Model refinery

Refinery Bleach. Various bleaching clays purify and remove color bodies from refined oils. These wastes contain 5% to 35% oil. The characteristics of these materials are such that they will combust spontaneously, which has created problems for disposal in sanitary landfills, as well as at factory locations in some instances, but this condition can be overcome by several methods. The model refinery presented in the previous section will generate about 2500 kg of waste earth per day, of which 570 kg is oil. 

Spent Hydrogenation Nickel Catalyst. Nickel catalyst is used in the hydrogenation of oil. Depending on the processor, catalyst may be recycled many times therefore, waste generation rates differ. However, the model refinery will generate about 100 kg of spent catalyst per day. 

Several of the commercial simulation programs offer preconfigured complex column rigorous models for petroleum fractionation. These models include charge heaters, several side strippers, and one or two pump-around loops. These fractionation column models can be used to model refinery distillation operations such as crude oil distillation, vacuum distillation of atmospheric residue oil, fluidized catalytic cracking (FCC) process main columns, and hydrocracker or coker main columns. Aspen Plus also has a shortcut fractionation model, SCFrac, which can be used to configure fractionation columns in the same way that shortcut distillation models are used to initialize multicomponent rigorous distillation models. 

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. 

This chapter discusses several key modeling steps regarding thermophysical properties of crude oil and petroleum fractions. The basic process for developing a set of pseudocomponents for modeling refinery fractionation systems is as follows ... 

While this chapter has focused extensively on the requirements for modeling fractionation systems, we can use the same techniques in the context of modeling refinery reaction process as well. We illustrate this process in Chapters 4 through 6 of this text It is possible to obtain good predictive results for fractionation systems provided that we make reasonable choices for the thermodynamic models and physical properties of the pseudocomponents involved. 

The most important consideration for a reactor model is an accurate measure of the feed composition. This is particularly troublesome when modeling refinery reaction processes. Feed to units may change quickly and unpredictably. While refinery techniques for online measurements of feed composition have improved, many still do not perform detailed molecule-based analysis required for complex kinetic models. Without an accurate and update-to-date feed composition, kinetic models lail to make reasonable predictions of product yield and process performance. 

Classification Process simulation refers to the activity in which mathematical models of chemical processes and refineries are modeled with equations, usually on the computer. The usual distinction must be made between steady-state models and transient models, following the ideas presented in the introduction to this sec tion. In a chemical process, of course, the process is nearly always in a transient mode, at some level of precision, but when the time-dependent fluctuations are below some value, a steady-state model can be formulated. This subsection presents briefly the ideas behind steady-state process simulation (also called flowsheeting), which are embodied in commercial codes. The transient simulations are important for designing startup of plants and are especially useful for the operating of chemical plants. 

Finally, in this Introduction, it is worthwhile to reproduce one of the several current definitions, in the Oxford English Dictionary, of the word simulate To imitate the conditions or behaviour of (a situation or process) by means of a model, especially for the purpose of study or training specifically, to produce a computer model of (a process) . The Dictionary quotes this early (1958) passage from a text on high-speed data processing A computer can simulate a warehouse, a factory, an oil refinery, or a river system, and if due regard is paid to detail the imitation can be very exact . Clearly, in 1958 the scientific uses of computer simulation were not yet thought worthy of mention, or perhaps the authors did not know about them. 

While this unit is considerably cheaper, it also has certain disadvantages. For example, changes or upsets in any one unit may be felt throughout the refinery because of the changes in fractionator operation. However, the considerable cost saving possible with the combination type unit has permitted many small refineries to finance a catalytic cracking unit when they could not afford a conventional model. 

Figure 1-16B. Detailed layout and piping model for a refinery unit. Courtesy of Socony Mobil Oil Co. Inc.

First commercial FCC unit (Model I upflow design) started up at Standard of New Jersey s Baton Rouge, Louisiana, refinery. 

An important consequence of sucrose degradation is the development of color from degradation products. Kuridis and Mauch60 have developed an equation for the prediction of color development in model sucrose solutions. Color development was expressed as a function of temperature (90 to 120°C), time (0 to 80 min), pH (7.5 to 9.5), and composition of the solution (sucrose 20 to 60%, invert sugar 0.02 to 0.18%, and amino acids 1 to 3 g/L). The authors claimed, with caution, that the effects of an intended alteration in a unit process in the refinery can be predicted in advance. 

The bulk chemical commodity producing companies (e.g., refineries, petrochemicals) have been practicing this philosophy for some time, using dynamic models to contain operational variability through feedback controllers, and employing static models to determine the optimal levels of operating conditions (Lasdon and Baker, 1986 Garcia and Prett, 1986). 

Hydrodesulfurization (HDS) is a very important large-scale process used in refineries to remove sulfur from oil products. It is actually one of the largest catalytic processes. As a model system for this process we shall consider the HDS of thio-... 

The refinery will evolve to meet the market (and so, the environmental) needs. Some characteristics are easy to foresee versatility, integration from resources to final user ( well-to-wheels), intensive incorporation of computing tools (integrated and predictive modeling at all levels feedstock-process-product), large dynamic incorporation of new catalysts, chemistry driven , fast incorporation of emerging knowledge and last, but most important, environmental preservation and safe operation. 

Some recent applications have benefited from advances in computing and computational techniques. Steady-state simulation is being used off-line for process analysis, design, and retrofit process simulators can model flow sheets with up to about a million equations by employing nested procedures. Other applications have resulted in great economic benefits these include on-line real-time optimization models for data reconciliation and parameter estimation followed by optimal adjustment of operating conditions. Models of up to 500,000 variables have been used on a refinery-wide basis. 

The corporate operations planning model sets target levels and prices for interrefinery transfers, crude and product allocations to each refinery, production targets, and inventory targets for the end of each refinery model s time horizon. 

In plant operations planning each refinery model produces target operating conditions, stream allocations, and blends across the whole refinery, which determines (a) optimal operating conditions, flows, blend recipes, and inventories and (b) costs, cost limits, and marginal values to the scheduling and real-time optimization (RTO) models. 

The scheduling models for each refinery convert the preceding information into detailed unit-level directives that provide day-by-day operating conditions or set points. 

In the real world, it is possible that these early stations could be supplied using excess hydrogen from industrial or refinery sources, rather than dedicated hydrogen production facilities, but this option is not included in the model. 

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