A mixed integer linear programming (MILP) model for optimal operation of industrial resource conservation networks (RCNs) under abnormal conditions
College
Gokongwei College of Engineering
Department/Unit
Chemical Engineering
Document Type
Article
Source Title
Computer Aided Chemical Engineering
Volume
40
First Page
607
Last Page
612
Publication Date
10-1-2017
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. © 2017 Elsevier B.V.
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Digitial Object Identifier (DOI)
10.1016/B978-0-444-63965-3.50103-3
Recommended Citation
Tan, R. R., Foo, D., Bandyopadhyay, S., Aviso, K. B., & Ng, D. K. (2017). A mixed integer linear programming (MILP) model for optimal operation of industrial resource conservation networks (RCNs) under abnormal conditions. Computer Aided Chemical Engineering, 40, 607-612. https://doi.org/10.1016/B978-0-444-63965-3.50103-3
Disciplines
Chemical Engineering
Keywords
Industrial districts; Industrial ecology
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