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Automated process synthesis for optimal flowsheet design of a hybrid membrane cryogenic carbon capture process

机译:自动过程合成,可为混合膜低温碳捕获过程的最佳流程设计提供条件

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Process flowsheet synthesis is one critical step in the design of any chemical process and is a key factor for consideration in plant operation and economic efficiencies. Previously an automated process flow sheet synthesis is outlined that using a systematic computational approach. This method considers the design and operation variables to converge to an optimum flowsheet using genetic algorithm (GA). In this study, this algorithm is implemented to investigate the potential for a hybrid process combining membrane and cryogenic separation to achieve an efficient and effective carbon dioxide (CO2) capture plant design. The optimum flowsheet is selected using an objective function by screening among a variety of random flowsheets. The studied objective function is a combination of three effective factors in the performance of a flowsheet for this process which are: permeate CO2 purity, CO2 recovery of the system, and energy penalty of the configuration. The outcome of the optimization algorithm is presented as a structurally and parametrically optimized process flowsheet. Within the defined constraints the algorithm estimates that the optimum configuration of a hybrid structure of the membrane/cryogenic system for a three membrane unit process can provide CO2 permeate purity of 0.941, CO2 recovery of 0.979 and energy penalty of 1.249 GJ/t. While the same values for a membrane-based CO2 capture system are 0.940, 0.865 and 3.722 for the optimum estimated flowsheet. The presented results for the optimum hybrid process in comparison with other options shows a promising possibility of exchanging conventional technologies with the proposed optimal configuration. These results along with a global optimality analysis demonstrate the value of automated process synthesis in developing optimal process flowsheet designs. (C) 2017 Elsevier Ltd. All rights reserved.
机译:工艺流程图的合成是任何化学工艺设计中的关键步骤,并且是在工厂运营和经济效率中考虑的关键因素。以前,概述了使用系统计算方法的自动过程流程图综合。该方法使用遗传算法(GA)考虑设计和操作变量以收敛到最佳流程图。在这项研究中,该算法的实施旨在研究将膜和低温分离相结合以实现高效,有效的二氧化碳(CO2)捕集装置设计的混合过程的潜力。使用目标函数通过在各种随机流程图中进行筛选来选择最佳流程图。研究的目标函数是该过程流程图性能中三个有效因素的组合,这些因素是:渗透CO2纯度,系统的CO2回收率以及配置的能耗。优化算法的结果显示为结构和参数优化的过程流程图。在定义的约束条件下,算法估计,用于三膜单元工艺的膜/低温系统混合结构的最佳配置可以提供0.941的CO2透过水纯度,0.979的CO2回收率和1.249 GJ / t的能量损失。对于最佳估算流程,基于膜的CO2捕集系统的相同值为0.940、0.865和3.722。与其他选项相比,最佳混合过程的呈现结果显示了用建议的最佳配置替换传统技术的可能性。这些结果与全局最优性分析一起证明了自动化过程综合在开发最优过程流程图设计中的价值。 (C)2017 Elsevier Ltd.保留所有权利。

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