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Multi-objective optimisation of a double contact double absorption sulphuric acid plant for cleaner operation

机译:双触点双吸收硫酸装置清洁运行的多目标优化

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The release of oxides of sulphur (SOX) and acid mist (H2SO4) during the production of sulphuric acid in the double contact double absorption (DCDA) process is hazardous to the environment. It is a challenging task to minimise these emissions while keeping plant operation within the production requirements and maximise revenue. In this study, SOx emissions, acid mist emissions, and net revenue are considered as objectives for multi-objective optimisation (MOO) of the DCDA process. Firstly, the process is modelled and simulated in Aspen HYSYS, and validated with plant data. MOO is then performed using the elitist non-dominated sorting genetic algorithm to predict sets of Pareto-optimal operating conditions for improved environmental and economic performance. The effect of operating parameters such as air flow rate and pressure, inlet temperatures to catalytic beds and absorbers, demineralized water flow rate, and boiler feed water flow rate on the process performance is also studied. The results show that the DCDA process can be operated at different optimal conditions, each of which involves some trade-off among the objectives of interest. A multi-criteria decision-making technique (known as technique for order of preference by similarity to ideal solution, TOPSIS) is used to determine the most suitable optimum operating point. Among the optimal conditions, the chosen solution through TOPSIS has 9.5 ppm of SOx emissions, 70.9 ppm of acid mist emission and 143.0 MS/y of net revenue (i.e., gross profit). The air flow rate strongly influences the objectives in opposite direction; at the selected optimum solution, it provides improved environmental and economic performance within acceptable limits of product quality. (C) 2018 Elsevier Ltd. All rights reserved.
机译:在双接触双吸收(DCDA)工艺中生产硫酸时,释放出硫氧化物(SOX)和酸雾(H2SO4)对环境有害。最大限度地减少这些排放,同时使工厂的运营保持在生产要求之内并最大化收入,这是一项艰巨的任务。在本研究中,SOx排放,酸雾排放和净收入被视为DCDA流程的多目标优化(MOO)的目标。首先,在Aspen HYSYS中对过程进行建模和仿真,并使用工厂数据进行验证。然后使用精英非支配排序遗传算法执行MOO,以预测帕累托最优操作​​条件集,以改善环境和经济绩效。还研究了诸如空气流速和压力,催化床和吸收塔入口温度,软化水流速和锅炉给水流速等操作参数对工艺性能的影响。结果表明,DCDA过程可以在不同的最佳条件下运行,每个条件都涉及目标之间的一些权衡。使用多标准决策技术(通过与理想解决方案相似,称为优先顺序技术,TOPSIS)来确定最合适的最佳工作点。在最佳条件中,通过TOPSIS选择的解决方案具有9.5 ppm的SOx排放,70.9 ppm的酸雾排放和143.0 MS / y的净收入(即毛利润)。空气流速会反方向强烈影响目标。在选定的最佳解决方案下,它可以在可接受的产品质量范围内提供改善的环境和经济性能。 (C)2018 Elsevier Ltd.保留所有权利。

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