IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v163y2022ics1366554522001430.html
   My bibliography  Save this article

A computational approach for real-time stochastic recovery of electric power networks during a disaster

Author

Listed:
  • Inanlouganji, Alireza
  • Pedrielli, Giulia
  • Reddy, T. Agami
  • Tormos Aponte, Fernando

Abstract

Disasters are occurring with increasing frequency worldwide, causing significant social hardship and economic losses. Critical infrastructures such as electric power networks are prone to failure under such events, and this significantly impacts the daily lives of people in affected areas. It is hence critical that the restoration planning of these power networks be done proactively. Disaster response in power networks is a well-studied problem, especially for pre-and post-event restoration Similar to pre-event, we consider uncertainty associated with the failure paths, and we look into real-time response while failures are happening. In this regard, at each time step, we move repair teams towards distribution loads based on their current state, their likelihood to fail, and the impact of the damage in case of node failure. We consider large-scale networks (>50 nodes and >20 repair teams) and propose an efficient algorithm to support real-time recovery.

Suggested Citation

  • Inanlouganji, Alireza & Pedrielli, Giulia & Reddy, T. Agami & Tormos Aponte, Fernando, 2022. "A computational approach for real-time stochastic recovery of electric power networks during a disaster," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).
    • Handle: RePEc:eee:transe:v:163:y:2022:i:c:s1366554522001430
    DOI: 10.1016/j.tre.2022.102752
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554522001430
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tre.2022.102752?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. Tuzun Aksu, Dilek & Ozdamar, Linet, 2014. "A mathematical model for post-disaster road restoration: Enabling accessibility and evacuation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 61(C), pages 56-67.
    2. Michele Ciavotta & Carlo Meloni & Marco Pranzo, 2016. "Speeding up a Rollout algorithm for complex parallel machine scheduling," International Journal of Production Research, Taylor & Francis Journals, vol. 54(16), pages 4993-5009, August.
    3. Lu, Chung-Cheng & Ying, Kuo-Ching & Chen, Hui-Ju, 2016. "Real-time relief distribution in the aftermath of disasters – A rolling horizon approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 1-20.
    4. Caunhye, Aakil M. & Zhang, Yidong & Li, Mingzhe & Nie, Xiaofeng, 2016. "A location-routing model for prepositioning and distributing emergency supplies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 90(C), pages 161-176.
    5. anonymous, 2000. "Building personal wealth: a conversation with Bob McTeer," Banking and Community Perspectives, Federal Reserve Bank of Dallas, issue Q4, pages 1-2.
    6. Li, Anna C.Y. & Nozick, Linda & Xu, Ningxiong & Davidson, Rachel, 2012. "Shelter location and transportation planning under hurricane conditions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(4), pages 715-729.
    7. Rezaei-Malek, Mohammad & Tavakkoli-Moghaddam, Reza & Cheikhrouhou, Naoufel & Taheri-Moghaddam, Alireza, 2016. "An approximation approach to a trade-off among efficiency, efficacy, and balance for relief pre-positioning in disaster management," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 485-509.
    8. Ali Torabi, S. & Shokr, Iman & Tofighi, Saeideh & Heydari, Jafar, 2018. "Integrated relief pre-positioning and procurement planning in humanitarian supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 113(C), pages 123-146.
    9. Shahparvari, Shahrooz & Chhetri, Prem & Abbasi, Babak & Abareshi, Ahmad, 2016. "Enhancing emergency evacuation response of late evacuees: Revisiting the case of Australian Black Saturday bushfire," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 148-176.
    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. Kundu, Tanmoy & Sheu, Jiuh-Biing & Kuo, Hsin-Tsz, 2022. "Emergency logistics management—Review and propositions for future research," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    2. Rodríguez-Espíndola, Oscar & Ahmadi, Hossein & Gastélum-Chavira, Diego & Ahumada-Valenzuela, Omar & Chowdhury, Soumyadeb & Dey, Prasanta Kumar & Albores, Pavel, 2023. "Humanitarian logistics optimization models: An investigation of decision-maker involvement and directions to promote implementation," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    3. Sabbaghtorkan, Monir & Batta, Rajan & He, Qing, 2020. "Prepositioning of assets and supplies in disaster operations management: Review and research gap identification," European Journal of Operational Research, Elsevier, vol. 284(1), pages 1-19.
