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Implementing hydrogen injection in coal-dominated regions: Supply chain optimisation and reliability analysis

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  • Wang, Bohong
  • Klemeš, Jiří Jaromír
  • Liang, Yongtu
  • Yuan, Meng
  • Zhang, Haoran
  • Liu, Jiayi

Abstract

In coal-dominated regions, hydrogen by-product from refineries can be used to replace coal as heating fuel. This can be a viable method for reducing CO2 emissions. Given that hydrogen injection into existing natural gas pipeline networks is an economical way to utilise this clean gas, this paper explores its benefits by studying its supply chain optimisation and analysing its reliability. First, a mixed-integer linear programming model is developed to minimise transport and dissatisfaction costs. Material balance, supply and transport of natural gas, operation of pipeline networks, and hydrogen injection are considered as constraints. The operating plans of a regional natural gas supply chain (NGSC), with and without hydrogen injection, are optimised. Then, three types of indicators – economic indices, coal and hydrogen as percentages of total energy consumption, and CO2 emissions – are applied to compare the performance of the NGSC in different situations. A case verifies the proposed model and shows the influence of utilising hydrogen in an NGSC. The optimal operating plans under one standard and two non-standard conditions are calculated, and the reliability of the supply chain is analysed. Results illustrate that injecting hydrogen in the NGSC is beneficial in reducing CO2 emissions and operating costs.

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  • Wang, Bohong & Klemeš, Jiří Jaromír & Liang, Yongtu & Yuan, Meng & Zhang, Haoran & Liu, Jiayi, 2020. "Implementing hydrogen injection in coal-dominated regions: Supply chain optimisation and reliability analysis," Energy, Elsevier, vol. 201(C).
    • Handle: RePEc:eee:energy:v:201:y:2020:i:c:s0360544220306721
    DOI: 10.1016/j.energy.2020.117565
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    as
    1. Zarei, Javad & Amin-Naseri, Mohammad Reza, 2019. "An integrated optimization model for natural gas supply chain," Energy, Elsevier, vol. 185(C), pages 1114-1130.
    2. Foo, Dominic C.Y. & Tan, Raymond R. & Lam, Hon Loong & Abdul Aziz, Mustafa Kamal & Klemeš, Jiří Jaromír, 2013. "Robust models for the synthesis of flexible palm oil-based regional bioenergy supply chain," Energy, Elsevier, vol. 55(C), pages 68-73.
    3. 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.
    4. Mokarizadeh Haghighi Shirazi, M. & Mowla, D., 2010. "Energy optimization for liquefaction process of natural gas in peak shaving plant," Energy, Elsevier, vol. 35(7), pages 2878-2885.
    5. Pavlović, Darko & Banovac, Eraldo & Vištica, Nikola, 2018. "Defining a composite index for measuring natural gas supply security - The Croatian gas market case," Energy Policy, Elsevier, vol. 114(C), pages 30-38.
    6. Balcombe, Paul & Speirs, Jamie & Johnson, Erin & Martin, Jeanne & Brandon, Nigel & Hawkes, Adam, 2018. "The carbon credentials of hydrogen gas networks and supply chains," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 1077-1088.
    7. Sayed, Ahmed R. & Wang, Cheng & Bi, Tianshu, 2019. "Resilient operational strategies for power systems considering the interactions with natural gas systems," Applied Energy, Elsevier, vol. 241(C), pages 548-566.
    8. Liang, Yingzong & Hui, Chi Wai, 2018. "Convexification for natural gas transmission networks optimization," Energy, Elsevier, vol. 158(C), pages 1001-1016.
    9. 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.
    10. Madžarević, Aleksandar & Ivezić, Dejan & Živković, Marija & Tanasijević, Miloš & Ivić, Milica, 2018. "Assessment of vulnerability of natural gas supply in Serbia: State and perspective," Energy Policy, Elsevier, vol. 121(C), pages 415-425.
    11. Li, Jianglong & Xie, Chunping & Long, Houyin, 2019. "The roles of inter-fuel substitution and inter-market contagion in driving energy prices: Evidences from China’s coal market," Energy Economics, Elsevier, vol. 84(C).
    12. Zhang, Haoran & Liang, Yongtu & Liao, Qi & Yan, Xiaohan & Shen, Yun & Zhao, Yabin, 2017. "A three-stage stochastic programming method for LNG supply system infrastructure development and inventory routing in demanding countries," Energy, Elsevier, vol. 133(C), pages 424-442.
    13. Ren, Jingzheng & An, Da & Liang, Hanwei & Dong, Liang & Gao, Zhiqiu & Geng, Yong & Zhu, Qinghua & Song, Shaoxian & Zhao, Wenhui, 2016. "Life cycle energy and CO2 emission optimization for biofuel supply chain planning under uncertainties," Energy, Elsevier, vol. 103(C), pages 151-166.
    Full references (including those not matched with items on IDEAS)

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    2. Xu, Yifan & Ji, Mengmeng & Klemeš, Jiří Jaromír & Tao, Hengcong & Zhu, Baikang & Varbanov, Petar Sabev & Yuan, Meng & Wang, Bohong, 2023. "Optimal renewable energy export strategies of islands: Hydrogen or electricity?," Energy, Elsevier, vol. 269(C).
    3. Pierre, Cayet & Catherine, Azzaro-Pantel & Sylvain, Bourjade & Catherine, Muller-Vibes, 2024. "Beyond the “bottom-up” and “top-down” controversy: A methodological inquiry into hybrid modeling methods for hydrogen supply chains," International Journal of Production Economics, Elsevier, vol. 268(C).
    4. Shuxia Yang & Shengjiang Peng & Xianzhang Ling, 2021. "Discussion on the Feasibility of the Integration of Wind Power and Coal Chemical Industries for Hydrogen Production," Sustainability, MDPI, vol. 13(21), pages 1-14, October.
    5. Wang, Guotao & Liao, Qi & Wang, Chang & Liang, Yongtu & Zhang, Haoran, 2022. "Multiperiod optimal planning of biofuel refueling stations: A bi-level game-theoretic approach," Renewable Energy, Elsevier, vol. 200(C), pages 1152-1165.
    6. Seferlis, Panos & Varbanov, Petar Sabev & Papadopoulos, Athanasios I. & Chin, Hon Huin & Klemeš, Jiří Jaromír, 2021. "Sustainable design, integration, and operation for energy high-performance process systems," Energy, Elsevier, vol. 224(C).
    7. Tian, Xiaoge & Chen, Weiming & Hu, Jinglu, 2023. "Game-theoretic modeling of power supply chain coordination under demand variation in China: A case study of Guangdong Province," Energy, Elsevier, vol. 262(PA).

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