Optimisation of heat exchanger network cleaning schedules: incorporating uncertainty in fouling and cleaning model parameters
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Authors
Al Ismaili, R
Lee, MW
Wilson, DI
Vassiliadis, VS
Publication Date
2019Journal Title
Computers and Chemical Engineering
ISSN
0098-1354
Publisher
Elsevier BV
Volume
121
Pages
409-421
Type
Article
This Version
AM
Metadata
Show full item recordCitation
Al Ismaili, R., Lee, M., Wilson, D., & Vassiliadis, V. (2019). Optimisation of heat exchanger network cleaning schedules: incorporating uncertainty in fouling and cleaning model parameters. Computers and Chemical Engineering, 121 409-421. https://doi.org/10.1016/j.compchemeng.2018.11.009
Abstract
The optimisation of the cleaning schedule in heat exchanger networks (HENs) subject to fouling is presented in which the impact of parametric uncertainty is considered. This work is based on the realisation that these HEN cleaning scheduling problems are multistage mixed-integer optimal control problems (MIOCPs) in which the controls, i.e. cleaning actions, exhibit bang-bang behaviour as they occur linearly in the system equations. A multiple scenario feasible path MIOCP approach is proposed, whereby many scenarios of the HEN multiperiod problem are stacked, sharing the same control actions. This is implemented on a 10 unit and a 25 unit HEN case studies representing crude oil refinery preheat trains (PHTs). Results show that there is a large difference in financial performance for the deterministic case versus the parametric uncertainty problem and hence it is vital that uncertainty be taken into account during the optimisation of schedules for HEN maintenance problems.
Sponsorship
This research was supported by the Ministry of Higher Education in the Sultanate of Oman and Petroleum Development Oman (PDO).
Funder references
Engineering and Physical Sciences Research Council (EP/D50306X/1)
Identifiers
External DOI: https://doi.org/10.1016/j.compchemeng.2018.11.009
This record's URL: https://www.repository.cam.ac.uk/handle/1810/287000
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Licence URL: http://creativecommons.org/licenses/by-nc-nd/4.0/
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