    4. Dönmez, Zehranaz & Kara, Bahar Y. & Karsu, Özlem & Saldanha-da-Gama, Francisco, 2021. "Humanitarian facility location under uncertainty: Critical review and future prospects," Omega, Elsevier, vol. 102(C).
    5. Fatemeh Faghih-Mohammadi & Mohammad Mahdi Nasiri & Dinçer Konur, 2023. "Cross-dock facility for disaster relief operations," Annals of Operations Research, Springer, vol. 322(1), pages 497-538, March.
    6. Yiping Jiang & Yufei Yuan, 2019. "Emergency Logistics in a Large-Scale Disaster Context: Achievements and Challenges," IJERPH, MDPI, vol. 16(5), pages 1-23, March.
    7. Zhang, Lingye & Lu, Jing & Yang, Zaili, 2021. "Optimal scheduling of emergency resources for major maritime oil spills considering time-varying demand and transportation networks," European Journal of Operational Research, Elsevier, vol. 293(2), pages 529-546.
    8. Govindan, Kannan & Mina, Hassan & Alavi, Behrouz, 2020. "A decision support system for demand management in healthcare supply chains considering the epidemic outbreaks: A case study of coronavirus disease 2019 (COVID-19)," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    9. Khanchehzarrin, Saeed & Ghaebi Panah, Mona & Mahdavi-Amiri, Nezam & Shiripour, Saber, 2022. "A bi-level multi-objective location-routing optimization model for disaster relief operations considering public donations," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    10. Zhongzhen Yang & Liquan Guo & Zaili Yang, 2019. "Emergency logistics for wildfire suppression based on forecasted disaster evolution," Annals of Operations Research, Springer, vol. 283(1), pages 917-937, December.
    11. Ghavamifar, Ali & Torabi, S. Ali & Moshtari, Mohammad, 2022. "A hybrid relief procurement contract for humanitarian logistics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    12. Wang, Qingyi & Nie, Xiaofeng, 2022. "A stochastic programming model for emergency supply planning considering transportation network mitigation and traffic congestion," Socio-Economic Planning Sciences, Elsevier, vol. 79(C).
    13. Hu, Shaolong & Dong, Zhijie Sasha & Lev, Benjamin, 2022. "Supplier selection in disaster operations management: Review and research gap identification," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    14. Aghajani, Mojtaba & Torabi, S. Ali & Heydari, Jafar, 2020. "A novel option contract integrated with supplier selection and inventory prepositioning for humanitarian relief supply chains," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    15. Hu, Shaolong & Hu, Qingmi & Tao, Sha & Dong, Zhijie Sasha, 2023. "A multi-stage stochastic programming approach for pre-positioning of relief supplies considering returns," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    16. Bian Liang & Dapeng Yang & Xinghong Qin & Teresa Tinta, 2019. "A Risk-Averse Shelter Location and Evacuation Routing Assignment Problem in an Uncertain Environment," IJERPH, MDPI, vol. 16(20), pages 1-28, October.
    17. Akbarpour, Mina & Ali Torabi, S. & Ghavamifar, Ali, 2020. "Designing an integrated pharmaceutical relief chain network under demand uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    18. Aghajani, Mojtaba & Ali Torabi, S. & Altay, Nezih, 2023. "Resilient relief supply planning using an integrated procurement-warehousing model under supply disruption," Omega, Elsevier, vol. 118(C).
    19. Shuanglin Li & Kok Lay Teo, 2019. "Post-disaster multi-period road network repair: work scheduling and relief logistics optimization," Annals of Operations Research, Springer, vol. 283(1), pages 1345-1385, December.
    20. Sarhadi, Hassan & Naoum-Sawaya, Joe & Verma, Manish, 2020. "A robust optimization approach to locating and stockpiling marine oil-spill response facilities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(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:transe:v:163:y:2022:i:c:s1366554522001430. 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.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .

    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.