A generalized disjunctive programming model for multi-stage compression for natural gas liquefaction processes
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 m...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2023-01-01
|
| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/106/e3sconf_icegc2023_00072.pdf |
| _version_ | 1797344956133670912 |
|---|---|
| author | Matovu Fahad Mahadzir Shuhaimi Rozali Nor Erniza Mohammad |
| author_facet | Matovu Fahad Mahadzir Shuhaimi Rozali Nor Erniza Mohammad |
| author_sort | Matovu Fahad |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-08T11:10:27Z |
| format | Article |
| id | doaj.art-67fa65508ece461c9c1047e67483a028 |
| institution | Directory Open Access Journal |
| issn | 2267-1242 |
| language | English |
| last_indexed | 2024-03-08T11:10:27Z |
| publishDate | 2023-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj.art-67fa65508ece461c9c1047e67483a0282024-01-26T10:45:10ZengEDP SciencesE3S Web of Conferences2267-12422023-01-014690007210.1051/e3sconf/202346900072e3sconf_icegc2023_00072A generalized disjunctive programming model for multi-stage compression for natural gas liquefaction processesMatovu Fahad0Mahadzir Shuhaimi1Rozali Nor Erniza Mohammad2Chemical Engineering Department, Universiti Teknologi PetronasChemical Engineering Department, Universiti Teknologi PetronasChemical Engineering Department, Universiti Teknologi PetronasThe 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.https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/106/e3sconf_icegc2023_00072.pdf |
| spellingShingle | Matovu Fahad Mahadzir Shuhaimi Rozali Nor Erniza Mohammad A generalized disjunctive programming model for multi-stage compression for natural gas liquefaction processes E3S Web of Conferences |
| title | A generalized disjunctive programming model for multi-stage compression for natural gas liquefaction processes |
| title_full | A generalized disjunctive programming model for multi-stage compression for natural gas liquefaction processes |
| title_fullStr | A generalized disjunctive programming model for multi-stage compression for natural gas liquefaction processes |
| title_full_unstemmed | A generalized disjunctive programming model for multi-stage compression for natural gas liquefaction processes |
| title_short | A generalized disjunctive programming model for multi-stage compression for natural gas liquefaction processes |
| title_sort | generalized disjunctive programming model for multi stage compression for natural gas liquefaction processes |
| url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/106/e3sconf_icegc2023_00072.pdf |
| work_keys_str_mv | AT matovufahad ageneralizeddisjunctiveprogrammingmodelformultistagecompressionfornaturalgasliquefactionprocesses AT mahadzirshuhaimi ageneralizeddisjunctiveprogrammingmodelformultistagecompressionfornaturalgasliquefactionprocesses AT rozalinorernizamohammad ageneralizeddisjunctiveprogrammingmodelformultistagecompressionfornaturalgasliquefactionprocesses AT matovufahad generalizeddisjunctiveprogrammingmodelformultistagecompressionfornaturalgasliquefactionprocesses AT mahadzirshuhaimi generalizeddisjunctiveprogrammingmodelformultistagecompressionfornaturalgasliquefactionprocesses AT rozalinorernizamohammad generalizeddisjunctiveprogrammingmodelformultistagecompressionfornaturalgasliquefactionprocesses |