Application case of intelligent control system for refining industry of atmospheric and vacuum unit in a factory
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Cooperation Case
Typical Case
Figure 1 VOA online predictive control process Zhejiang Bangye Technology Co., Ltd. and Zhenhai Refining Co., Ltd. jointly developed the 1# set of atmospheric and pressure reducing device advanced control system, introduced virtual online analyzers (VOAs) to predict the quality of fractionation tower products, VOAs can Provides a much higher quality estimate than the laboratory analysis and can be connected to the Model Predictive Controller (MPC) for feedback control. VOA can be corrected with a credible laboratory test to eliminate the effects of model bias and unmeasurable disturbances. Figure 1 shows the flow structure of VOA's online predictive control.
Fig. 2 Prediction of dry point quality of atmospheric and vacuum distillation unit Zhenhai refining and chemical decompression first control system design Product quality soft instrument includes constant top dry point, constant first line dry point, constant three line 95 points, minus one line 95 points. The controller automatically controls in advance according to the predicted changes of the soft instruments of each product during the oil change, and automatically switches the crude oil under the premise of ensuring product quality. The application of this technology plays an important role in achieving accurate quality control, smooth operation of the device, and reduced labor intensity. The following is a comparison of the normal top dry point test sample value with the dry point predicted value before online VOA correction.
It can be found that the predicted value before the VOA correction is basically the same as the actual test sample, and there is a big change to the dry point, such as oil switching, which can be predicted in time. This is the condition for MPC to realize online control of product quality.
Fig. 3 The control effect of the constant top decompression point indicator switching control and the advanced control system. After adjusting the dry point index according to actual demand (normal top quality is adjusted from 170 °C to 182 °C), the dry mass controller will automatically adjust the operating variable according to the change of the dry point control range, and the controller operating variable can be found gradually. Adjustment, the dry point quality prediction will return to the adjusted setting range. It is found through the test sample that the actual dry point quality also returns to the set range, indicating that the controller can automatically adjust the dry point index.
Figure 4 shows the control effect of the advanced control system on the VOA of the constant top dry point during crude oil switching. The advanced control system changes the predicted value of the constant top dry point through the signal feedback of the disturbance variable (oil switching). When the oil product changes relatively, the predicted value of the normal top dry point will exceed the control range. The device responds quickly and automatically adjusts the operating variables. It can be found that the predicted VOA of the dry point returns to the control range faster, indicating that the quality of the constant top product is basically maintained within the control range during the crude oil switching process, achieving automatic switching.
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