Online integration of optimal cleaning scheduling and control of heat exchanger networks under fouling
File(s)
Author(s)
Lozano Santamaria, Federico
Macchietto, Sandro
Type
Journal Article
Abstract
Fouling mitigation is paramount to maintaining the reliable and efficient operation of a heat exchanger network (HEN). From the operational perspective, fouling can be mitigated by changing the flow distribution in the network (control actions), or performing periodic cleanings of the units (scheduling actions). Flow control and scheduling have usually been considered independently, ignoring their interaction. This paper presents an online methodology and implementation that integrates control and scheduling decisions for fouling mitigation in HEN, using first principle models of the heat exchangers subject to fouling. A multiloop NMPC/MHE scheme is proposed to estimate the current state of the HEN, and then define the optimal flow distribution and cleaning schedule over a moving horizon. It is shown that this online scheme reacts rapidly to disturbances and copes with model-plant mismatch by updating the model parameters at an appropriate frequency. The methodology is demonstrated on a real industrial case study involving crude oil fouling in the preheat train of a refinery. Application of the methodology shows that (i) significant economic benefits result relative to the actual historical operation, (ii) the online integration achieves a lower operating cost than that of the optimization of control or scheduling individually, (iii) the effect of disturbances is important and the scheme rejects them efficiently, (iv) updating the prediction models deals effectively with plant-model mismatch and process variability, and gives a sufficiently accurate representation of the underlying process, and (v) the computational effort required to solve all optimization problems is low and allows for the practical online implementation of the scheme.
Date Issued
2020-02-12
Date Acceptance
2019-11-06
Citation
Industrial and Engineering Chemistry Research, 2020, 59 (6), pp.2471-2490
ISSN
0888-5885
Publisher
American Chemical Society
Start Page
2471
End Page
2490
Journal / Book Title
Industrial and Engineering Chemistry Research
Volume
59
Issue
6
Copyright Statement
© 2019 American Chemical Society. This document is the Accepted Manuscript version of a Published Work that appeared in final form in Industrial and Engineering Chemistry Research, after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1021/acs.iecr.9b04531
Identifier
https://pubs.acs.org/doi/abs/10.1021/acs.iecr.9b04531
Subjects
Science & Technology
Technology
Engineering, Chemical
Engineering
SOLVING MATHEMATICAL PROGRAMS
MODEL-PREDICTIVE CONTROL
FLOW-RATE DISTRIBUTION
DYNAMIC OPTIMIZATION
OPTIMAL OPERATION
MILP MODEL
IMPLEMENTATION
MITIGATION
03 Chemical Sciences
09 Engineering
Chemical Engineering
Publication Status
Published
Article Number
acs.iecr.9b04531
Date Publish Online
2019-11-21