催化裂化汽油脱硫精制技术研究进展

催化裂化汽油是我国车用汽油的主要调和来源,但是硫含量远高于车用汽油质量标准的要求值;因此如何高效降低硫含量是催化裂化汽油精制处理的关键。本文综述了国内外催化裂化汽油脱硫精制生产技术。从选择性加氢脱硫技术（Prime-G⁺技术、SCANfining技术、CD Tech技术、RSDS技术、OCT-M技术和DSO技术）,选择性加氢脱硫耦合辛烷值恢复技术（RIDOS技术和GARDES技术）以及吸附脱硫技术（S-Zorb技术）三方面来阐述国内外催化裂化汽油清洁化技术的原理、特点及其应用。指出深度脱硫和辛烷值保持、烯烃饱和率之间的矛盾,后续研究者仍需在工艺流程改进、工艺条件优化以及新型催化剂开发等方面做出巨大努力。     

Refinery continuous-time crude scheduling with consideration of long-distance pipeline transportation

In reality, crudes from unloading storage tanks at a docking berth may experience long-distance pipeline transportation to refinery charging tanks before their processing by crude distillation units. Such pipeline transportations cause significant transport delay and crude holdup that will substantially affect plant production performance. Unfortunately, current short-term crude scheduling studies have never systematically considered these issues. In this work, a new continuous-time crude scheduling model has been developed, which addresses the long-distance pipeline transportation and other realistic considerations such as brine settling and multiple jetties for crude unloading. The feeding of crudes into pipeline, and crude movements inside pipeline, as well as crude discharging to the receiving charging tanks are combined with the continuous time formulation of crude scheduling. The efficacy of the developed scheduling model has been demonstrated by three case studies including one industrial size example. An outer-approximation (OA) based iterative algorithm (Karuppiah et al., 2008) is implemented to successfully solve the case studies.     

Multi-objective optimization for the periodic operation of the naphtha pyrolysis process using a new parallel hybrid algorithm combining NSGA-II with SQP

Nowadays naphtha pyrolysis is the most important process for ethylene production, which can bring along another important monomer, namely propylene. The demand of both the ethylene and propylene has recently increased dramatically and naphtha pyrolysis is indispensable to satisfy the demand of both crucial products simultaneously, resulting in a typical multi-objective optimization problem. The nondominated sorting genetic algorithm (NSGA-II), which has been successfully applied to many multi-objective optimization problems, cannot efficiently generate the Pareto set which spreads as widely as the true Pareto front in a limited time, meanwhile, its convergence process is rather slow and could not meet the speed requirement when used for the complicated industrial problem mentioned above. To efficiently solve the multi-objective optimization problem of the industrial complicated chemical processes, this paper first proposed a new parallel hybrid multi-objective optimization algorithm combing NSGA-II with SQP (Successive Quadratic Programming) used to improve the efficiency of the NSGA-II and the quality of the Pareto-optimal set. Then the multi-objective operation optimization model of naphtha pyrolysis was established, and at last the application of the proposed algorithm to improve the performance of an industrial naphtha pyrolysis process was presented and analyzed.     

Modified molecular matrix model for predicting molecular composition of naphtha

To improve the naphtha composition prediction model based on molecular type homologous series matrix (MTHS), this paper puts forward a novelmolecular matrix to characterize the naphtha composition and the normal distribution hypothesis to better describe the molecular composition distribution within each homologous series of the molecular matrix. Through prediction calculation of eight groups of naphtha samples and eight groups of gasoline samples, it is verified that the normal distribution hypothesis is more applicable than gamma distribution hypothesis for the prediction model. According to the prediction results of the samples, the restrain range of normal distribution parameters during model computing process is summarized. With the bulk properties of naphtha samples and the value range of distribution parameters as input conditions, this study utilizes the improved novelmolecular matrix to predict the composition of naphtha samples. As the results show, the novel molecular matrix can predict more detailed composition information of naphtha and improve prediction accuracy with less unknown parameters.     

