IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v282y2023ics0360544223016948.html
   My bibliography  Save this article

Mobile energy storage systems with spatial–temporal flexibility for post-disaster recovery of power distribution systems: A bilevel optimization approach

Author

Listed:
  • Shen, Yueqing
  • Qian, Tong
  • Li, Weiwei
  • Zhao, Wei
  • Tang, Wenhu
  • Chen, Xingyu
  • Yu, Zeyuan

Abstract

In recent years, the damage to power distribution systems caused by the frequent occurrence of extreme disasters in the world cannot be ignored. In the face of the customer’s demand for high power supply reliability and high power quality, it is urgent to establish a resilient distribution network that can not only resist extreme disasters and quickly recover the power distribution system loads, but also ensure a high voltage quality of the distribution system during recovery process. Therefore, mobile energy storage systems with adequate spatial–temporal flexibility are added, and work in coordination with resources in an active distribution network and repair teams to establish a bilevel optimization model. The objective of the upper-level optimization model is minimum the total load curtailment of the distribution system after the disaster. And the objective of the lower-level optimization model is minimum the voltage offset of power supply buses during the recovery stage. A modified IEEE 33-bus distribution test system is used to verify this model. The simulation results show that the bilevel optimization strategy proposed in this research can effectively reduce the voltage offset during the recovery process of distribution systems, and ensure the minimum total load curtailment simultaneously.

Suggested Citation

  • Shen, Yueqing & Qian, Tong & Li, Weiwei & Zhao, Wei & Tang, Wenhu & Chen, Xingyu & Yu, Zeyuan, 2023. "Mobile energy storage systems with spatial–temporal flexibility for post-disaster recovery of power distribution systems: A bilevel optimization approach," Energy, Elsevier, vol. 282(C).
  • Handle: RePEc:eee:energy:v:282:y:2023:i:c:s0360544223016948
    DOI: 10.1016/j.energy.2023.128300
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223016948
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2023.128300?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. Pesaran H.A., Mahmoud & Nazari-Heris, Morteza & Mohammadi-Ivatloo, Behnam & Seyedi, Heresh, 2020. "A hybrid genetic particle swarm optimization for distributed generation allocation in power distribution networks," Energy, Elsevier, vol. 209(C).
    2. Zakernezhad, Hamid & Nazar, Mehrdad Setayesh & Shafie-khah, Miadreza & Catalão, João P.S., 2021. "Multi-level optimization framework for resilient distribution system expansion planning with distributed energy resources," Energy, Elsevier, vol. 214(C).
    3. Zamani Gargari, Milad & Tarafdar Hagh, Mehrdad & Ghassem Zadeh, Saeid, 2023. "Preventive scheduling of a multi-energy microgrid with mobile energy storage to enhance the resiliency of the system," Energy, Elsevier, vol. 263(PC).
    4. Clegg, J. & Smith, M. J., 2001. "Cone projection versus half-space projection for the bilevel optimisation of transportation networks," Transportation Research Part B: Methodological, Elsevier, vol. 35(1), pages 71-82, January.
    5. Wu, Hao & Xie, Yunyun & Xu, Yan & Wu, Qiuwei & Yu, Chen & Sun, Jinsheng, 2022. "Resilient scheduling of MESSs and RCs for distribution system restoration considering the forced cut-off of wind power," Energy, Elsevier, vol. 244(PB).
    6. Zhao, Baining & Qian, Tong & Tang, Wenhu & Liang, Qiheng, 2022. "A data-enhanced distributionally robust optimization method for economic dispatch of integrated electricity and natural gas systems with wind uncertainty," Energy, Elsevier, vol. 243(C).
    7. Nikoobakht, Ahmad & Aghaei, Jamshid, 2022. "Resilience promotion of active distribution grids under high penetration of renewables using flexible controllers," Energy, Elsevier, vol. 257(C).
    8. Olabi, A.G. & Onumaegbu, C. & Wilberforce, Tabbi & Ramadan, Mohamad & Abdelkareem, Mohammad Ali & Al – Alami, Abdul Hai, 2021. "Critical review of energy storage systems," Energy, Elsevier, vol. 214(C).
    9. Younesi, Abdollah & Shayeghi, Hossein & Safari, Amin & Siano, Pierluigi, 2020. "Assessing the resilience of multi microgrid based widespread power systems against natural disasters using Monte Carlo Simulation," Energy, Elsevier, vol. 207(C).
    10. Zhang, Yin & Qian, Tong & Tang, Wenhu, 2022. "Buildings-to-distribution-network integration considering power transformer loading capability and distribution network reconfiguration," Energy, Elsevier, vol. 244(PB).
    11. Jeon, Soi & Choi, Dae-Hyun, 2022. "Joint optimization of Volt/VAR control and mobile energy storage system scheduling in active power distribution networks under PV prediction uncertainty," Applied Energy, Elsevier, vol. 310(C).
    12. Gilani, Mohammad Amin & Kazemi, Ahad & Ghasemi, Mostafa, 2020. "Distribution system resilience enhancement by microgrid formation considering distributed energy resources," Energy, Elsevier, vol. 191(C).
    13. Qian, Tong & Chen, Xingyu & Xin, Yanli & Tang, Wenhu & Wang, Lixiao, 2022. "Resilient decentralized optimization of chance constrained electricity-gas systems over lossy communication networks," Energy, Elsevier, vol. 239(PB).
    14. Esteban, Miguel & Portugal-Pereira, Joana, 2014. "Post-disaster resilience of a 100% renewable energy system in Japan," Energy, Elsevier, vol. 68(C), pages 756-764.
    Full references (including those not matched with items on IDEAS)

