Process simulator-based optimization of biorefinery downstream processes under the Generalized Disjunctive Programming framework

作者：Corbetta Michele; Grossmann Ignacio E; Manenti Flavio^*

来源：Computers & Chemical Engineering, 2016, 88: 73-85.

DOI：10.1016/j.compchemeng.2016.02.009

• Generalized disjunctive programming
• MINLP
• Downstream
• Process simulator
• Azeotropes
• Derivative free optimization

Downstream processing of biofuels and bio-based chemicals represents a challenging problem for process synthesis and optimization, due to the intrinsic nonideal thermodynamics of the liquid mixtures derived from the (bio) chemical conversion of biomass. In this work, we propose a new interface between the process simulator PRO/II (SimSci, Schneider-Electric) and the optimization environment of GAMS for the structural and parameter optimization of this type of flowsheets with rigorous and detailed models. The optimization problem is formulated within the Generalized Disjunctive Programming (GDP) framework and the solution of the reformulated MINLP problem is approached with a decomposition strategy based on the Outer-Approximation algorithm, where NLP subproblems are solved with the derivative free optimizer belonging to the BzzMath library, and MILP master problems are solved with CPLEX/GAMS. Several validation examples are proposed spanning from the economic optimization of two different distillation columns, the dewatering task of diluted bio-mixtures, up to the distillation sequencing with simultaneous mixed-integer design of each distillation column for a quaternary mixture in the presence of azeotropes.

• 出版日期2016-5-8