石脑油和轻烃资源裂解方式优选研究

由于我国轻烃资源缺乏,而石脑油资源相对丰富,考虑将其掺入石脑油进行共裂解。在实验室裂解装置上对油田轻烃、拔头油的分组裂解以及与石脑油共裂解的产物收率变化进行了研究,得出油田轻烃、拔头油的分组裂解优于与石脑油共裂解,因此探讨了拔头油与油田轻烃共裂解的可行性,提出在原料短缺的情况下,可根据"性质相近"的原则进行共裂解,即可将油田轻烃与拔头油掺混进行共裂解。同时在工业裂解炉上进行了拔头油与石脑油共裂解标定试验,得出的结论与实验室结论一致。     

二氧化碳+重整汽油拟二元体系高压汽液平衡数据的测定及关联

为了满足超临界CO2回收溶剂法提取油砂沥青的提取溶剂重整汽油的工艺需要,采用可变体积高压相平衡装置,在温度为30.3～70.2℃下,测定了4.02～14.01MPa范围内CO2-重整汽油拟二元体系的气液两相的平衡组成、密度以及摩尔体积。通过得到的结果确定了利用超临界二氧化碳来回收重整汽油的操作条件范围。利用基团贡献法估算了重整汽油的特性参数。采用Peng-Robinson方程拟合回归实验数据,得到了CO2-重整汽油体系的交互参数,计算出CO2-重整汽油体系的相平衡数据,结果表明计算值与实验值吻合较好。     

国内溶剂油精制技术现状

介绍了国内溶剂油精制技术的现状。催化加氢脱芳烃技术在工业生产中广泛应用，在适合的条件下，可以将原料中的芳烃脱除至较低水平；现有脱硫技术可以将溶剂油中的硫脱除至0.5 μg·g^-1以下。目前，我国溶剂油质量与国际溶剂油质量差距较大,生产符合国际质量标准的低芳烃和低硫含量的环保型溶剂油是今后发展的方向。     

混合型抗爆剂在石脑油调和汽油中的应用研究

开发了一种新型混合抗爆剂,对石蜡基、环烷基等原油炼制的汽油具有显著的提高辛烷值的作用。在对基础油分析基础上,针对性地设计出一种新型的混合抗爆剂,进行了优化研究。结果表明,该混合型汽油抗爆剂对汽油辛烷值的感受性较好,在基础油中加入质量分数3%—4%最为合适,综合成本与性能因素,基础油中精制催化汽油与石脑油的体积比在1.2∶1最为合适。混合抗爆剂不含国家限制或限量的铅等有机金属,稳定性好,适于长期储存,有一定的清洁性和节能效果,而且外观感观性好。     

石脑油裂解炉的维护

中国石油吉林石化公司有机合成厂乙烯车间裂解炉一直是以轻柴油为裂解原料的,由于轻柴油价格上调,石脑油价格下降,为了提高经济效益,该厂决定在F-107炉实现石脑油裂解。笔者对裂解炉的选材、施工到操作,及炉管的维护措施进行了初步探讨,旨在延长炉管使用寿命,保证生产平稳运行。     

煤基石脑油裂解丙烯在聚丙烯生产中粉料结块问题及处理

国家能源集团宁夏煤业有限责任公司烯烃二分公司聚丙烯装置,采用工艺为LUMMUS NOVOLEN工艺,所用原料丙烯来自世界上首套以煤基石脑油为原料的乙烯装置。自2017年9月投产以来,聚丙烯反应器内一直存在不同程度的粉料结块问题。结合近年来对原料组分的分析和"三剂"的使用,对反应器内粉料结块问题进行剖析和总结,提出相应处理建议,以提高反应器稳定运行。     

