NLP optimization of a methanol plant by using H2 co-product in fuel cells
نویسندگان
چکیده
Fuel cells, process heat integration and open gas turbine electricity cogeneration can be optimized simultaneously using nonlinear programming (NLP) algorithm. The NLP model contains equations of structural and parametric optimization and is used to optimize complex and energy intensive continuous processes. The procedure does not guarantee the global cost optimum, but it does lead to good, perhaps near-optimum designs. The optimization approach is illustrated by a complex low-pressure Lurgi methanol process, giving an additional profit of 2,65 MUSD/a. The plant, which is producing methanol, has a surplus of hydrogen (H2) flow rate in purge gas. H2 shall be separated from the purge gas by an existing pressure swing adsorption (PSA) column. Pure H2 can be used as fuel in fuel cells.
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