Abstract Using optimum conditions in CO2 capture processes to maximize CO2 capture capacity and rich amine temperature leads to saving energy and reducing costs. In the present article, an industrial CO2 capture process with aqueous MEA was studied using the sensitivity analysis and an optimization method. The process was simulated using a rate-based model. The results were validated against four different industrial operational data. In the four different industrial situations, the average relative error was 1.38%–3.85%. The liquid temperature profiles and CO2 absorption (%), calculated by the model agree with the real operational data. In the second part of the work, a sensitivity analysis of the absorption column's important variables was carried out to determine sensitive parameters for CO2 absorption capacity and rich MEA temperature. The variables are gas flow rate, solvent flow rate, flue gas temperature, inlet solvent temperature, CO2 concentration in the flue gas, loading of inlet solvent, and MEA concentration. Based on the results, all of the operational parameters except the inlet solvent and the inlet liquid temperature are considered influential. In the third and final part of the article, the operational conditions are optimized to maximize CO2 absorption (%) and rich solvent temperature. Response surface methodology (RSM) is used as a statistical optimization tool. The experimental design data were analyzed by analysis of variance (ANOVA) and fitted to the second-order polynomial equation using multiple regression analysis. By applying the optimum operational conditions in the model, CO2 absorption (%) and rich solvent temperature of 95.63% and 56.15 °C can be obtained, which indicate 13% and 17% increase, respectively compared to the base case. The results showed that the absorber's energy consumption is decreased by 16%, when applying optimum operational conditions. In contrary to previous studies, it is found that rich solution temperature is not a function of lean solution temperature. According to the results, the inlet gas flow rate is the most influential parameter in CO2 absorption and rich solution temperature.

中文翻译：

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使用基于速率的模拟、灵敏度分析和响应面方法优化工业 CO2 捕集厂

摘要 在 CO2 捕集过程中使用最佳条件来最大化 CO2 捕集能力和富胺温度，从而节省能源并降低成本。在本文中，使用敏感性分析和优化方法研究了含水 MEA 的工业 CO2 捕获过程。该过程使用基于速率的模型进行模拟。结果根据四种不同的工业运营数据进行了验证。在四种不同的工业情况下，平均相对误差为 1.38%~3.85%。模型计算的液体温度曲线和 CO2 吸收率 (%) 与实际运行数据一致。在工作的第二部分，对吸收塔的重要变量进行了敏感性分析，以确定 CO2 吸收能力和富 MEA 温度的敏感参数。变量是气体流速、溶剂流速、烟气温度、入口溶剂温度、烟气中的 CO2 浓度、入口溶剂的负载和 MEA 浓度。根据结果​​，除入口溶剂和入口液体温度外的所有操作参数都被认为是有影响的。在文章的第三部分也是最后一部分，优化了操作条件以最大限度地提高 CO2 吸收率 (%) 和富溶剂温度。响应面方法 (RSM) 用作统计优化工具。实验设计数据通过方差分析 (ANOVA) 进行分析，并使用多元回归分析拟合二阶多项式方程。通过在模型中应用最佳操作条件，CO2 吸收 (%) 和富溶剂温度分别为 95.63% 和 56。可以获得 15 °C，与基本情况相比，分别增加了 13% 和 17%。结果表明，当采用最佳运行条件时，吸收器的能耗降低了 16%。与先前的研究相反，发现富溶液温度不是贫溶液温度的函数。根据结果​​，入口气体流速是对 CO2 吸收和富溶液温度影响最大的参数。