石脑油萃取脱芳烃技术研究进展

现有的萃取脱芳烃工艺技术成熟,种类多,工业应用广,但在处理低芳烃含量的石脑油(质量分数小于15%)时普遍存在能耗高、经济效益低等问题。本文回顾了萃取脱芳烃的多种工艺,重点讨论了常规溶剂和离子液体对石脑油中芳烃的萃取效果,认为常规溶剂中的环丁砜、N-甲基吡咯烷酮以及复合溶剂环丁砜(水)-三甘醇、环丁砜(水)-N-甲基吡咯烷酮、环丁砜-2-丙醇、RAH-1脱芳烃效果优异,能为改进目前的石脑油萃取脱芳烃工艺提供基础数据;离子液体中咪唑类离子液体如1-丁基-3-甲基咪唑六氟磷酸盐、1-丁基-3-甲基咪唑双(三氟甲基磺酰)亚胺盐、1-丁基-3-甲基咪唑四氯化铁等,有潜力用于低芳烃的石脑油萃取脱芳中,指出开发能够对复杂原料中低含量芳烃萃取的新型离子液体将会是以后的研究方向。     

催化裂化汽油清洁化技术研究开发进展

为满足日益严格的清洁汽油标准不断降低硫和烯烃含量的需求,国内外在汽油清洁化领域开展了大量的研究工作。本文综述了近年来相关研究开发工作的进展,概述了催化裂化汽油中硫化物和烯烃的分布及特点、各种烃类的辛烷值、各种烯烃的加氢反应活性及其对加氢脱硫反应的抑制作用,重点分析比较了国内外典型的催化裂化汽油清洁化工艺技术（包括选择性加氢脱硫工艺、选择性加氢脱硫-烯烃定向转化工艺、临氢吸附脱硫工艺以及选择性加氢脱硫-溶剂抽提组合工艺）的优缺点,简述了加氢脱硫催化剂的活性相模型及选择性加氢脱硫催化剂的研究开发现状,指出实现烯烃的定向转化将是未来催化裂化汽油清洁化技术的重点研发方向,以期为后续的研究开发提供参考。     

Emergy evaluation of aromatics production from methanol and naphtha

Aromatics are traditionally produced by the catalytic reforming of naphtha. However, with the demand of aromatics increasing and the reserves of petroleum resources declining, measures should be made to reduce the dependence of aromatics production on petroleum resources. Methanol-to-aromatics is proved to be an effective way to replace traditional naphtha-to-aromatics path. In order to compare the economic and environmental performance of aromatics production from naphtha and methanol, this paper carries out an emergy evaluation for each system by sorting out the simulation and literature data. Based on the emergy data collected, the emergy indices of each system are calculated. The results show that the sustainabilities of methanol-to-aromatics systems are higher than that of the naphtha-to-aromatics system, indicating the advantages of aromatics production from methanol. Among the methanol-to-aromatics systems, the aromatics from biomass-methanol system has the highest sustainability, indicating that the biomass based methanol-to-aromatics system is worth promoting. The sustainability indexes of methanol-to-aromatics systems based on coal and coke oven gas are less than 1, which means unsustainable. Meanwhile, the sustainability of natural gas based system is slightly higher than 1. The economic and environmental benefits of these systems can be optimized by improving resource utilization and reducing investment costs. Furthermore, the combination of different raw materials for methanol production should be considered.     

优化乙烯石脑油提高乙烯收率

介绍广泛分公司加工原油的特点和乙烯石脑油组成与乙烯收率的关联情况，分析了影响乙烯收率的主要原因，并着重论述了优化乙烯石脑油的具体措施。     

石脑油高效资源化研究进展

为了实现石脑油的高效资源化利用,需开发石脑油高效分离技术。简述了石脑油正/异构烷烃吸附分离原理及分离技术现状,介绍了新型吸附剂材料的研发进展,包括金属有机框架材料(MOFs)、沸石咪唑框架材料(ZIFs)、碳分子筛(CMS)、中空沸石分子筛等,阐述了新型吸附材料对正构烷烃的分离效果和分离机理,探讨了新型吸附剂、膜分离技术和吸附-膜分离耦合技术用于分离石脑油中正/异构烷烃的可行性,展望了新型正/异构烷烃分离技术,以期为石脑油高效资源化利用提供新途径。     

Economics of the oxidative coupling of methane as an add-on unit for naphtha cracking

The feasibility of methane coupling as an add-on unit to a naphtha cracker was studied. The existing cold box was used for separation of ethylene and unconverted methane, but arrangements were made for separation of the coupling by-products. The cracker's methane was used as a feedstock. The concept is technically and economically feasible at spring 1992 prices, provided the catalyst meets the assumed 30% conversion and 80% C₂ selectivity.     

