Multi-criteria optimization in a methanol process

Opportunities for additional profit in retrofits depend very much on the existing plant structure, its parameters and energy system. Combined production of heat flow rate, power and chemical products can improve process efficiency. This paper presents an application of the nonlinear programming (NLP) optimization techniques, including increased chemical product output, heat integration and electricity cogeneration by changing amount flow ratios of raw material, and modifying the separation and reaction systems. The existing NLP model has been extended with basic chemical kinetics, including the effects of changing raw material flow rate ratios on product yield. A case studied methanol plant was optimized using the NLP model developed earlier by including an additional flow rate of hydrogen (H2), decreasing flowrate of high-pressure steam in crude methanol recycling, and increasing methanol production by 2.5%. The potential additional profit from the cogeneration and additional methanol production was estimated to be 2.51 MEUR/a