Reforming process model 13 kinetic lumps

While the 13 hydrocarbon lumps accurately represent the hydrocarbon conversion kinetics, they must be delumped for the deactivation kinetics. In addition, delumping is necessary to estimate many of the product properties and process conditions important to an effective reformer process model. These include H2 consumption, recycle gas H2 purity, and key reformate properties such as octane number and vapor pressure. The following three lump types had to be delumped the C5- kinetic lump into Cl to C5 light gas components, the paraffin kinetic lumps into isoparaffin and n-paraffin components, and the Cg+ kinetic lumps into Cg, C9, C10, and Cn components by molecular type. 

A kinetic model for the naphtha catalytic reforming process, which utilizes lumped mathematical representation of the reactions that take place, is presented. The reaction are written in terms of isomers of the same nature, which range from 1 to 11 atoms of carbon for paraffins, and from 6 to 11 carbon atoms for naphthenes and aromatics. The kinetic parameters values were estimated using experimental information obtained in a fixed-bed pilot plant. The pilot reactor was loaded with different amounts of catalyst in order to simulate a series of three reforming reactors. The reformate composition calculated with the proposed model agrees very well with experimental information. 

The last sets of correlations we will address are composition correlations. These correlations identify chemical composition in terms of total paraffin, naphthene and aromatic (PNA) content of a particular feed based on key bulk measurements. These correlations are useful in two respects. First, we use these correlations to screen feeds to different refinery reaction units. For example, we may wish to send a more paraffinic feed to a reforming process when we want to increase the yield of aromatic components from the refinery. Secondly, these types of correlations form the basis of more detailed lumping for kinetic models that we will discuss at great length in subsequent chapters of this book. We will use these types of correlations to build extensive component lists that we can use to model refinery reaction processes. 

Table 5.5 summarizes the key features in reported unit-level models (using lumped kinetics) applied to reforming processes. We have only included studies where the authors compare their results to pilot-plant or industrial data. In addition, we include those studies where the authors use the model for case studies and plant optimization. 

Figure 5.54 shows the Feed Data tab from the Reformer sub-model. The Feed Type is a basic set of relationships and initial values for the all kinetic lumps in the reactor model. Aspen HYSYS uses bulk property information such as density, distillation curves and total PNA content in conjunction with the feed type to predict the composition of feed lumps to the model. The Default type is sufficient for hght-to-heavy naphtha. However, there is no guarantee that a particular feed type represents the actual feed accurately. Aspen HYSYS will attempt to manipulate the feed composition to satisfy bulk property measures given. In general, we advise users to develop a few sets of compositional analysis to verify the kinetics lumps calculated by Aspen HYSYS. We discuss a process to verify these lumps later. 

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