Original scientific paper
https://doi.org/10.15255/CABEQ.2018.1400
A Robust Decomposition Methodology for Synthesis of Flexible Processes with Many Uncertainty Parameters – Application to HEN Synthesis
K. Zirngast
; Faculty of Chemistry and Chemical Engineering, University of Maribor, Maribor, Slovenia
Z. Kravanja
; Faculty of Chemistry and Chemical Engineering, University of Maribor, Maribor, Slovenia
Z. Novak Pintarič
orcid.org/0000-0003-0054-6567
; Faculty of Chemistry and Chemical Engineering, University of Maribor, Maribor, Slovenia
Abstract
This contribution presents a new robust decomposition methodology for generating optimal flexible process flow sheets with a large number of uncertain parameters. During the initial steps, first-stage variables are determined by performing mixed-integer nonlinear
programming (MINLP) synthesis of a flow sheet at the nominal conditions, and then by exposing the obtained flow sheet sequentially over a set of extreme MINLP scenarios of uncertain parameters. As a result, the sizes of the flow-sheet units gradually increase, and/or new units are added until the required feasibility is achieved. After testing the flexibility of the obtained design, a Monte Carlo stochastic optimization of the second-stage variables is performed using a sampling method in order to obtain an optimum value of the expected objective variable. The advantages of the proposed methodology
are the independence of process model sizes from the number of uncertain parameters, the straightforward use of deterministic models for incorporating uncertainty, and relatively simple execution of MINLP synthesis of processes under uncertainty. Thus, it could be used for designing large processes with a large number of uncertain parameters. The methodology is illustrated by synthesis of a flexible Heat Exchanger Network.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Keywords
decomposition methodology; flexibility; uncertainty; synthesis of flow sheets; Heat Exchanger Network
Hrčak ID:
215694
URI
Publication date:
15.1.2019.
Visits: 1.075 *