NLP optimization of gas turbine including experimental catalyst conversion data in methanol plant

نویسندگان

  • Anita Kovač Kralj
  • Peter Glavič
چکیده

This paper presents a study on experimentally measured degrees of conversion in successive catalyst bed levels which can be included in simultaneous optimization using nonlinear programming (NLP) algorithm. The NLP model is including equations of structural and parametric optimization of: existing catalyst model, recycled gas stream, reactor, gas turbine, heat exchangers, flash, compressors, splitter and CO2 reuse. The optimization approach is illustrated by a complex low-pressure Lurgi methanol process, giving an additional profit of 3,5 MUSD/a.

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تاریخ انتشار 2007