Real time optimization of MIP technology catalytic cracking in Qingdao Petrochemical
Abstract: Real time optimization of self adaptation which is implemented on the fluid catalytic cracking unit of the MIPCGP technology by using the dynamic correlation integration optimizer is introduced in this paper. Such situations as optimization targets, optimized variables and application effects are introduced. The industrial application results of the optimizer on 1.4Mt/a heavy oil catalytic cracking (RFCC) unit showed that: the system operation was stable, related parameters of the reaction regeneration tended to stable and the unit could adapt to change of properties of raw materials automatically; both the yield of liquefied gas and the total liquid yield were increased, in which the yield of liquefied gas was increased by 2.31% and the total liquid yield was increased by 1.07%; the changes of dry gas yield and coke forming ratio were not obvious and the economic benefits were increased by about USD 1/barrel. Therefore very good optimization effects were obtained.
1 IntroductionThere are rather high difficulties in real time optimization of the fluid catalytic cracking unit. The challenge is how to trace the optimum operation point automatically under the situations of variable raw material properties, modification of unit and updating of catalysts, but no manmade interference is needed, such as reconstruction of models, modification of parameters. For an application example introduced in this paper, the dynamic correlation integration technology is adopted so that such a self adaptation optimization control can be realized.
2 Composition of the system
The system is a secondary computer control and it consists of one group of optimization control and an advanced control sub system. The system includes:
2.1 Optimization control schemes
According to the present market situations of oil product selling and variability of the catalytic cracking processing schemes, the whole optimization system can adapt to different processing materials and product different main products. The optimization control system can adapt to five processing schemes:
2.2 Objective function
In the optimization scheme whose main product is liquid hydrocarbon, the yield of liquid hydrocarbon is taken as the objective function (OBJ) In the optimization scheme whose main product is gasoline, the yield of gasoline is taken as the objective function (OBJ) In the optimization scheme whose main product is diesel oil, the yield of diesel oil is taken as the objective function (OBJ) In the optimization scheme whose target is the total liquid yield, the yield of liquid hydrocarbon + gasoline + diesel oil in 12 hours is taken as the objective function (OBJ) In the optimization scheme whose target is the total economic benefits of the unit, the total economic benefits of the unit is taken as the objective function (OBJ) The prices of raw materials and finished products in the above equations can be modified at any moment in the environment of engineer. These four processing schemes can be switched at any moment according to the instruction of the technological control. 2.3 Optimized variables
In selection of optimized variables, those variables which are important for the reactionregeneration technology and are easy to be controlled were mainly considered. In the fluid catalytic cracking unit, the following variables are taken as the online optimized variables:
2.4 Constraint conditions2.4.1 Constraint of the optimized variables
2.4.2 Constraints of product distribution In the optimization system, the constraint conditions on product distribution are added and they are shown in table 4. Table 2.1: Constraints on product distribution in various optimization schemes
The manually set value of Constraint conditions in table 4 can be modified by engineers or the constraint conditions can be removed.
2.5 Optimization methods and optimization softwareThe dynamic correlation integration optimization technology is adopted for optimization control of the unit. The dynamic correlation integration optimization technology has been applied on the dewaxing process and fluid catalytic cracking unit of the refining plant. In addition, the technology experienced change of processing oil products, maintenance and updating of equipments, and it has been subjected to the practice test of long term stable operation. The dynamic correlation integration optimization technology can be applied to most of continuous production processes. Practices showed that this method has the following features: 1) No dynamic or static model of the system should be established in advance. Due to the complexity of the fluid catalytic cracking process, it is very difficult to establish a precise model for online optimization. Moreover, once the components in the unit are replaced or large changes happen on processing raw materials and catalysts, the adopted process model must be adjusted or updated again, while adoption of the dynamic correlation integration method can solve the problem easily. 2) The system runs by using the natural pulse in the production and no manual test signal is needed. No effect or interference will be produced on normal operations of the process during optimization. 3) The system can overcome the dynamic interferences whose characteristics are unknown existing in the optimized variables and objective functions. For example, the fluctuation of the objective function caused by the changes of properties of catalytic cracking processing raw materials will not generate large effects on the optimization process. 4) Strong adaptability. The theory and practices showed that the dynamic correlation integration optimizer had very strong adaptability on the characteristics changes of the optimized system. For example, when the process properties change due to modification of equipments, the system can work well. Practical applications showed such an advantage of the technology sufficiently. The product of Beijing OptimiPro Control Technology Co., Ltd is adopted as the optimization software of the system: Dynamic Correlation Integration Optimizer Express for FCC for Centum CS3000 (FCC dynamic correlation integration optimizer Express Centum CS3000). 2.6 Level of the reprocessing oil tank – optimization coordination advanced control systemIn order to ensure that the level of the fractioning tower bottom changes within the normal range, the level – optimization coordination advanced control is added for these two variables such as reprocessing ratio and addition amount of new catalysts which will affect the level of the reprocessing oil tank directly. The controller harmonizes the level of the fractioning tower bottom and level of the refluxing oil tank according to the rule as well as optimizes these two systems, which will keep the level of the fractioning tower bottom and level of the refluxing oil tank between 30% ~ 70% in so far as possible during the course of optimization control. 