提出的实验结果进行了验证。 SE-SMR过程的已开发模型与OTM减少模型相结合,以模仿燃料反应堆(FR)系统中发生的动态过程。此FR与空气反应堆(AR)组合,组合模型运行10个循环。在温度(873-1023 K),压力(1-30 bar),摩尔S / C(2-6)和气相质量通量(Gs = 2- 7公斤m-2 s-1)。在这项工作中,用于生产H2的操作条件代表了实际的工业生产条件。灵敏度分析表明,开发的SE-CLSR工艺模型具有灵活性,可以模拟温度,压力,S / C和Gs的各种工作条件。

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    Abbas Syed Zaheer;

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