IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v212y2021ics0951832021001927.html
   My bibliography  Save this article

An integrated gas supply reliability evaluation method of the large-scale and complex natural gas pipeline network based on demand-side analysis

Author

Listed:
  • Yu, Weichao
  • Huang, Weihe
  • Wen, Yunhao
  • Li, Yichen
  • Liu, Hongfei
  • Wen, Kai
  • Gong, Jing
  • Lu, Yanan

Abstract

The fluctuation characteristics of the gas demand and the effect of the user importance are usually ignored in previous gas supply reliability research. With the intent of overcoming these deficiencies, an integrated method based on the demand-side analysis is proposed in this study to assess the gas supply reliability of the large-scale and complex natural gas pipeline network. The method is composed of the establishment of the indicator system, the demand-side analysis, the estimation of the unit failure probability, and the calculation of the gas supply. Among them, the demand-side analysis focuses on the market demand forecasting and user importance research. Moreover, the coupling effect of the user importance, the hydraulic and pressure constraints, and the unit failure on the gas supply calculation is considered. Furthermore, a real natural gas pipeline network located in China is applied to confirm the feasibility of the method. According to the evaluation results of the gas supply reliability, the weakest nodes and key links of the natural gas pipeline network are identified, and the suggestions to improve the gas supply reliability are proposed as well. At last, the significance of the demand side in the gas supply reliability is elaborated and validated.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:reensy:v:212:y:2021:i:c:s0951832021001927
    DOI: 10.1016/j.ress.2021.107651
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832021001927
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2021.107651?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. Yu, Weichao & Wen, Kai & Min, Yuan & He, Lei & Huang, Weihe & Gong, Jing, 2018. "A methodology to quantify the gas supply capacity of natural gas transmission pipeline system using reliability theory," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 128-141.
    2. Yu, Weichao & Gong, Jing & Song, Shangfei & Huang, Weihe & Li, Yichen & Zhang, Jie & Hong, Bingyuan & Zhang, Ye & Wen, Kai & Duan, Xu, 2019. "Gas supply reliability analysis of a natural gas pipeline system considering the effects of underground gas storages," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    3. Yu, Feng & Xu, Xiaozhong, 2014. "A short-term load forecasting model of natural gas based on optimized genetic algorithm and improved BP neural network," Applied Energy, Elsevier, vol. 134(C), pages 102-113.
    4. Flouri, Maria & Karakosta, Charikleia & Kladouchou, Charikleia & Psarras, John, 2015. "How does a natural gas supply interruption affect the EU gas security? A Monte Carlo simulation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 785-796.
    5. Monforti, F. & Szikszai, A., 2010. "A MonteCarlo approach for assessing the adequacy of the European gas transmission system under supply crisis conditions," Energy Policy, Elsevier, vol. 38(5), pages 2486-2498, May.
    6. Praks, Pavel & Kopustinskas, Vytis & Masera, Marcelo, 2015. "Probabilistic modelling of security of supply in gas networks and evaluation of new infrastructure," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 254-264.
    7. Su, Huai & Zhang, Jinjun & Zio, Enrico & Yang, Nan & Li, Xueyi & Zhang, Zongjie, 2018. "An integrated systemic method for supply reliability assessment of natural gas pipeline networks," Applied Energy, Elsevier, vol. 209(C), pages 489-501.
    8. Rodríguez-Gómez, Nuria & Zaccarelli, Nicola & Bolado-Lavín, Ricardo, 2016. "European ability to cope with a gas crisis. Comparison between 2009 and 2014," Energy Policy, Elsevier, vol. 97(C), pages 461-474.
    9. Pambour, Kwabena Addo & Cakir Erdener, Burcin & Bolado-Lavin, Ricardo & Dijkema, Gerard P.J., 2017. "SAInt – A novel quasi-dynamic model for assessing security of supply in coupled gas and electricity transmission networks," Applied Energy, Elsevier, vol. 203(C), pages 829-857.
