Simultaneous selection and optimization of reaction pathways and downstream separation network

Synthesis of separation networks has been researched for many years because of their potential in improving profit and reducing carbon emissions. However, most of the presented work concentrated on identifying novel solutions for the downstream section such as improving thermal efficiency by using complex heat exchanger networks, applying advanced separation techniques, and optimizing the design/operating parameters, etc., without considering the effect of upstream reaction pathways. This work aims to develop a mixed integer non-linear programming (MINLP) optimization model, which integrates reaction pathway selection and downstream separation optimization. To ensure both process profit and sustainability, the objective is to maximize the process profit per carbon emission. Decision variables such as binary variables, which represent the selection of reaction pathway and separation task, and continuous variables, which influence the separation mass/energy balance, are considered. By giving parameters like reaction conversion rate, component relative volatility, component enthalpy, raw material/product price, etc., this optimization model can simultaneously identify the optimal reaction pathways and their separation network. The optimization model was applied to isobutylene and methanol utilization case studies. The results indicate that the model could identify the best product and the associated best performing process.