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Impact of Compressor Station Availability on the Techno-Economics of Natural Gas Pipeline Transportation

Author

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  • Oluwatayo Babatope Ojo

    (Centre for Propulsion and Thermal Power Engineering, Cranfield University, Cranfield, Bedford MK43 0AL, UK)

  • Abdelrahman Hegab

    (Centre for Propulsion and Thermal Power Engineering, Cranfield University, Cranfield, Bedford MK43 0AL, UK)

  • Pericles Pilidis

    (Centre for Propulsion and Thermal Power Engineering, Cranfield University, Cranfield, Bedford MK43 0AL, UK)

Abstract

This study aims to examine the impact of compressor station availability on the techno-economic aspects of natural gas pipeline transportation, using the proposed Trans-Saharan Gas Pipeline (TSGP) project as a case study. A scenario-based technical and economic analysis was conducted to highlight the economic sensitivities of the systems to availability. The economic assessment of the project was performed using a discounted cash flow method, considering lifecycle costs. The techno-economic model was developed using MATLAB R2020b, accounting for variations in ambient temperatures at the compressor station under different flow conditions. Findings indicate an 8.41% increase in project lifecycle cost in one scenario compared to the baseline, assuming a 15% discount rate. However, the baseline case with a 100% compressor station availability assumption appears unrealistic, as shown by its lifecycle cost and net present value estimates. This is because constant operating conditions throughout the project lifecycle are impossible. Additionally, when station availability increases by 7.87% and the cost of standby units rises by 10.24%, avoided income loss due to station unavailability increases by 14.06%. This reveals a trade-off between the extra capital expenditure on standby units and the savings from avoiding income loss. Furthermore, the impact of 2% and 4% escalation rates of fuel and maintenance costs on lifecycle costs results in a rise of 2.70% and 6.15%, respectively, in one scenario compared to the 0% escalation rate. The results demonstrate the significant influence of compressor station availability analysis on pipeline projects, particularly in reducing engine downtime costs and enhancing project revenue. Therefore, the methods presented here help in understanding the importance of compressor station availability in pipeline techno-economics, leading to more effective resource and financial management.

Suggested Citation

  • Oluwatayo Babatope Ojo & Abdelrahman Hegab & Pericles Pilidis, 2025. "Impact of Compressor Station Availability on the Techno-Economics of Natural Gas Pipeline Transportation," Energies, MDPI, vol. 18(16), pages 1-28, August.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:16:p:4243-:d:1721113
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    References listed on IDEAS

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    1. Aretakis, N. & Roumeliotis, I. & Doumouras, G. & Mathioudakis, K., 2012. "Compressor washing economic analysis and optimization for power generation," Applied Energy, Elsevier, vol. 95(C), pages 77-86.
    2. Arya, Adarsh Kumar & Kumar, Adarsh & Pujari, Murali & Pacheco, Diego A.de J., 2023. "Improving natural gas supply chain profitability: A multi-methods optimization study," Energy, Elsevier, vol. 282(C).
    3. Xiong, Zhiyi & Liu, Yuhui & Cai, Yongjun & Chang, Weichun & Wang, Ziqiang & Li, Zhenlin & Peng, Shiyao, 2025. "Research on the effect of green hydrogen blending on natural gas centrifugal compressor performance," Renewable Energy, Elsevier, vol. 242(C).
    4. Zhou, Jun & Qin, Can & Fu, Tiantian & Liu, Shitao & Liang, Guangchuan & Li, Cuicui & Hong, Bingyuan, 2024. "Automatic response framework for large complex natural gas pipeline operation optimization based on data-mechanism hybrid-driven," Energy, Elsevier, vol. 307(C).
    5. repec:cdl:itsdav:qt9m40m75r is not listed on IDEAS
    6. repec:cdl:itsdav:qt2gk0j8kq is not listed on IDEAS
    7. Xuejie Li & Yuan Xue & Yuxing Li & Qingshan Feng, 2022. "An Optimization Method for a Compressor Standby Scheme Based on Reliability Analysis," Energies, MDPI, vol. 15(21), pages 1-16, November.
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