Techno-economic optimisation of gas compressor station location as a decision variable
| dc.contributor.author | Ojo, Oluwatayo Babatope | |
| dc.contributor.author | Igie, Uyioghosa | |
| dc.contributor.author | Pilidis, Pericles | |
| dc.date.accessioned | 2024-10-18T09:10:13Z | |
| dc.date.available | 2024-10-18T09:10:13Z | |
| dc.date.freetoread | 2024-10-18 | |
| dc.date.issued | 2024-06-24 | |
| dc.date.pubOnline | 2024-08-28 | |
| dc.description.abstract | An economical natural gas transportation will require the lowest possible capital and operating expenditures over its lifecycle. To attain these conditions, the designers and investors must estimate the number of compressor stations (CS) that are needed along the pipeline route. More so is the need to determine their optimised locations at various pipeline segments along the pipeline. This study considers the techno-economic optimisation of the compressor station and pipeline segments, making up the proposed Trans-Saharan Gas Pipeline (TSGP) project. The optimised lifecycle cost, CS locations and pipeline segments are evaluated with the main aim of minimising costs. A SIMULINK model is developed using the techno-economic and environmental risk analysis (TERA) framework. The model is incorporated with an optimiser that enables an economic analysis of the TERA framework. Including the optimiser affects the outcome of the TERA in terms of the lifecycle cost. The optimisation problems are formulated considering the compressor station location as the decision variable. The lifecycle cost of the compressor stations and pipeline system is the objective function. A scenarios-based techno-economic optimisation study is performed to mimic the standard compressor station and pipeline system network configurations in the real world. The baseline case consists of 18 compressor stations at fixed locations along the pipeline route. The results show 12 compressor station locations along the pipeline route with a reduction in the lifecycle cost by 12.95% in one of the optimised scenarios compared to the baseline case. The net present value is $28.77 billion assuming a discount rate of 15%. The optimised compressor station locations are at 1, 38, 76, 113, 150, 186, 222, 260, 296, 332, 368, and 408 segments of the pipeline. The outcome of the analyses shows the importance of the two-level optimisation algorithm utilised by the SIMULINK model for the integrated TERA. Hence, this study shows the potential of the TERA modelling and CS location optimisation method utilised in this research in guiding decision-makers on the selection of compressor-turbine configurations. These configurations will give the optimal lifecycle cost at the optimised compressor station locations along the pipeline route. | |
| dc.description.conferencename | ASME Turbo Expo 2024: Turbomachinery Technical Conference and Exposition | |
| dc.description.sponsorship | The authors are grateful to the Petroleum Technology Development Fund of Nigeria (PTDF/ED/PHD/OOB/1386/18), for funding the PhD research that has led to the publication of this paper. | |
| dc.identifier.citation | Ojo OB, Igie U, Pilidis P. (2024) Techno-economic optimisation of gas compressor station location as a decision variable. In: ASME Turbo Expo 2024: Turbomachinery Technical Conference and Exposition, 24-28 June 2024, London, UK. Proceeding Volume 9: Manufacturing Materials and Metallurgy; Microturbines, Turbochargers, and Small Turbomachines; Oil & Gas Applications; Steam Turbine | |
| dc.identifier.elementsID | 553342 | |
| dc.identifier.isbn | 978-0-7918-8801-8 | |
| dc.identifier.uri | https://doi.org/10.1115/gt2024-126805 | |
| dc.identifier.uri | https://dspace.lib.cranfield.ac.uk/handle/1826/23061 | |
| dc.identifier.volumeNo | 9 | |
| dc.language.iso | en | |
| dc.publisher | American Society of Mechanical Engineers | |
| dc.publisher.uri | https://asmedigitalcollection.asme.org/GT/proceedings/GT2024/88018/V009T19A018/1204346 | |
| dc.rights | Attribution 4.0 International | en |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | 46 Information and Computing Sciences | |
| dc.subject | 33 Built Environment and Design | |
| dc.subject | 4602 Artificial Intelligence | |
| dc.title | Techno-economic optimisation of gas compressor station location as a decision variable | |
| dc.type | Conference paper | |
| dcterms.coverage | London, UK | |
| dcterms.dateAccepted | 2024-02-10 | |
| dcterms.temporal.endDate | 28 Jun 2024 | |
| dcterms.temporal.startDate | 24 Jun 2024 |