    10. Yu, Weichao & Song, Shangfei & Li, Yichen & Min, Yuan & Huang, Weihe & Wen, Kai & Gong, Jing, 2018. "Gas supply reliability assessment of natural gas transmission pipeline systems," Energy, Elsevier, vol. 162(C), pages 853-870.
    11. Chen, Qian & Zuo, Lili & Wu, Changchun & Bu, Yaran & Lu, Yifei & Huang, Yanfei & Chen, Feng, 2020. "Short-term supply reliability assessment of a gas pipeline system under demand variations," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    12. Gong, C. & Zhou, W., 2018. "Importance sampling-based system reliability analysis of corroding pipelines considering multiple failure modes," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 199-208.
    13. Chaudry, Modassar & Wu, Jianzhong & Jenkins, Nick, 2013. "A sequential Monte Carlo model of the combined GB gas and electricity network," Energy Policy, Elsevier, vol. 62(C), pages 473-483.
    14. Hribar, Rok & Potočnik, Primož & Šilc, Jurij & Papa, Gregor, 2019. "A comparison of models for forecasting the residential natural gas demand of an urban area," Energy, Elsevier, vol. 167(C), pages 511-522.
    15. Szikszai, A. & Monforti, F., 2011. "GEMFLOW: A time dependent model to assess responses to natural gas supply crises," Energy Policy, Elsevier, vol. 39(9), pages 5129-5136, September.
    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. 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).
    2. 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).
    3. Jiang, Qiangqiang & Cai, Baoping & Zhang, Yanping & Xie, Min & Liu, Cuiwei, 2023. "Resilience assessment methodology of natural gas network system under random leakage," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    4. Zhou, Jun & Zhu, Jiaxing & Liang, Guangchuan & Ma, Junjie & He, Jiayi & Du, Penghua & Ye, Zhanpeng, 2024. "Three-layer and robust planning models to evaluate the strategies of defense layer, attack layer, and operation layer for optimal protection in natural gas pipeline network," Reliability Engineering and System Safety, Elsevier, vol. 249(C).
    5. 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).
    6. Azhdari, Armaghan & Ardakan, Mostafa Abouei & Najafi, Mojtaba, 2023. "An approach for reliability optimization of a multi-state centralized network," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    7. Du, Jian & Zheng, Jianqin & Liang, Yongtu & Wang, Bohong & Klemeš, Jiří Jaromír & Lu, Xinyi & Tu, Renfu & Liao, Qi & Xu, Ning & Xia, Yuheng, 2023. "A knowledge-enhanced graph-based temporal-spatial network for natural gas consumption prediction," Energy, Elsevier, vol. 263(PD).
    8. Fan, Lin & Su, Huai & Wang, Wei & Zio, Enrico & Zhang, Li & Yang, Zhaoming & Peng, Shiliang & Yu, Weichao & Zuo, Lili & Zhang, Jinjun, 2022. "A systematic method for the optimization of gas supply reliability in natural gas pipeline network based on Bayesian networks and deep reinforcement learning," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    9. Zerouali, Bilal & Sahraoui, Yacine & Nahal, Mourad & Chateauneuf, Alaa, 2024. "Reliability-based maintenance optimization of long-distance oil and gas transmission pipeline networks," Reliability Engineering and System Safety, Elsevier, vol. 249(C).
    10. 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).
    11. 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).
    12. Sergey Vorobev & Anton Kolosnitsyn & Ilya Minarchenko, 2022. "Determination of the Most Interconnected Sections of Main Gas Pipelines Using the Maximum Clique Method," Energies, MDPI, vol. 15(2), pages 1-14, January.
    13. Senderov, Sergey M. & Vorobev, Sergey V. & Smirnova, Elena M., 2022. "Peak underground gas storage efficiency in reducing the vulnerability of gas supply to consumers in an extensive gas transmission system," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    14. Aalirezaei, Armin & Kabir, Dr. Golam & Khan, Md Saiful Arif, 2023. "Dynamic predictive analysis of the consequences of gas pipeline failures using a Bayesian network," International Journal of Critical Infrastructure Protection, Elsevier, vol. 43(C).
    15. 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).

