Refinery configurations

Figure 10.2 shows the locations of reforming and isomerization units in refinery configurations. 

Figure 10.19 shows one of the possible configurations for a refinery of the year 2000. 

Identify potential sources of strong blast present within the area covered by the flammable cloud. Potential sources of strong blast include —extended spatial configuration of objects such as process equipment in chemical plants or refineries and stacks of crates or pallets ... 

The previous comments concerning maintenance of the refinery analyser described in Section 14.2.2, also apply to this analysis configuration, i.e. proper automation and the use of accurate flow and temperature controls are a necessity. 

The overhead stream from the debutanizer or stabilizer is a mix of C, s and C4 s, usually referred to as LPG (liquefied petroleum gas). It is rich in olefins, propylene, and butylene. These light olefins play an important role in the manufacture of reformulated gasoline (RFG). Depending on the refinery s configuration, the cat cracker s LPG is used in the following areas ... 

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. 

FIGURE 12.5 Refinery site facility layout map showing well locations and configuration of the water table. 

Part 1, comprised of one chapter, introduces the reader to the configuration of petroleum refining and the petrochemical industry. It also discusses key classifications of petrochemical industry feedstock from petroleum products. The final part explains and proposes possible synergies between the petroleum refinery and the petrochemical industry. 

Figure 1.2 Schematic diagram of standard refinery configuration.

Constraints (5.13) and (5.14) represent the material balance that governs the operation of the petrochemical system. The variable x 1 represents the annual level of production of process m Mpa where ttcpm is the input-output coefficient matrix of material cp in process m Mpel. The petrochemical network receives its feed from potentially three main sources. These are, (i) refinery intermediate streams of an intermediate product cir RPI, (ii) refinery final products Ff ri of a final product cfr RPF, and (iii) non-refinery streams Fn px of a chemical cp NRF. For a given subset of chemicals cp CP, the proposed model selects the feed types, quantity and network configuration based on the final chemical and petrochemical lower and upper product demand Dpet and DPet for each cp CFP, respectively. In constraint (5.15), defining a binary variable yproc et for each process m Mpet is required for the process selection requirement as yproc et will equal 1 only if process m is selected or zero otherwise. Furthermore, if only process m is selected, its production level must be at least equal to the process minimum economic capacity B m for each m Mpet, where Ku is a valid upper... 

This section presents computational results of the models and the sampling scheme proposed in this chapter. The refinery examples considered represent industrial-scale size refineries and an actual configuration that can be found in many industrial sites around the world. In the presentation of the results, we focus on demonstrating the sample average approximation computational results as we vary the sample sizes and compare their solution accuracy and the CPU time required for solving the models. 

This example illustrates the performance of the proposed approach on a single site total refinery planning problem. The refinery scale, capacity and configuration mimic an existing refinery in the Middle East. Figure 7.1 is a state equipment network (SEN)... 

Most DCS were, and still are, being sold to refineries and chemical plants where the distances involved and the environment do not require microwave communication. Responding to the market demand, few manufacturers were interested in developing the technique. Such systems that were available were, quite naturally, configured around the concept of closed loop control at the PCM level. Consequently, none of them could compete with the SCADA system in terms of numbers of data acquisition points. Alternatively, none of the SCADA system manufacturers could provide a sufficiently intelligent remote unit to execute closed loop control. 

A previous chapter (Chapter 7) has dealt with the processes used in refineries that were developed for conventional feedstocks (Figure 9-1). The current chapter will deal with those processes that are relatively late comers to refinery scenarios. These processes have evolved during the last three decades, and were developed (and installed) to address the refining of the heavy feedstocks. Thus, refining heavy feedstocks has become a major issue in modem refinery practice and several process configurations have evolved to accommodate the heavy feedstocks (RAROP, 1991 Shih and Oballa, 1991 Hydrocarbon Processing, 1998). 

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