Delta-base vectors

Refiners can typically obtain the base yield of the FCC unit by averaging the measured yields over some period of time. The DELTA vectors often come from estimations, refiner s internal correlations or published correlations [7, 58,59]. Previous work by Id et al. [60] uses correlations from Gary et al. [7] to generate FCC DELTA-BASE vectors. These vectors are then combined with a blending and crude distillation unit model. This process results in two significant problems. 

Figure 4.36 Process to generate DELTA-BASE vectors.

It is important to note that the process in Figure 4.33 essentially generates an approximation to the Jacobian of the non-linear FCr unit model. If we consider the vector y represents the model outputs, then the vector represents the base case in our planning scenario and the Ax vector represents the change in model inputs from the base case. We then have a matrix of Ay/Ax which represents the change from the base condition as a function of the selected feed attributes (or possibly process conditions). Eq. (4.15) illustrates the connection between the Jacobian and DELTA-BASE vectors... 

Table 4.18 Existing DELTA-BASE vectors for FCC unit (normalized to a feed rate of 1.0).

Workshop 4.1 Cu/de for Modeling FCC Units in Aspen HYSYS Petroleum Refining 195 Table 4.19 DELTA-BASE vectors generated using rigorous modei. 

Table 4.19 shows the DELTA-BASE vectors we generated using the procedure in Figure 4.36. The new BASE vector accurately reflects the current base gasoline and LPG yields of the FCC unit In addihon, as a consistency check, we note that SUL coefficient for the sour gas (row 1) has a negative coefficient This indicates that the sour gas increases as the sulfur in the feed increases. A similar consistency test with CON coefficient and coke (row 5) shows the same result We can use the LP model optimally, knowing that LP model does not underestimate key product yields. 

The advantage of this method is that LP now reflects the actual capabihties of the unit and not the perceived capabilities based historical data or correlations. In addition, if the rigorous simulation is updated alongside with plant retrofits, we can modify the LP model quickly to track these retrofits. The workflow we describe in Figure 4.36 is easy to integrate into existing process simulation and LP software. Aspen HYSYS Petroleum Refining includes tools to automate the workflow and export the updated DELTA-BASE vectors to Aspen PIMS (LP software) directly. This automahon allows quick updates of the LP model to accurately reflect unit performance. 

Workshop 4.5 Model Application to Production Planning - Generate DELTA-BASE Vectors for Linear-Programming (LP)-Based Production Planning... 

An important application of the calibrated model is the generation of LP DELTA-BASE vectors for refinery planning. The DELTA-BASE vectors essentially represent a linearized model of FCC unit as a function of a several key variables. We have extensively discussed linear models in a previous chapter. In this workshop, we wiU demonstrate how to generate LP DELTA-BASE vectors for the calibrated FCC for use with a specific planning software, Aspen PIMS. 

Once we select the Utilties menu entry, Aspen HYSYS shows a list of available utilities. There are many types of utilities available to modify different aspects of the model. To generate DELTA-BASE vectors, we must choose the appropriate utility. In recent versions of Aspen HYSYS, this utility is called the Common Model Utility as shown in Figure 4.108. Figure 4.109 shows Delta Base Utility used in older versions. Both versions are equivalent for the purposes of this workshop. We select either utility and click Add Utility. 

Figure 4.118 PIMS style output for delta-base vectors.

If necessary, we can also rename all the variables to be consistent with PIMS DELTA-BASE vectors. To rename variables, we enter new names for each entry in the corresponding Tag box as show in Figure 4.119. When we re-export the delta-base table, all variables will be replaced with the new tags as shown in Figure 4.120. 

A refinery LP and linear unit model represents a set of linear correlations that predict yield given an average yield value and changes in the certain operating variables. In this section, we discuss how to apply the rigorous reforming model in the context of a hnear unit model. The key information for a linear model of a nonlinear process is the DELTA-BASE vector ... 

We use the yield information from the rigorous model in Table 5.21 to construct the LP yield vectors. The BASE vector is the average of the yields in each RON case. We choose the average value of N-i-2A of 64 to compute the Ax . We then use one of the N-I-2A data points to compute the DELTA-BASE vector. We show the steps and results of this calculation for RON 102 case in Table 5.22. We compare the results of the linear yield vector predictions and model predictions for an intermediate N-I-2A value of 66.6 in Table 5.23. Table 5.24 shows the DELTA-BASE calculated for all the RON cases. 

Table 5.22 Calculating the DELTA-BASE vectors for the C5-t RON = i 102 case. ...

Table 5.24 DELTA-BASE vectors for different RON cases. ...

Model Application - Delta-Base Vector Generation I 429... 

Model Application-Delta-Base Vector Ceneration I 431... 

Figure 6.76 Multi-scenario delta-base vectors in a catalytic reforming process.

To generate delta-base vector, refiners produce case studies by running process model under varied feed and operating conditions by the following procedures ... 

Apply Equation (6.29) to run linear regression to obtain delta-base vector ... 

Figure 6.77 Delta-base vector of HP HCR process generated in this work.

We apply the integrated HP HCR process model to generate delta-base vector for LP-based production planning. 

Workshop V in Chapter 4 - Generate DELTA-BASE vectors for LP using ECC model... 

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