A Mixed Integer Linear Programming (MILP) Model for Optimal Operation of Industrial Resource Conservation Networks (RCNs) Under Abnormal Conditions

Raymond R. Tan, Dominic Chwan Yee Foo, Santanu Bandyopadhyay, Kathleen B. Aviso, D. K. S. Ng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Process integration (PI) techniques have been developed to facilitate the design of efficient and sustainable industrial systems. One large class of applications deals with the synthesis of resource conservation networks (RCNs). However, there is a relatively small body of published work on PI methods for optimizing operations. In the case of RCNs, there may be a need to determine optimal operations in response to process abnormalities that result from internal (e.g., process equipment failure) or external (e.g., climatic events such as drought) disruptions. In this work, a mixed integer linear programming (MILP) model is developed to determine optimal operation of RCNs under abnormal conditions resulting from such disturbances. The model formulation is based on conventional MILP models for grassroots RCN synthesis, but is modified to address the problem of temporarily reallocating process streams using an existing pipeline network, without additional capital investment. The model assumes that the plant is forced to operate at an abnormal steady state for the duration of the aforementioned disturbance. A modified literature case study on water reuse/recycle is presented to illustrate the use of the model.

Original languageEnglish
Title of host publication27th European Symposium on Computer Aided Process Engineering
PublisherElsevier
Pages607-612
Number of pages6
ISBN (Print)9780444640802, 9780444639653
DOIs
Publication statusPublished - 2017

Publication series

NameComputer Aided Chemical Engineering
PublisherElsevier
Volume40
ISSN (Print)1570-7946

Keywords

  • mixed integer linear programming
  • Process Integration
  • resource conservation networks

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Computer Science Applications

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    Tan, R. R., Foo, D. C. Y., Bandyopadhyay, S., Aviso, K. B., & Ng, D. K. S. (2017). A Mixed Integer Linear Programming (MILP) Model for Optimal Operation of Industrial Resource Conservation Networks (RCNs) Under Abnormal Conditions. In 27th European Symposium on Computer Aided Process Engineering (pp. 607-612). (Computer Aided Chemical Engineering; Vol. 40). Elsevier. https://doi.org/10.1016/B978-0-444-63965-3.50103-3