Value Chain Optimization of a Xylitol Biorefinery with Delaunay Triangulation Regression Models

Nikolaus I. Vollmer*, Krist V. Gernaey, Gürkan Sin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

The presented work focuses on the value chain optimization of a conceptually designed biorefinery, considering the plant capacity and other logistic and design constraints. An existing framework is used to create surrogate models, which are then used to reformulate the underlying optimization problem for performing value chain optimization. The used Delaunay triangulation regression surrogate model performs well and is a suitable candidate for value chain optimization. The results indicate an apparent effect of the economics of scale, and the market conditions mainly constrain the designed value chain.
Original languageEnglish
Title of host publicationProceedings of the 14th International Symposium on Process Systems Engineering
EditorsYoshiyuki Yamashita, Manabu Kano
Place of PublicationAmsterdam
PublisherElsevier
Publication date2022
Pages73-78
ISBN (Electronic)978-0-443-18726-1, 978-0-323-85159-6
DOIs
Publication statusPublished - 2022
Event14th International Symposium on Process Systems Engineering (PSE 2021+) - Kyoto, Japan
Duration: 19 Jun 202223 Jun 2022

Conference

Conference14th International Symposium on Process Systems Engineering (PSE 2021+)
Country/TerritoryJapan
CityKyoto
Period19/06/202223/06/2022
SeriesComputer Aided Chemical Engineering
Volume49
ISSN1570-7946

Keywords

  • biorefinery
  • Surrogate Modelling
  • Delaunay Triangulation
  • Mixed-Integer Linear Program
  • Value Chain Optimization

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