IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v282y2023ics0360544223022508.html
   My bibliography  Save this article

Operational optimization of large-scale thermal constrained natural gas pipeline networks: A novel iterative decomposition approach

Author

Listed:
  • Wang, Guotao
  • Zhao, Wei
  • Qiu, Rui
  • Liao, Qi
  • Lin, Zhenjia
  • Wang, Chang
  • Zhang, Haoran

Abstract

Operation optimization is an effective but quite challenging way to reduce the energy consumption of large-scale pipeline networks. The thermal-hydraulic performance of natural gas, combined with the detailed constraints of compressors, creates many nonlinear constraints that make optimization models difficult to solve. Previous studies aimed at optimizing large-scale natural gas pipeline networks have often simplified multiple compressors into a single compressor station and ignored the operating envelopes of centrifugal compressors. This oversimplification can lead to solutions that deviate from reality. To address this issue, this paper presents an optimization model that is more practical to real-world scenarios. The model incorporates thermal-hydraulic constraints, reverse processes, and detailed constraints of compressors, including the operating envelopes of centrifugal compressors. To solve the Mixed Integer Nonlinear Programming (MINLP) model, an iterative four-stage decomposition algorithm is proposed. The proposed model and algorithm are verified by three large-scale natural gas pipeline networks, demonstrating advantages in solving time and scalability. Specifically, the solving time only requires 9.9 s for a pipeline network containing 406 nodes, even when considering the operating envelopes of centrifugal compressors. These characteristics of the model and algorithm enable them to be portable for similar problems and future research.