    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. Yu, Weichao & Gong, Jing & Song, Shangfei & Huang, Weihe & Li, Yichen & Zhang, Jie & Hong, Bingyuan & Zhang, Ye & Wen, Kai & Duan, Xu, 2019. "Gas supply reliability analysis of a natural gas pipeline system considering the effects of underground gas storages," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    2. Yu, Weichao & Song, Shangfei & Li, Yichen & Min, Yuan & Huang, Weihe & Wen, Kai & Gong, Jing, 2018. "Gas supply reliability assessment of natural gas transmission pipeline systems," Energy, Elsevier, vol. 162(C), pages 853-870.
    3. 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.
    4. Chen, Qian & Zuo, Lili & Wu, Changchun & Cao, Yankai & Bu, Yaran & Chen, Feng & Sadiq, Rehan, 2021. "Supply reliability assessment of a gas pipeline network under stochastic demands," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    5. Zhu, Jianhua & Peng, Yan & Gong, Zhuping & Sun, Yanming & Lai, Chaoan & Wang, Qing & Zhu, Xiaojun & Gan, Zhongxue, 2019. "Dynamic analysis of SNG and PNG supply: The stability and robustness view #," Energy, Elsevier, vol. 185(C), pages 717-729.
    6. Wang, Can & Xie, Haipeng & Bie, Zhaohong & Li, Gengfeng & Yan, Chao, 2021. "Fast supply reliability evaluation of integrated power-gas system based on stochastic capacity network model and importance sampling," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    7. Chen, Qian & Zuo, Lili & Wu, Changchun & Bu, Yaran & Lu, Yifei & Huang, Yanfei & Chen, Feng, 2020. "Short-term supply reliability assessment of a gas pipeline system under demand variations," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    8. Zhaoming Yang & Qi Xiang & Yuxuan He & Shiliang Peng & Michael Havbro Faber & Enrico Zio & Lili Zuo & Huai Su & Jinjun Zhang, 2023. "Resilience of Natural Gas Pipeline System: A Review and Outlook," Energies, MDPI, vol. 16(17), pages 1-19, August.
    9. Cabrales, Sergio & Valencia, Carlos & Ramírez, Carlos & Ramírez, Andrés & Herrera, Juan & Cadena, Angela, 2022. "Stochastic cost-benefit analysis to assess new infrastructure to improve the reliability of the natural gas supply," Energy, Elsevier, vol. 246(C).
    10. 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).
    11. Su, Huai & Zhang, Jinjun & Zio, Enrico & Yang, Nan & Li, Xueyi & Zhang, Zongjie, 2018. "An integrated systemic method for supply reliability assessment of natural gas pipeline networks," Applied Energy, Elsevier, vol. 209(C), pages 489-501.
    12. Zhou, Dengji & Jia, Xingyun & Ma, Shixi & Shao, Tiemin & Huang, Dawen & Hao, Jiarui & Li, Taotao, 2022. "Dynamic simulation of natural gas pipeline network based on interpretable machine learning model," Energy, Elsevier, vol. 253(C).
    13. Corrado lo Storto, 2019. "An SNA-DEA Prioritization Framework to Identify Critical Nodes of Gas Networks: The Case of the US Interstate Gas Infrastructure," Energies, MDPI, vol. 12(23), pages 1-18, December.
    14. Yu, Weichao & Huang, Weihe & Wen, Kai & Zhang, Jie & Liu, Hongfei & Wang, Kun & Gong, Jing & Qu, Chunxu, 2021. "Subset simulation-based reliability analysis of the corroding natural gas pipeline," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    15. Yassine Rqiq & Jesus Beyza & Jose M. Yusta & Ricardo Bolado-Lavin, 2020. "Assessing the Impact of Investments in Cross-Border Pipelines on the Security of Gas Supply in the EU," Energies, MDPI, vol. 13(11), pages 1-23, June.
    16. Zhou, Xingyuan & van Gelder, P.H.A.J.M. & Liang, Yongtu & Zhang, Haoran, 2020. "An integrated methodology for the supply reliability analysis of multi-product pipeline systems under pumps failure," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    17. Yu, Weichao & Wen, Kai & Min, Yuan & He, Lei & Huang, Weihe & Gong, Jing, 2018. "A methodology to quantify the gas supply capacity of natural gas transmission pipeline system using reliability theory," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 128-141.
    18. Balali, Amirhossein & Valipour, Alireza & Edwards, Rodger & Moehler, Robert, 2021. "Ranking effective risks on human resources threats in natural gas supply projects using ANP-COPRAS method: Case study of Shiraz," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    19. 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).
    20. 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).

    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:reensy:v:212:y:2021:i:c:s0951832021001927. 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: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    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.