基于热力学分析的常减压装置流程优化
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摘要
能源是人类物质活动的基础,节约能源一直是摆在学术界和工业界面前的重大课题。作为石油化工企业用能大户的常减压装置,其能量消耗约占整个炼油厂所用能量的20%～30%。目前,常减压装置的节能措施主要是从提高装置能量回收率入手。随着节能工作的深入,这方面的困难越来越大。因此,今后要进一步降低能耗,必须在降低工艺用能方面挖潜力。常减压装置的改造及设计主要依靠经验,但是近年来很多炼油装置所加工的原油品种、性质发生了较大的变化。为了分析、筛选并组合提高原油加工能力和节约能量的工艺路线,本文选取两套正在运行的进料分别为轻油及重油两种工况的常减压装置现场数据进行热力学分析,分别优化组合并设计出针对轻油及重油的最优工艺路线。
首先采集并整理现场操作数据,搭建两套装置的模型,模拟结果与现场运行数据吻合的很好,为热力学分析提供了准确的原始状态数据集。另外,根据现场数据反推得到修正的原油蒸馏曲线,并采用聚类分析的方法判断了三种原油之间的亲疏关系,表明修正在合适的范围内。
然后,在对常减压工艺流程中初馏、常压及减压单元各工艺方案深入分析的基础上,利用热力学分析模型、R软件及正交试验方法,针对现有装置单独分析初馏单元各方案,常压和减压单元采用传统流程。针对新建装置,以工艺流程中每个单元的方案变化为变量,进行全流程深入的理论分析,提出了炼制不同类型原油的优化流程。
完成流程层面的优化工作以后,利用CGCC曲线、灵敏度分析及目标函数优化,进一步进行分馏塔内部优化,以期达成整个过程的全面优化。总之,本文结合大量现场数据,基于相关热力学原理进行流程的系统分析和全面优化,研究方法和成果对同类装置用能分析的相关研究方法以及工艺优化等工业实践具有重要的参考价值。
Energy is the material base of human activity and doubtlessly saving energy is also a significant issue met with academia and industry societies. Crude distillation is so energy intensive that it reportedly requires up to 20-30% of the total that of the whole refinery. Presently, the energy conservation measures for this distillation unit are spontaneously directed to improving the energy recovery, which becomes more and more difficult along with the progress and maturity of technology in this respect. Therefore, further energy saving lies in diging latent capacity from process energy supply through process optimization. To make the whole thing worse, crudes and their features for more and more refinery distillation unit have been changed, sometimes from heavy to light. Thus, designing process scheme based on experience can hardly reach a satisfying result. In this regard, this work focuses its attention on thermodynamic analyses, screening and combination or development of two schemes individually for light and heavy cases. The whole work started with field investigation of two running atmospheric and vacuum distillation units, with their feeding, heavy and light respectively.
First, operational data from the spot were collected and processed. Then Aspen Plus platform was applied to these 2 operative modes. The simulation results describing the original flowsheet were in good accordance with the plant data, which provided datasets to thermodynamic analysis. Furthermore, the new distillation curve was deduced by plant data. And the clustering analysis of three kinds of crude was done to examine the close or distant relationships among them. This indicates that the revised distillation curve obtained is in proper range.
Then based on in-depth analysis on pre-distillation unit, atmosphere distillation unit and vacuum distillation, only the schemes of pre-distillation unit were changed aiming at revamp device, and various schemes of three units were used to carry out the permutation and combination for new device. The optimum process flows, evaluated by exergy analyses, orthogonal testing method and R software, were proposed aiming at crude with different property.
After the accomplishment of the process level optimization, Column Grand Composite Curve (CGCC), sensitivity analysis and off-line optimization were applied to optimize the column inner to reach a sound completion. In all, a system analysis and fully optimization on this issue is made based on a mass of field data under thermodynamic principles. This approach and its results can gave reference to researches about energy analyses on similar units, as well as guidance to industrial practice on process optimization.
首先采集并整理现场操作数据,搭建两套装置的模型,模拟结果与现场运行数据吻合的很好,为热力学分析提供了准确的原始状态数据集。另外,根据现场数据反推得到修正的原油蒸馏曲线,并采用聚类分析的方法判断了三种原油之间的亲疏关系,表明修正在合适的范围内。
然后,在对常减压工艺流程中初馏、常压及减压单元各工艺方案深入分析的基础上,利用热力学分析模型、R软件及正交试验方法,针对现有装置单独分析初馏单元各方案,常压和减压单元采用传统流程。针对新建装置,以工艺流程中每个单元的方案变化为变量,进行全流程深入的理论分析,提出了炼制不同类型原油的优化流程。
完成流程层面的优化工作以后,利用CGCC曲线、灵敏度分析及目标函数优化,进一步进行分馏塔内部优化,以期达成整个过程的全面优化。总之,本文结合大量现场数据,基于相关热力学原理进行流程的系统分析和全面优化,研究方法和成果对同类装置用能分析的相关研究方法以及工艺优化等工业实践具有重要的参考价值。
Energy is the material base of human activity and doubtlessly saving energy is also a significant issue met with academia and industry societies. Crude distillation is so energy intensive that it reportedly requires up to 20-30% of the total that of the whole refinery. Presently, the energy conservation measures for this distillation unit are spontaneously directed to improving the energy recovery, which becomes more and more difficult along with the progress and maturity of technology in this respect. Therefore, further energy saving lies in diging latent capacity from process energy supply through process optimization. To make the whole thing worse, crudes and their features for more and more refinery distillation unit have been changed, sometimes from heavy to light. Thus, designing process scheme based on experience can hardly reach a satisfying result. In this regard, this work focuses its attention on thermodynamic analyses, screening and combination or development of two schemes individually for light and heavy cases. The whole work started with field investigation of two running atmospheric and vacuum distillation units, with their feeding, heavy and light respectively.
First, operational data from the spot were collected and processed. Then Aspen Plus platform was applied to these 2 operative modes. The simulation results describing the original flowsheet were in good accordance with the plant data, which provided datasets to thermodynamic analysis. Furthermore, the new distillation curve was deduced by plant data. And the clustering analysis of three kinds of crude was done to examine the close or distant relationships among them. This indicates that the revised distillation curve obtained is in proper range.
Then based on in-depth analysis on pre-distillation unit, atmosphere distillation unit and vacuum distillation, only the schemes of pre-distillation unit were changed aiming at revamp device, and various schemes of three units were used to carry out the permutation and combination for new device. The optimum process flows, evaluated by exergy analyses, orthogonal testing method and R software, were proposed aiming at crude with different property.
After the accomplishment of the process level optimization, Column Grand Composite Curve (CGCC), sensitivity analysis and off-line optimization were applied to optimize the column inner to reach a sound completion. In all, a system analysis and fully optimization on this issue is made based on a mass of field data under thermodynamic principles. This approach and its results can gave reference to researches about energy analyses on similar units, as well as guidance to industrial practice on process optimization.
引文
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