NLP optimization of a methanol plant by using H2co-product in fuel cells

摘要

Fuel cells, process heat integration and open gas turbine electricity cogenerationcan be optimized simultaneously using nonlinear programming (NLP)algorithm. The NLP model contains equations of structural and parametricoptimization and is used to optimize complex and energy intensive continuousprocesses. The procedure does not guarantee the global cost optimum, but itdoes lead to good, perhaps near-optimum designs. The optimization approach isillustrated by a complex low-pressure Lurgi methanol process, giving anadditional profit of 2,65 MUSD/a. The plant, which is producing methanol, hasa surplus of hydrogen (H2) flow rate in purge gas. H2 shall be separated from thepurge gas by an existing pressure swing adsorption (PSA) column. Pure H2 canbe used as fuel in fuel cells.