Academia.eduAcademia.edu

Figure 3 – uploaded by Mehdi Panahi

See full PDFdownloadDownload figure
Fig. 5- Effect on operation of changes in flowrate of natural gas feed. Fig. 6- Relation between reoptimized oxygen flowrate and natural gas flowrate OU FO The flowrate of natural gas is allowed to change +10%. Fig.5 shows the value of reoptimized objective function when we let to al (solid line), The do optimal nominal poi the six unconstrained DOFs vary ted line shows the value if we keep all DOFs constant at their ints. We see that if the flowra e of natural gas increases by 10%, then the simple policy with constant DOFs gives a 20.6% loss in liquid fuel production, which is not accepta ble. We also considered the op found that the largest variation was in the oxygen we may attempt to let the other DOFs be constant. in Fig. 5 that if we oxygen flowrate, then we have an acceptable loss there are other disturbances, so it is too early to conclude that we can keep all these DOFs constant. imal variation in the six DOFs, and flowrate (Fig. 6). This suggests that ndeed, we see from the dashed line keep all DOFs (u;) at their optimal nominal points, except for the 1.3%) in the worst case. However,

Figure 5 - Effect on operation of changes in flowrate of natural gas feed. Fig. 6- Relation between reoptimized oxygen flowrate and natural gas flowrate OU FO The flowrate of natural gas is allowed to change +10%. Fig.5 shows the value of reoptimized objective function when we let to al (solid line), The do optimal nominal poi the six unconstrained DOFs vary ted line shows the value if we keep all DOFs constant at their ints. We see that if the flowra e of natural gas increases by 10%, then the simple policy with constant DOFs gives a 20.6% loss in liquid fuel production, which is not accepta ble. We also considered the op found that the largest variation was in the oxygen we may attempt to let the other DOFs be constant. in Fig. 5 that if we oxygen flowrate, then we have an acceptable loss there are other disturbances, so it is too early to conclude that we can keep all these DOFs constant. imal variation in the six DOFs, and flowrate (Fig. 6). This suggests that ndeed, we see from the dashed line keep all DOFs (u;) at their optimal nominal points, except for the 1.3%) in the worst case. However,

Related Figures (7)

The effect of reactor volume on liquid fuels production is shown in Fig. 3. From this figure, it can be observed that a volume greater than about 2200 m* does not significantly increase liquid fuel production, so the reactor volume was selected to be 2200 m?. The final process flowsheet is shown in Fig. 4. All units were modelled using the Unisim flowsheet simulator.
The effect of reactor volume on liquid fuels production is shown in Fig. 3. From this figure, it can be observed that a volume greater than about 2200 m* does not significantly increase liquid fuel production, so the reactor volume was selected to be 2200 m?. The final process flowsheet is shown in Fig. 4. All units were modelled using the Unisim flowsheet simulator.
Fig. 4- Process flowsheet for GTL process 3. Optimal operation and Self-optimizing control With a given process design the objective is now to study operation and we use the procedure of Skogestad (2004). One important step is to perform optimization to find optimal conditions of the process for various disturbances. Proceedings of the 2" Annual Gas Processing Symposium F. T. Eljack, G.V. Rex Reklaitis and M.M. El-Hawagi (Editors) © 2010 Elsevier B.V. All rights reserved.
Fig. 4- Process flowsheet for GTL process 3. Optimal operation and Self-optimizing control With a given process design the objective is now to study operation and we use the procedure of Skogestad (2004). One important step is to perform optimization to find optimal conditions of the process for various disturbances. Proceedings of the 2" Annual Gas Processing Symposium F. T. Eljack, G.V. Rex Reklaitis and M.M. El-Hawagi (Editors) © 2010 Elsevier B.V. All rights reserved.
J.4.2. DECONA ALSLUPOANCE. CHANSE th COMPOSILLON Of MYAFOCAFOONS Ii JEEd The same method was applied to the second disturbance, which is an increase in the N; contents in the range from 0.6% to 10%. The results in Fig.7 show that the effect of this disturbance is quite small. In the worst case, the fuel production loss is 3.3%. If we allow for reoptimization of the O, feed rate (Fig. 8) then the loss is almost zero (Fig. 7).
J.4.2. DECONA ALSLUPOANCE. CHANSE th COMPOSILLON Of MYAFOCAFOONS Ii JEEd The same method was applied to the second disturbance, which is an increase in the N; contents in the range from 0.6% to 10%. The results in Fig.7 show that the effect of this disturbance is quite small. In the worst case, the fuel production loss is 3.3%. If we allow for reoptimization of the O, feed rate (Fig. 8) then the loss is almost zero (Fig. 7).
Fig. 9- Effect on operation of change in FT kinetic parameter a
Fig. 9- Effect on operation of change in FT kinetic parameter a
Table 2- Summary of losses for various disturbances Table 3- Effect of CV implementation error on objective function (loss)
Table 2- Summary of losses for various disturbances Table 3- Effect of CV implementation error on objective function (loss)
The results for all four disturbances are summarized in Table 2. It seems that we can always keep all the DOFs constant, except of the O, feedrate. However, in addition to disturbances, we should also examine the effect on the objective function of the implementation errors in the selected controlled variables, for example caused by measurement errors. From Table 3 we see that objective function is sensitive to implementation errors in recycled flue gas to ATR (u;) and H,O feedrate (u,), while its sensitivity to the other CVs (ug, Us, Us) is negligible. Note that the implementation error in the active constraint (u;) has already been considered as a disturbance, while we have already decided that the oxygen feedrate (u2) should not be kept constant.
The results for all four disturbances are summarized in Table 2. It seems that we can always keep all the DOFs constant, except of the O, feedrate. However, in addition to disturbances, we should also examine the effect on the objective function of the implementation errors in the selected controlled variables, for example caused by measurement errors. From Table 3 we see that objective function is sensitive to implementation errors in recycled flue gas to ATR (u;) and H,O feedrate (u,), while its sensitivity to the other CVs (ug, Us, Us) is negligible. Note that the implementation error in the active constraint (u;) has already been considered as a disturbance, while we have already decided that the oxygen feedrate (u2) should not be kept constant.
Related topics:
EngineeringBubble column reactor
580 California St., Suite 400
San Francisco, CA, 94104
© 2025 Academia. All rights reserved