Ethylene glycol (EG) serves as a primary raw material in the polyester industry, with syngas-to-dimethyl oxalate (DMO) conversion representing an advanced EG production method. However, this process encounters conflicting objectives between maximization of economic benefits and minimization of carbon emissions, particularly exacerbated by constraints and market prices. To address this challenge, we developed a multi-objective optimization framework for various working conditions: First, we establish a steady-state simulation system incorporating reaction kinetics and mechanisms to model the DMO synthesis process. Then, an innovative economy-carbon emission multi-objective optimization problem is formulated, where the ranges of pivotal operating parameters are determined by sensitivity analysis, and the response surface method is used to obtain the reference points under different conditions. Finally, the optimization problem is solved by the Pareto frontier (PF) estimation algorithm to solve the irregular PF problem, which arises from the complex nonlinear interactions between process variables under various working and price conditions. Under regular working conditions, we compare the knee point among the obtained Pareto solution set with the reference point, and the framework reduces carbon emissions by 19.63% (129.5 kmol/h) while increasing economic benefits by 1.38% (1253.1 yuan/h). Considering three typical conditions of sharp increase of DMC prices, limited production capacity and short-term negative profits, our framework identifies solutions that dominate the reference points and the original turning points in the obtained PF. The results have verified that this study is able to support the decision-making in providing solutions with a good balance between economy and carbon emissions under various working and price conditions.
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