    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. Li, Weiwei & Qian, Tong & Zhang, Yin & Shen, Yueqing & Wu, Chenghu & Tang, Wenhu, 2023. "Distributionally robust chance-constrained planning for regional integrated electricity–heat systems with data centers considering wind power uncertainty," Applied Energy, Elsevier, vol. 336(C).
    2. Nikoobakht, Ahmad & Aghaei, Jamshid, 2022. "Resilience promotion of active distribution grids under high penetration of renewables using flexible controllers," Energy, Elsevier, vol. 257(C).
    3. da Silva, Fellipe Sartori & Matelli, José Alexandre, 2021. "Resilience in cogeneration systems: Metrics for evaluation and influence of design aspects," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    4. Yang, Tongxu & Zhang, Limei & Zhen, Linteng & Liu, Yongfu & Song, Qianqian & Tang, Wei, 2021. "Fast microgrids formation of distribution network with high penetration of DERs considering reliability," Energy, Elsevier, vol. 236(C).
    5. Cheayb, Mohamad & Marin Gallego, Mylène & Tazerout, Mohand & Poncet, Sébastien, 2022. "A techno-economic analysis of small-scale trigenerative compressed air energy storage system," Energy, Elsevier, vol. 239(PA).
    6. Jānis Krūmiņš & Māris Kļaviņš, 2023. "Investigating the Potential of Nuclear Energy in Achieving a Carbon-Free Energy Future," Energies, MDPI, vol. 16(9), pages 1-31, April.
    7. Timothy Fraser & Lily Cunningham & Amos Nasongo, 2021. "Build Back Better? Effects of Crisis on Climate Change Adaptation Through Solar Power in Japan and the United States," Global Environmental Politics, MIT Press, vol. 21(1), pages 54-75, Winter.
    8. J. Rajalakshmi & S. Durairaj, 2021. "Application of multi-objective optimization algorithm for siting and sizing of distributed generations in distribution networks," Journal of Combinatorial Optimization, Springer, vol. 41(2), pages 267-289, February.
    9. Ameen, Muhammad Tahir & Ma, Zhiwei & Smallbone, Andrew & Norman, Rose & Roskilly, Anthony Paul, 2023. "Demonstration system of pumped heat energy storage (PHES) and its round-trip efficiency," Applied Energy, Elsevier, vol. 333(C).
    10. Li, Weiwei & Qian, Tong & Zhao, Wei & Huang, Wenwei & Zhang, Yin & Xie, Xuehua & Tang, Wenhu, 2023. "Decentralized optimization for integrated electricity–heat systems with data center based energy hub considering communication packet loss," Applied Energy, Elsevier, vol. 350(C).
    11. Li, Chengchen & Wang, Huanran & He, Xin & Zhang, Yan, 2022. "Experimental and thermodynamic investigation on isothermal performance of large-scaled liquid piston," Energy, Elsevier, vol. 249(C).
    12. Dzido, Aleksandra & Krawczyk, Piotr & Wołowicz, Marcin & Badyda, Krzysztof, 2022. "Comparison of advanced air liquefaction systems in Liquid Air Energy Storage applications," Renewable Energy, Elsevier, vol. 184(C), pages 727-739.
    13. Toufani, Parinaz & Nadar, Emre & Kocaman, Ayse Selin, 2022. "Short-term assessment of pumped hydro energy storage configurations: Up, down, or closed?," Renewable Energy, Elsevier, vol. 201(P1), pages 1086-1095.
    14. Knuepfer, K. & Rogalski, N. & Knuepfer, A. & Esteban, M. & Shibayama, T., 2022. "A reliable energy system for Japan with merit order dispatch, high variable renewable share and no nuclear power," Applied Energy, Elsevier, vol. 328(C).
    15. Herc, Luka & Pfeifer, Antun & Duić, Neven & Wang, Fei, 2022. "Economic viability of flexibility options for smart energy systems with high penetration of renewable energy," Energy, Elsevier, vol. 252(C).
    16. Liu, Mingyi & Qian, Feng & Mi, Jia & Zuo, Lei, 2022. "Biomechanical energy harvesting for wearable and mobile devices: State-of-the-art and future directions," Applied Energy, Elsevier, vol. 321(C).
    17. Martina Pilloni & József Kádár & Tareq Abu Hamed, 2022. "The Impact of COVID-19 on Energy Start-Up Companies: The Use of Global Financial Crisis (GFC) as a Lesson for Future Recovery," Energies, MDPI, vol. 15(10), pages 1-15, May.
    18. Savolainen, Rebecka & Lahdelma, Risto, 2022. "Optimization of renewable energy for buildings with energy storages and 15-minute power balance," Energy, Elsevier, vol. 243(C).
    19. Chia-Nan Wang & Hector Tibo & Duy Hung Duong, 2020. "Renewable Energy Utilization Analysis of Highly and Newly Industrialized Countries Using an Undesirable Output Model," Energies, MDPI, vol. 13(10), pages 1-21, May.
    20. Kabir, Farzana & Yu, Nanpeng & Gao, Yuanqi & Wang, Wenyu, 2023. "Deep reinforcement learning-based two-timescale Volt-VAR control with degradation-aware smart inverters in power distribution systems," Applied Energy, Elsevier, vol. 335(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:s0360544223016948. 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.