Suggested Citation

  • Wang, Guotao & Zhao, Wei & Qiu, Rui & Liao, Qi & Lin, Zhenjia & Wang, Chang & Zhang, Haoran, 2023. "Operational optimization of large-scale thermal constrained natural gas pipeline networks: A novel iterative decomposition approach," Energy, Elsevier, vol. 282(C).
    • Handle: RePEc:eee:energy:v:282:y:2023:i:c:s0360544223022508
    DOI: 10.1016/j.energy.2023.128856
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223022508
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.128856?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wang, Guotao & Liao, Qi & Li, Zhengbing & Zhang, Haoran & Liang, Yongtu & Wei, Xuemei, 2022. "How does soaring natural gas prices impact renewable energy: A case study in China," Energy, Elsevier, vol. 252(C).
    2. Björn Geißler & Antonio Morsi & Lars Schewe & Martin Schmidt, 2018. "Solving Highly Detailed Gas Transport MINLPs: Block Separability and Penalty Alternating Direction Methods," INFORMS Journal on Computing, INFORMS, vol. 30(2), pages 309-323, May.
    3. Yu, Weichao & Huang, Weihe & Wen, Yunhao & Li, Yichen & Liu, Hongfei & Wen, Kai & Gong, Jing & Lu, Yanan, 2021. "An integrated gas supply reliability evaluation method of the large-scale and complex natural gas pipeline network based on demand-side analysis," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    4. Quinteros, Martin & Guignard, Monique & Weintraub, Andres & Llambias, Marc & Tapia, Camilo, 2019. "Optimizing the pipeline planning system at the national oil company," European Journal of Operational Research, Elsevier, vol. 277(2), pages 727-739.
    5. Mengying Xue & Tianhu Deng & Dingzhi Liu, 2016. "CNPC Uses an Iterative Two-Stage Convex Relaxation Approach to Operate Natural Gas Pipelines," Interfaces, INFORMS, vol. 46(6), pages 533-546, December.
    6. D’Ambrosio, Claudia & Lodi, Andrea & Wiese, Sven & Bragalli, Cristiana, 2015. "Mathematical programming techniques in water network optimization," European Journal of Operational Research, Elsevier, vol. 243(3), pages 774-788.
    7. Jingkuan Han & Yingjun Xu & Dingzhi Liu & Yanfang Zhao & Zhongde Zhao & Shuhui Zhou & Tianhu Deng & Mengying Xue & Junchi Ye & Zuo-Jun Max Shen, 2019. "Operations Research Enables Better Planning of Natural Gas Pipelines," Interfaces, INFORMS, vol. 49(1), pages 23-39, January.
    8. Xia Wu & Changjun Li & Yufa He & Wenlong Jia, 2018. "Operation Optimization of Natural Gas Transmission Pipelines Based on Stochastic Optimization Algorithms: A Review," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-18, April.
    9. Pia Domschke & Bjorn Geißler & Oliver Kolb & Jens Lang & Alexander Martin & Antonio Morsi, 2011. "Combination of Nonlinear and Linear Optimization of Transient Gas Networks," INFORMS Journal on Computing, INFORMS, vol. 23(4), pages 605-617, November.
    10. Wen, Kai & Lu, Yangfan & Lu, Meitong & Zhang, Wenwei & Zhu, Ming & Qiao, Dan & Meng, Fanpeng & Zhang, Jing & Gong, Jing & Hong, Bingyuan, 2022. "Multi-period optimal infrastructure planning of natural gas pipeline network system integrating flowrate allocation," Energy, Elsevier, vol. 257(C).
    11. Wei, Xintong & Qiu, Rui & Liang, Yongtu & Liao, Qi & Klemeš, Jiří Jaromír & Xue, Jinjun & Zhang, Haoran, 2022. "Roadmap to carbon emissions neutral industrial parks: Energy, economic and environmental analysis," Energy, Elsevier, vol. 238(PA).
    12. Chen, Qian & Zuo, Lili & Wu, Changchun & Li, Yun & Hua, Kaixun & Mehrtash, Mahdi & Cao, Yankai, 2022. "Optimization of compressor standby schemes for gas transmission pipeline systems based on gas delivery reliability," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    13. Tianhu Deng & Yong Liang & Shixuan Zhang & Jingze Ren & Shuyi Zheng, 2019. "A Dynamic Programming Approach to Power Consumption Minimization in Gunbarrel Natural Gas Networks with Nonidentical Compressor Units," INFORMS Journal on Computing, INFORMS, vol. 31(3), pages 593-611, July.
    14. Vieira, Bruno S. & Mayerle, Sérgio F. & Campos, Lucila M.S. & Coelho, Leandro C., 2020. "Optimizing drinking water distribution system operations," European Journal of Operational Research, Elsevier, vol. 280(3), pages 1035-1050.
    15. Liang, Yingzong & Hui, Chi Wai, 2018. "Convexification for natural gas transmission networks optimization," Energy, Elsevier, vol. 158(C), pages 1001-1016.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhao, Wei & Liao, Qi & Qiu, Rui & Liu, Chunying & Xu, Ning & Yu, Xiao & Liang, Yongtu, 2024. "Pipe sharing: A bilevel optimization model for the optimal capacity allocation of natural gas network," Applied Energy, Elsevier, vol. 359(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mengying Xue & Tianhu Deng & Zuo‐Jun Max Shen, 2019. "Optimizing natural gas pipeline transmission with nonuniform elevation: A new initialization approach," Naval Research Logistics (NRL), John Wiley & Sons, vol. 66(7), pages 547-564, October.
