The economic design of a distillation column or distillation sequences is a challenging problem that has been addressed by superstructure approaches. However, these methods have not been widely used because they lead to mixed-integer nonlinear programs that are hard to solve, and require complex initialization procedures. In this paper, we propose to address this challenging problem by substituting the distillation columns by kriging-based surrogate models generated via state of the art distillation models. We study different columns with increasing difficulty, and show that it is possible to get accurate kriging based surrogate models. The optimization strategy ensures that convergence to a local optimum is guaranteed for numerical noise-free models. For distillation columns (slightly noisy systems), Karush-Kuhn-Tucker optimality conditions cannot be tested directly on the actual model, but still we can guarantee a local minimum in a trust region of the surrogate model that contains the actual local minimum.Topical Heading: Process System Engineering.

10This paper introduces a new disjunctive formulation for the simultaneous optimization and heat integration of 11 systems with variable inlet and outlet temperatures in process streams as well as the possibility of selecting and 12 using different utilities. The starting point is the original compact formulation of the Pinch Location Method, 13 however, instead of approximating the "maximum" operator with smooth, but non-convex functions, these 14 operators are modeled by means of a disjunction. The new formulation has shown to have equal or lower 15 relaxation gap than the best alternative reformulation, thus reducing computational time and numerical problems 16 related to non-convex approximations. 17 18

Highlights  A methodology for the optimization of complex chemical processes is developed.  A hybrid model is solved (simulation units, Kriging models and explicit equations).  Optimization of VCM process is performed to show the performance of our approach.  This approach has proved to be robust and reliable to solve complex problems.  Additionally, heat integration and economic feasibility are studied.

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Please cite this article as: Quirante, Natalia., & Caballeroa, José A., Large scale optimization of a sour water stripping plant using surrogate models.Computers and Chemical Engineering http://dx.doi.org/10. 1016/j.compchemeng.2016.04.039 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.Large scale optimization of a sour water stripping plant using surrogate models We present a case study of the optimization of a sour water stripping plant in which we simultaneously consider economics, heat integration and environmental impact using the ReCiPe indicator, which incorporates the recent advances made in Life Cycle Assessment (LCA).The optimization strategy guarantees the convergence to a local optimum inside the tolerance of the numerical noise.