2.7 Fault tolerant optimization and emergency systemAn abnormality detecting system of the measuring signals is provided for the optimization control. The system checks the input signals once every minute. If abnormal situations of the signals are found, an alarming signal will be given on the operator interface to alert the operator to perform examination on corresponding instruments. At the same time, the core of optimization control will reconstruct the optimization control according to the detection results of the abnormal detecting system. The system will suspend the optimization on those variables which are affected by the abnormal measuring signals and keep the status before abnormality, while continues optimizing those variables which will not be affected by the abnormal measuring signals. When the abnormality or measuring signals detected by the abnormality detecting system disappears, the core of the optimization control recovers the reconstruction automatically so as to restore the normal control pattern. When emergent situations occur on the unit, the operator can start the emergency system. After the red button is pressed and confirmation is made, the emergency system should exclude all variables from the optimization control. At the same time, the system should switch the basic controllers related to the optimization control from remote setting to manual setting. The control right of all circuits should be returned to the operator. When the unit recovers to the normal state, the operator can put variables into optimization according to normal procedures. 2.8 Reaction – regeneration catalyst average activity optimization control systemDuring the course of reaction, aiming at different requirements on product distribution, there are different optimum catalyst average activities. The system adjusts the average activity of system catalysts through controlling addition amount of new catalysts. While addition amount of new catalysts is implemented through a set of IVB type automatic small feeding unit. An independent optimization controller calculates the optimum feeding amount through certain methods and performs the pulse feeding of new catalysts through an automatic small feeding unit which is controlled by DCS. 2.9 IVB type FCC new catalyst automatic feeding systemThe IVB type FCC new catalyst automatic feeding system which obtain the national patent of China (ZL 90 1 07310.5) is a pulse automatic feeder for new catalysts in the fluid catalytic cracking unit which is controlled by DCS. The feeder feeds materials in pulse pattern. Compared to other automatic feeders, the feeder has such features as simple structure, high operation reliability and long life. The optimum feeding of new catalysts can be realized when the feeder is cooperated with the optimization control system, which plays important roles for adjusting and controlling activity of catalysts and reaching the optimum product distribution. 2.10 Control structureThe overall control structure of the system is shown in figure 1 and it is a secondary computer control pattern when seen in logic. Being the client, the optimization controller obtains the needed measurement information from the OPC Server connected to the DCS. The controller calculates the correlation integration between various variables and correlation integration between various variables and the objective function once every minute. The optimizer calculates the setting value once every ten minutes according to these correlation integration values and these setting values are sent to the basic controller for implementation. As such, the online closed ring optimization control is finished. 2.11 Human machine interfaceThe human machine interface consists of the operator interface and the engineer interface. 3 Application effects3.1 Tests on effects of the optimization control system effectsIn order to examine the effects of the optimization control system, one test is organized on the system. During the optimization test, the optimization scheme is the economic benefits of the unit. The variables of the optimization operation are the temperature of the first reactor, reserve of the second reactor, flow quantity of the prelifting steams, feeding temperature, feeding flow quantity of new catalysts. Other variables are kept constant and they will be not optimized. The results are shown in figure 3.1, table 3.1, table 3.2 and table 3.3.
It can be seen from figure 3.1 that the economic benefits of the unit appears the tendency of increase after the optimization control is put into effect. The detail change is shown in table 3.1.
Note: the economic benefit value in the table is the average value of economic benefits in one period before and after optimization.
Table 3.2: Change of the measurement value of the optimized variables before and after optimization
Table 3.3: Change of yield of various kinds of products after optimization is put into effect
Note: the detail yield values in the table are the average value of accumulated yield of various products in one period before and after optimization.
It can be seen from the above test results that: after the optimization control is put into effect, the temperature of the first reactor is improved, the reserve of the second reactor is increased, the flow quantity of prelifting steams is reduced and the feeding temperature is decreased. Change of these variables can increase the reaction depth while decrease of the addition amount of catalysts can decrease the costs. Change of the total economic benefits is improved a little. Considering that the economic benefit optimization scheme embodies the comprehensive performances of the unit and the scheme has more practical application value when compared to other optimization schemes, therefore the economic benefit optimization scheme is mainly put into effect in the unit. Table 3.4: Statistics on change of yields of various products before and after optimization is put into effect
It can be seen from the above table that the results of long term operation of the optimization system is consistent with the conclusions obtained from the test reports in the early stage of operation. After long term and constant optimization and operation examination, the effects are obvious and economic benefits are increased. After the system is put into effect, the coke forming ratio of the reaction is reduced obviously and the total liquid yield is increased increasingly. Due to decrease of the coke forming ratio in the reaction, the control on temperature of the dilute and dense phases in the regenerator is more stable and rational.
