Iterative Real-Time Optimization Scheme for Optimal Operation of Chemical Processes under Uncertainty: Proof of Concept in a Miniplant

Optimization of the Countercurrent Continuous Reforming Process Based on Equation-Oriented Modeling and the SQP Algorithm

Catalytic reforming is a key technology in the petroleum refining and petrochemical industry. In recent years, countercurrent continuous reforming has put forward and practiced the new concept of matching the activity of the catalyst with the difficulty of the reaction. Based on the equation-oriented method, the steady-state model for the reactor-regenerator section of countercurrent continuous reforming was established, including the reactor module, the regenerator module, the compressor model, the heat exchanger model, the heating furnace model, and the oil property model. The inlet and outlet of each module are connected according to the actual technological process, and the model conforms to the requirement of real-time optimization (RTO). The sequential quadratic programming (SQP) algorithm is used for calculation in this study. The model is calibrated to make the calculated value more consistent with the actual value. The model simulation showed the trend of the reforming reaction and the difference between countercurrent reforming and cocurrent reforming. Finally, the process model was optimized for different goals such as the yield of aromatics, the yield of high-octane gasoline, and the yield of C₇ ⁺ aromatics. These results indicate that the established model can simulate the actual industrial process, which can meet the requirements of RTO, and obtain considerable profits for different optimization objectives.

Integrated Process Re-Design with Operation in the Digital Era: Illustration through an Industrial Case Study

This work discusses what should be the desirable path and correct tools for the optimal re-design and operation of processes in the Industry 4.0 framework, as illustrated in a challenging case study corresponding to a complex network of evaporation plants in a viscose-fiber factory. The goal is to integrate optimal design, to improve the existing cooling systems, together with the optimal operation of the whole network, balancing the initial investment with the potentially achievable savings. A rigorous mathematical model for such optimization purpose has been built. The model explicitly considers different structural alternatives as a superstructure for the incorporation of new equipment into the network. The uncertainty associated to future operating conditions is also considered by using a two-stage stochastic formulation. Furthermore, the model is also the base from which a deterministic real-time optimization (RTO) builds upon to support the daily management of the future network operation. The RTO tool suggests the allocation of different products to evaporation plants, the distribution of the cooling water and the suitable number of heat pumps to switch on for optimal economic operation. Design and operation problems are formulated and solved via mixed-integer non-linear programming and the results have been tested with historical plant data.