某提氦装置工艺优化研究

发布时间：2018-03-03 13:23

本文选题：氦气　切入点：天然气提氦　出处：《西南石油大学》2015年硕士论文　论文类型：学位论文

【摘要】：氦气是保障我国国防安全和经济发展的一种重要稀有气体资源,因其独特性质被广泛应用于多种领域。目前,从天然气中提取氦气是工业用氦的主要来源。我国氦资源十分贫乏,如何高效、节能的从天然气中提取氦气成为国内重要研究课题。深冷法是目前天然气提氦的主要方法。某天然气提氦装置采用深冷法进行提氦,在实际生产运行中,装置的提氦塔和压缩机等主要设备由于操作参数的影响导致该生产装置能耗较大,针对该提氦装置的现状分析,对该天然气提氦装置进行工艺参数优化研究,使其有效降低能耗,且满足装置的实际生产。本论文利用Aspen-HYSYS对该天然气提氦装置工艺流程进行了流程模拟,并对关键设备进行了能耗分析。通过对装置可控参数进行单因素分析,分析比较各参数对总能耗和粗氦摩尔比的影响程度,确定四个优化因素,分别为一级提浓塔进料温度、一级提浓塔进料压力、一级提浓塔塔底物流分配比和二级提浓塔回流比。在参数分析基础是,采用响应面优化法拟合出优化参数与能耗、二次粗氦摩尔比之间的回归关系式,并分析多因素的交互作用,结果表明：一级提浓塔进料压力与一级提浓塔塔底物流分配比、级提浓塔进料温度与一级提浓塔塔底物流分配比、一级提浓塔进料温度与一级提浓塔进料压力之间存在显著交互作用,其交互作用大小关系为：一级提浓塔进料压力与一级提浓塔塔底物流分配比交互作用一级提浓塔进料温度与一级提浓塔塔底物流分配比交互作用一级提浓塔进料温度与一级提浓塔进料压力交互作用。在对响应面回归方程方差分析的基础上,合理简化原拟合出的多项式模型,以总能耗最小为优化目标,四个优化因素的优化范围为约束条件,对简化后的方程进行能耗优化。结果显示,优化因素的最优值分别为一级提浓塔进料温度-116.93℃、一级提浓塔进料压力2205.56kPa、一级提浓塔塔底物流分配比0.09、二级提浓塔回流比4.74,优化后的总能耗降低31.6%。
[Abstract]:Helium is a kind of important rare gas resources security in our country national security and economic development, because of its unique properties and have been widely used in many fields. At present, extracted from natural gas helium is the main source of industrial helium. Helium resource in China is very poor, how efficient, energy extraction from natural gas is helium an important research topic in China. Cryogenic method is the main method of natural gas helium. A gas helium extraction device for helium by cryogenic method, in the practical operation, the main equipment of the helium compressor tower and due to the influence of operating parameters to the energy consumption of production equipment is large, according to the analysis of the current situation of helium. Device, study of parameters optimization for the gas helium extraction device, which effectively reduces the energy consumption, and meet the actual production device.
Aspen-HYSYS in the gas extraction process of helium device of process simulation in this paper, and the key equipment of energy analysis. Through single factor analysis of device parameters, analysis and comparison of various parameters impact on the total energy consumption and crude helium mole ratio, determine the four optimization factors, namely a concentrated the column feed temperature, level of concentration tower feeding pressure and the level of concentration in the bottom of the logistics distribution ratio and two concentrated reflux ratio. In the parameter analysis is based on the fitting, parameter optimization and energy consumption of RSM, the regression relation between the two crude helium mole ratio, and analysis the interaction of multiple factors, the results showed that the level of concentration tower and feed pressure level is concentrated in the bottom of the logistics distribution ratio, level of concentration tower feed temperature and level of concentration in the bottom of the logistics distribution ratio, level of concentration tower feed temperature and level of concentration tower There was a significant interaction between the feeding pressure and the interaction relationship of size is: a concentrated feed the tower pressure and a concentrated in the bottom of the logistics distribution ratio of the interaction level of concentration tower feed temperature and level of concentration in the bottom of the logistics distribution ratio of the interaction level of concentration tower feed temperature with a concentrated column feed pressure interaction.
Based on the response surface regression equation analysis of variance, simplified polynomial model fitting out, with the minimum total energy consumption as the optimization objective, the optimization range of four optimization factors as constraint conditions, the energy consumption optimization of the simplified equations. The results show that the optimization of the optimal values of the factors were level of concentration tower the feed temperature of -116.93 DEG C, a concentrated column feed pressure of 2205.56kPa, a concentrated in the bottom of logistics distribution ratio of 0.09, two concentration column reflux ratio was 4.74, the total energy consumption optimization after reducing 31.6%.

【学位授予单位】：西南石油大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TQ116.41

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