《Optimization of hydrogen production with CO2 capture by autothermal chemical-looping reforming using different bioethanol purities》

  • 来源专题:生物质生化转化信息监测
  • 编译者: giecinfo
  • 发布时间:2016-03-24
  • Autothermal Chemical-Looping Reforming (a-CLR) is a process which allows hydrogen production avoiding the environmental penalty of CO2 emission typically produced in other processes. The major advantage of this technology is that the heat needed for syngas production is generated by the process itself. The heat necessary for the endothermic reactions is supplied by a Ni-based oxygen-carrier (OC) circulating between two reactors: the air reactor (AR), where the OC is oxidized by air, and the fuel reactor (FR), where the fuel is converted to syngas. Other important advantage is that this process also allows the production of pure N2 in the AR outlet stream. A renewable fuel such as bioethanol was chosen in this work due to their increasing worldwide production and the current excess of this fuel presented by different countries.

    In this work, mass and heat balances were done to determine the auto-thermal conditions that maximize H2 production, assuming that the product gas was in thermodynamic equilibrium. Three different types of bioethanol has been considered according to their ethanol purity; Dehydrated ethanol (≈100 vol.%), hydrated ethanol (≈96 vol.%), and diluted ethanol (≈52 vol.%). It has been observed that the higher H2 production (4.62 mol of H2 per mol of EtOH) has been obtained with the use of diluted ethanol and the surplus energy needed could be compensated by the energy save achieved during the purification of ethanol in the production process.

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    • 来源专题:广州能源研究所信息监测
    • 编译者:giecinfo
    • 发布时间:2016-03-17
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    • 来源专题:广州能源研究所信息监测
    • 编译者:giecinfo
    • 发布时间:2016-03-24
    • The purpose of this paper is to develop a model for the decision-makers/stakeholders to design biofuel supply chain under uncertainties. Life cycle energy and CO2 emission of biofuel supply chain are employed as the objective functions, multiple feedstocks, multiple transportation modes, multiple sites for building biofuel plants, multiple technologies for biofuel production, and multiple markets for biofuel distribution are considered, and the amount of feedstocks in agricultural system, transportation capacities, yields of crops, and market demands are considered as uncertainty variables in this study. A bi-objective interval mix integer programming model has been developed for biofuel supply chain design under uncertainties, and the bio-objective interval programming method has been developed to solve this model. An illustrative case of a multiple-feedstock-bioethanol system has been studied by the proposed method, and the results show that the proposed model can help decision-makers/stakeholders plan and design the biofuel supply chain by proposing feasible solutions to them.