神府煤液化油石脑油馏分重整生产芳烃的研究

由于煤液化油石脑油馏分(200℃)中芳烃潜含量较高,利用煤液化油石脑油馏分为原料,进行加氢精制,将原料中的硫氮含量降至1 mg/kg左右,满足重整进料要求,然后在小型固定床连续反应器上进行加氢重整生产芳烃试验。着重考察重整反应前、后族组成的变化及主要芳烃化合物的产率。结果表明,加氢重整过程中发生正构烷烃异构化反应;环烷烃主要发生脱氢芳构化反应转化为芳香烃;煤液化油石脑油馏分适宜进行催化重整,C_1~C_4烃气产率6.03%,氢气产率3.60%;重整后,芳烃含量达83.20%,其中C_6~C_8芳烃含量61.03%,是提取BTX的良好原料。石脑油的馏程对芳烃的组成和产率有一定影响,适宜的馏程为60~160℃。     

石脑油催化裂解结构化反应器反应特性的CFD模拟

以石脑油为原料,采用催化裂解六集总动力学模型,建立描述结构化反应器内催化裂解的反应器数学模型,并利用CFD软件对结构化反应器内的石脑油催化裂解性能进行数值模拟。通过改变孔道直径、反应器长度以及反应器内温度、气体入口速率考察反应器结构尺寸和反应条件对目标产物乙烯、丙烯的收率及石脑油转化率的影响。结果表明,反应器孔道直径的增加,目标产物收率减小,反应器长度20 mm时反应完全,升高反应温度和增大入口速率均有利于目标产物的生成。在入口温度680 ℃和入口速率0.4 m·s^-1条件下,石脑油转化率92%,乙烯收率19.3%,丙烯收率23.1%。而在相同反应条件下的固定床反应器中乙烯收率10.3%,丙烯收率13.3%,石脑油转化率80.0%。     

前置抽提优化裂解原料的石脑油芳烃抽提大型化研究

大型乙烯联合装置采用前置抽提芳烃流程工艺技术,以优化裂解原料面临"放大效应"这个工程现实问题。应用萃取精馏过程大型化基础理论分析大型石脑油芳烃抽提萃取精馏过程,得出:对于生产规模为3.31 M t/a的大型芳烃抽提装置,需要选择最佳回流比和最佳溶剂浓度,其最佳设计方案可以保证生产装置长周期、满负荷平稳运行;同时,强化设计大型塔盘和大型塔器代替常规尺寸的塔器设备,既可减少投资,又可节能降耗,发挥"规模效应";对于不同类型大型塔盘和大型塔内件的优化设计能否适用于大型石脑油芳烃抽提装置,需要运用计算流体力学CFD和大型冷模试验进行验证,以保证研究成果的先进性和可靠性。     

Application of convolutional neural networks to large-scale naphtha pyrolysis kinetic modeling

System design and optimization problems require large-scale chemical kinetic models. Pure kinetic models of naphtha pyrolysis need to solve a complete set of stiff ODEs and is therefore too computational expensive. On the other hand, artificial neural networks that completely neglect the topology of the reaction networks often have poor generalization. In this paper, a framework is proposed for learning local representations from large-scale chemical reaction networks. At first, the features of naphtha pyrolysis reactions are extracted by applying complex network characterization methods. The selected features are then used as inputs in convolutional architectures. Different CNN models are established and compared to optimize the neural network structure. After the pre-training and fine-tuning step, the ultimate CNN model reduces the computational cost of the previous kinetic model by over 300 times and predicts the yields of main products with the average error of less than 3%. The obtained results demonstrate the high efficiency of the proposed framework.