Simultaneous deterministic global flowsheet optimization and heat integration: Comparison of formulations

Abstract

Heat integration can be considered in flowsheet optimization by including the minimum utility demand from pinch analysis in the objective and constraints. This often results in better process performance than conducting these steps separately. However, it comes with increased computational cost, especially for global optimization. This cost depends both on the problem formulation and on the solver. In this work, we compare several existing and new smooth, nonsmooth, and mixed-integer formulations. Furthermore, we test different choices of optimization variables and constraints reaching from full- to reduced-space formulations. In the reduced-space formulations, heat integration can be included with few, one, or even zero additional variables beyond the pure flowsheet optimization problem. For the considered case studies, this can significantly reduce the solution time of various global solvers, in particular for our open-source solver MAiNGO. Depending on the case study and solver, either nonsmooth or mixed-integer formulations are the fastest to solve.