    2. Wen, Kai & Lu, Yangfan & Lu, Meitong & Zhang, Wenwei & Zhu, Ming & Qiao, Dan & Meng, Fanpeng & Zhang, Jing & Gong, Jing & Hong, Bingyuan, 2022. "Multi-period optimal infrastructure planning of natural gas pipeline network system integrating flowrate allocation," Energy, Elsevier, vol. 257(C).
    3. Johannes Thürauf, 2022. "Deciding the feasibility of a booking in the European gas market is coNP-hard," Annals of Operations Research, Springer, vol. 318(1), pages 591-618, November.
    4. Shao, Yu & Zhou, Xinhong & Yu, Tingchao & Zhang, Tuqiao & Chu, Shipeng, 2024. "Pump scheduling optimization in water distribution system based on mixed integer linear programming," European Journal of Operational Research, Elsevier, vol. 313(3), pages 1140-1151.
    5. Yang, Kai & Hou, Lei & Man, Jianfeng & Yu, Qiaoyan & Li, Yu & Zhang, Xinru & Liu, Jiaquan, 2023. "Supply reliability analysis of natural gas pipeline network based on demand-side economic loss risk," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    6. Hong, Bingyuan & Qiao, Dan & Li, Yichen & Sun, Xiaoqing & Yang, Baolong & Li, Li & Gong, Jing & Wen, Kai, 2023. "Supply-demand balance of natural gas pipeline network integrating hydraulic and thermal characteristics, energy conservation and carbon reduction," Energy, Elsevier, vol. 283(C).
    7. Zhang, Zhonglian & Yang, Xiaohui & Li, Moxuan & Deng, Fuwei & Xiao, Riying & Mei, Linghao & Hu, Zecheng, 2023. "Optimal configuration of improved dynamic carbon neutral energy systems based on hybrid energy storage and market incentives," Energy, Elsevier, vol. 284(C).
    8. Lijuan Zhang & Tatyana Ponomarenko, 2023. "Directions for Sustainable Development of China’s Coal Industry in the Post-Epidemic Era," Sustainability, MDPI, vol. 15(8), pages 1-32, April.
    9. Du, Weijian & Li, Mengjie, 2023. "Opening the black box of environmental governance: Environmental target constraints and industrial firm pollution reduction," Energy, Elsevier, vol. 283(C).
    10. Han, Yongming & Cao, Lian & Guo, Qing & Geng, Zhiqiang & Yang, Weiyang & Fan, Jinzhen & Liu, Min, 2024. "Economy and carbon dioxide emissions effects of energy structures in China: Evidence based on a novel AHP-SBMDEA model," Energy, Elsevier, vol. 290(C).
    11. Anastasovski, Aleksandar, 2023. "What is needed for transformation of industrial parks into potential positive energy industrial parks? A review," Energy Policy, Elsevier, vol. 173(C).
    12. Wang, WuChang & Zhang, Yi & Li, YuXing & Hu, Qihui & Liu, Chengsong & Liu, Cuiwei, 2022. "Vulnerability analysis method based on risk assessment for gas transmission capabilities of natural gas pipeline networks," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    13. Du, Yanxiang & Liang, Jin & Yang, Shiliang & Hu, Jianhang & Bao, Guirong & Wang, Hua, 2022. "Numerical investigation of the Ni-based catalytic methanation process in a bubbling fluidized bed reactor," Energy, Elsevier, vol. 257(C).
    14. Anubhav Ratha & Pierre Pinson & Hélène Le Cadre & Ana Virag & Jalal Kazempour, 2022. "Moving from Linear to Conic Markets for Electricity," Working Papers hal-03799767, HAL.
    15. Emenike, Scholastica N. & Falcone, Gioia, 2020. "A review on energy supply chain resilience through optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    16. Chen, Ying & Koch, Thorsten & Zakiyeva, Nazgul & Zhu, Bangzhu, 2020. "Modeling and forecasting the dynamics of the natural gas transmission network in Germany with the demand and supply balance constraint," Applied Energy, Elsevier, vol. 278(C).
    17. Fengyuan Yan & Xiaolong Han & Qianwei Cheng & Yamin Yan & Qi Liao & Yongtu Liang, 2022. "Scenario-Based Comparative Analysis for Coupling Electricity and Hydrogen Storage in Clean Oilfield Energy Supply System," Energies, MDPI, vol. 15(6), pages 1-28, March.
    18. Falk M. Hante & Martin Schmidt, 2019. "Complementarity-based nonlinear programming techniques for optimal mixing in gas networks," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 7(3), pages 299-323, September.
    19. Lin, Zijie & Xie, Linbo & Zhang, Siyuan, 2024. "A compound framework for short-term gas load forecasting combining time-enhanced perception transformer and two-stage feature extraction," Energy, Elsevier, vol. 298(C).
    20. Zalitis, Ivars & Dolgicers, Aleksandrs & Zemite, Laila & Ganter, Sebastian & Kopustinskas, Vytis & Vamanu, Bogdan & Finger, Jörg & Fuggini, Clemente & Bode, Ilmars & Kozadajevs, Jevgenijs & Häring, Iv, 2022. "Mitigation of the impact of disturbances in gas transmission systems," International Journal of Critical Infrastructure Protection, Elsevier, vol. 39(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:282:y:2023:i:c:s0360544223022508. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.