eprintid: 17945
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/79/45
datestamp: 2024-06-04 14:10:01
lastmod: 2024-06-04 14:10:01
status_changed: 2024-06-04 14:00:55
type: conference_item
metadata_visibility: show
creators_name: Matovu, F.
creators_name: Mahadzir, S.
creators_name: Rozali, N.E.M.
title: A generalized disjunctive programming model for multistage compression for natural gas liquefaction processes
ispublished: pub
note: cited By 0; Conference of 2nd International Conference on Energy and Green Computing, ICEGC 2023 ; Conference Date: 23 November 2023 Through 24 November 2023; Conference Code:196180
abstract: The primary driver of operating costs in natural gas processes is the energy consumption of the compression system. Multistage compression configurations are commonly employed and hence play a vital role in optimization of natural gas processes. In this study, a generalized disjunctive programming model for multistage compression is formulated. The model is useful for both synthesis and optimization of multistage compression configurations. By using this approach, we further seek improvements in shaft work savings. The model relies on thermodynamic equations and is designed to minimize the consumption of shaft work. The model is handled by employing the logic-based branch and bound algorithm, eliminating the need for explicit conversion into a MINLP, which in turn leads to improved convergence and faster computational performance. The model solution yields optimal pressure levels, and hence stage shaft work consumptions. A case study of multistage compression for a prior optimized single mixed refrigerant (SMR) process obtained from literature is used to test the proposed model. The model�s outcomes are validated through simulation using the Aspen Hysys software. Savings in shaft work of atmost 0.0088, 0.4433, and 1.2321 are obtained for the two, three, and four stage compression systems respectively against the optimized base cases from literature. © The Authors, published by EDP Sciences.
date: 2023
publisher: EDP Sciences
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182947483&doi=10.1051%2fe3sconf%2f202346900072&partnerID=40&md5=a39c6af8f1697228064d4785a33ed625
id_number: 10.1051/e3sconf/202346900072
full_text_status: none
publication: E3S Web of Conferences
volume: 469
refereed: TRUE
issn: 25550403
citation:   Matovu, F. and Mahadzir, S. and Rozali, N.E.M.  (2023) A generalized disjunctive programming model for multistage compression for natural gas liquefaction processes.  In: UNSPECIFIED.