Refinery process variables

The hydrodesulfurization process variables (Chapter 5) usually require some modification to accommodate the various feedstocks that are submitted for this particular aspect of refinery processing. The main point of the text is to outline the hydrodesulfurization process with particular reference to the heavier oils and residua. However, some reference to the lighter feedstocks is warranted. This will serve as a base point to indicate the necessary requirements for heavy oil and residuum hydrodesulfurization (Table 6-6). 

This program concentrated on the requirements and problems that are expected during typical refinery processing. The main concerted efforts, therefore, were to detect and differentiate levels of performance of the synthetic liquids compared with the performances of an appropriate petroleum counterpart stream. Temperature was used as the primary process variable. If catalyst on-stream life and conversion are to be optimized, then an accurate temperature profile performance must be the initial step. Hydro-treating performances were evaluated under simulated refinery conditions while varying the most practical primary process variable, temperature. All experimental work utilized American Cyanamid HDS-3A catalyst. 

Sulfur is naturally present in many crude oils and petroleum fractions, most commonly as organic sulfides and heterocyclic compounds. Residual fuel oils are variable products whose sulfur contents depend not only on their crude oil sources but also on the extent of the refinery processing received by the fuel oil blending components. Sulfur, present in these fuel oils in varying amounts up to 4 or 5% w/w, is an undesirable constituent, and many refining steps aim to reduce the sulfur content to improve stability and reduce environmentally harmful emissions. 

All the information displayed on the computer console can be printed. Usually, one would print out the process flowsheet of a portion of the unit showing temperatures, flows, pressures, and control-valve positions at some point in time. Also, a particular plot or process variable may also be printed. However, one could print every process variable on one-minute intervals that the computer is monitoring in the entire refinery. I have, in my home, 300 lb of computer output representing a four-day operating period for a refinery in Chicago. The ability to accumulate data with a computer, therefore, can be potentially overwhelming. Unfortunately, the ability of engineers to analyze problems can be drowned in this sea of data. 

Isobutane concentration is generally expressed in terms of the isobutane-to-olefin ratio (I/O). This ratio is the most important process variable to control in terms of refinery alkylation productivity, yield, and quality of alkylate, as well as the add... 

The process variables temperature, acid strength, isobutane concentration, and mixing have to be carefully optimized in refinery alkylation to obtain high fuel quality. The optimum parameters differ for the H2SO4- and HF-catalyzed processes. 

This chapter differentiates itself from the reported studies in the literature through the following contributions (1) detailed kinetic model that accounts for coke generation and catalyst deactivation (2) complete implementation of a recontactor and primary product fractionation (3) feed lumping from limited feed information (4) detailed procedure for kinetic model calibration (5) industrially relevant case studies that highlight the effects of changes in key process variables and (6) application of the model to refinery-wide production planning. 

The reactor temperature is a primary method of shifting the reactor yield to produce more valuable product distributions. Toother process variable is the feed rate to the unit. The feed rate cannot take on drastically different values due to the demands of other units in the refinery. However, small changes in feed rate can influence the product distribution. This occurs because of the change in contact time with the catalyst Higher contact times increase of the conversion of feed to products. 

This chapter deals with catalytic hydrotreating (HDT), which is one of the most important processes in petroleum refining industry, not only for upgrading of heavy oils but also for producing low-impurity content fuels and preparing feeds for various conversion processes. Its importance in refineries and current worldwide situation, as well as the main process aspects (description, type of reactors, fundamentals, and process variables) are discussed. 

Supply of MU water for a medium-pressure (450 psig) WT boiler, from a surface water source with very variable suspended solids and hardness (sugar refinery, South Africa). The process used is a. carbonate removal using hot-lime precipitation softening coupled with silica adsorption by magnesia addition b. clarification in anthracite filters and c. cation ion-exchange for the balance of hardness removal. 

The networks that interconnect various process units and vessels to the discharge zones or flares occur widely in refineries and chemical plants. Figure 11 shows a typical configuration in which the root represents the flare, the terminal vertices represent the relief valves, and the edge (each labeled with an arabic numeral) represents a pipe section between two physical junctions (valves, flare, or pipe joints). The configuration of such a network is dictated by the layout of the process unit. In this discussion both the lengths of the pipe sections and the interconnections will be treated as specified variables. 

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 problem is to allocate optimally the crudes between the two processes, subject to the supply and demand constraints, so that profits per week are maximized. The objective function and all constraints are linear, yielding a linear programming problem (LP). To set up the LP you must (1) formulate the objective function and (2) formulate the constraints for the refinery operation. You can see from Figure El6.1 that nine variables are involved, namely, the flow rates of each of the crude oils and the four products. 

The problem is formulated as an MILP model where binary variables are used for designing the process integration network between the refineries and deciding on the production unit expansion alternatives. Linearity in the model was achieved by defining component flows instead of individual flows and associated fractions. The planning problem formulation is as follows. 

The intermediate material balances within and across the refineries can be expressed as shown in constraint (3.2). The coefficient acr,dr,i,P can assume either a positive sign if it is an input to a unit or a negative sign if it is an output from a unit. The multirefinery integration matrix dr y accounts for all possible alternatives of connecting intermediate streams dr CIR of crude cr CR from refinery ie I to process p P in plant i i. Variable xiRef. , represents the... 

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