Typical Case of the Intelligent Control System for Gas Separation and MTBE at Zhenhai Refining & Chemical
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Typical Cases
Zhejiang Bangye Technology Co., Ltd. and Zhenhai Refining & Chemical have leveraged multivariable model predictive control technology to design and develop advanced control systems for their gas fractionation and MTBE units. The implementation of these advanced control systems has further enhanced the automation level of the facilities and improved the stability of key process parameters, thereby ensuring consistent product quality, reducing unit energy consumption, and alleviating operator workload, yielding significant economic benefits.
Figure 1 shows the control performance of the sensitive plate temperature at the top of the depropanizer in the gas fractionation unit. By employing multivariable model predictive control and incorporating feedforward control, stable regulation of the sensitive plate temperature is achieved, thereby ensuring compliance with the target product’s separation specifications. A comparison of the control performance before and after implementation reveals a 75.56% reduction in the standard deviation of the sensitive plate temperature.
Figure 2 shows the control performance of propylene purity in the gas‑phase unit. By employing multivariable model predictive control, stable regulation of propylene purity was achieved, while “edge‑of‑limit” operation was used to increase plant throughput. A comparison of performance before and after the implementation of the advanced controller reveals that, following its deployment, the average propylene purity decreased from 99.65% to 99.55% (with a process specification of 99.5%), the standard deviation dropped by 89.71%, and the statistically determined propylene yield improved by 2.79%.
Figure 3 shows the control performance of the reactor hot-spot temperature in the MTBE unit. Hot-spot temperature control is a critical parameter for reactor operation; maintaining stable hot-spot temperatures ensures optimal process performance while minimizing disturbances to downstream separation units. Comparison of the control performance before and after implementation reveals a 38.24% reduction in the standard deviation of the reactor hot-spot temperature.
Figure 4 shows the control performance of the MTBE azeotropic distillation column’s overhead temperature. The overhead temperature significantly affects the separation efficiency of the components, and its stable regulation ensures the MTBE yield. Since the overhead temperature is strongly influenced by ambient conditions, the advanced MTBE control system employs multivariable model predictive control with feedforward variables, effectively mitigating disturbances caused by ambient temperature and stabilizing the overhead temperature. Comparison of the control performance before and after implementation reveals a 44.45% reduction in the standard deviation of the overhead temperature.
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