Simultaneous retrofit of complex and energy intensive processes-III
A simultaneous structural and parameter optimization model of a total process was used to approach the global optimum solution of the retrofit. Simultaneous nonlinear programming (NLP) optimization can be applied to a complex industrial process giving more economical and profitable operation. The NLP model with variable flow rates of all the streams in different structures has been chosen. The problem has been how to handle the additional effect of nonconvexities, which prevent the problem being converged. The NLP algorithm, which was included as the additional technique using a possibility of minimum variable-error with a lower upper bound in mass and energy balances, was easier to solve. The NLP model of an existing methanal plant has been extended with the process separation section. The additional profit for all the process was 5.262 MUSD/a, while for the process without purification it was 5.173 MUSD/a. (C) 2000 Elsevier Science Ltd. All rights reserved.
retrofit optimization model energy intensive processes global optimization solution simultaneous optimization superstructure nlp formulation