IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i6p2167-d331290.html
   My bibliography  Save this article

Enhancing Integrated Power and Water Distribution Networks Seismic Resilience Leveraging Microgrids

Author

Listed:
  • Javad Najafi

    (Department of Electrical Engineering, Ferdowsi University of Mashhad, Mashhad, Iran)

  • Ali Peiravi

    (Department of Electrical Engineering, Ferdowsi University of Mashhad, Mashhad, Iran)

  • Amjad Anvari-Moghaddam

    (Department of Energy Technology, Aalborg University, 9220 Aalborg, Denmark
    Faculty of Electrical and Computer Engineering, University of Tabriz, 5166616471 Tabriz, Iran)

Abstract

An earthquake, as one of the natural disasters, can damage vital infrastructures including the power distribution network (PDN) and water distribution network (WDN). The dependency of WDN on PDN is the other challenge that can be highlighted after the earthquake. In this paper, the resilience improvement planning of integrated PDN and WDN against earthquakes is solved through stochastic programming. Power lines and substation hardening in PDN and water pipes rehabilitation with better material are the candidate strategies to minimize the expected inaccessibility value of loads to power and water as the resilience index and to minimize the cost of strategies. The proposed model is tested on the modified IEEE 33-bus PDN with a designed WDN and its performance is evaluated under different cases where the impacts of using distributed generations (DG) in PDN, equipping the water pumps to back-up generators, and the value of loads accessibility to water on the system resilience are investigated.

Suggested Citation

  • Javad Najafi & Ali Peiravi & Amjad Anvari-Moghaddam, 2020. "Enhancing Integrated Power and Water Distribution Networks Seismic Resilience Leveraging Microgrids," Sustainability, MDPI, vol. 12(6), pages 1-16, March.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:6:p:2167-:d:331290
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/6/2167/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/6/2167/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Almoghathawi, Yasser & Barker, Kash & Albert, Laura A., 2019. "Resilience-driven restoration model for interdependent infrastructure networks," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 12-23.
    2. Hui Zhang & Xin Cheng & Tinglin Huang & Haibing Cong & Jinlan Xu, 2017. "Hydraulic Analysis of Water Distribution Systems Based on Fixed Point Iteration Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(5), pages 1605-1618, March.
    3. Lin, Yanling & Bie, Zhaohong, 2018. "Tri-level optimal hardening plan for a resilient distribution system considering reconfiguration and DG islanding," Applied Energy, Elsevier, vol. 210(C), pages 1266-1279.
    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. Artis, Reza & Assili, Mohsen & Shivaie, Mojtaba, 2022. "A seismic-resilient multi-level framework for distribution network reinforcement planning considering renewable-based multi-microgrids," Applied Energy, Elsevier, vol. 325(C).
    2. Wu, Raphael & Sansavini, Giovanni, 2020. "Integrating reliability and resilience to support the transition from passive distribution grids to islanding microgrids," Applied Energy, Elsevier, vol. 272(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. Xu, Luo & Guo, Qinglai & Sheng, Yujie & Muyeen, S.M. & Sun, Hongbin, 2021. "On the resilience of modern power systems: A comprehensive review from the cyber-physical perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    2. Liu, Huan & Tatano, Hirokazu & Pflug, Georg & Hochrainer-Stigler, Stefan, 2021. "Post-disaster recovery in industrial sectors: A Markov process analysis of multiple lifeline disruptions," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    3. Habiba Drias & Lydia Sonia Bendimerad & Yassine Drias, 2022. "A Three-Phase Artificial Orcas Algorithm for Continuous and Discrete Problems," International Journal of Applied Metaheuristic Computing (IJAMC), IGI Global, vol. 13(1), pages 1-20, January.
    4. Ghaneshvar Ramineni & Nafiseh Ghorbani-Renani & Kash Barker & Andrés D. González & Talayeh Razzaghi & Sridhar Radhakrishnan, 2023. "Machine learning approaches to modeling interdependent network restoration time," Environment Systems and Decisions, Springer, vol. 43(1), pages 22-35, March.
    5. Mühlhofer, Evelyn & Koks, Elco E. & Kropf, Chahan M. & Sansavini, Giovanni & Bresch, David N., 2023. "A generalized natural hazard risk modelling framework for infrastructure failure cascades," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    6. Talebiyan, Hesam & Dueñas-Osorio, Leonardo, 2023. "Auctions for resource allocation and decentralized restoration of interdependent networks," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    7. Emenike, Scholastica N. & Falcone, Gioia, 2020. "A review on energy supply chain resilience through optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    8. Bešinović, Nikola & Ferrari Nassar, Raphael & Szymula, Christopher, 2022. "Resilience assessment of railway networks: Combining infrastructure restoration and transport management," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    9. Hou, Hui & Tang, Junyi & Zhang, Zhiwei & Wang, Zhuo & Wei, Ruizeng & Wang, Lei & He, Huan & Wu, Xixiu, 2023. "Resilience enhancement of distribution network under typhoon disaster based on two-stage stochastic programming," Applied Energy, Elsevier, vol. 338(C).
    10. Liu, Jia & Cheng, Haozhong & Zeng, Pingliang & Yao, Liangzhong & Shang, Ce & Tian, Yuan, 2018. "Decentralized stochastic optimization based planning of integrated transmission and distribution networks with distributed generation penetration," Applied Energy, Elsevier, vol. 220(C), pages 800-813.
    11. Wang, Yi & Rousis, Anastasios Oulis & Strbac, Goran, 2020. "On microgrids and resilience: A comprehensive review on modeling and operational strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    12. Mottahedi, Adel & Sereshki, Farhang & Ataei, Mohammad & Qarahasanlou, Ali Nouri & Barabadi, Abbas, 2021. "Resilience estimation of critical infrastructure systems: Application of expert judgment," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    13. Liu, Xing & Fang, Yi-Ping & Zio, Enrico, 2021. "A Hierarchical Resilience Enhancement Framework for Interdependent Critical Infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    14. Gilani, Mohammad Amin & Kazemi, Ahad & Ghasemi, Mostafa, 2020. "Distribution system resilience enhancement by microgrid formation considering distributed energy resources," Energy, Elsevier, vol. 191(C).
    15. Sharma, Neetesh & Gardoni, Paolo, 2022. "Mathematical modeling of interdependent infrastructure: An object-oriented approach for generalized network-system analysis," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    16. Shang, Ce & Lin, Teng & Li, Canbing & Wang, Keyou & Ai, Qian, 2021. "Joining resilience and reliability evaluation against both weather and ageing causes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    17. Kamali, Behnaz & Ziaei, Ali Naghi & Beheshti, Aliasghar & Farmani, Raziyeh, 2022. "An open-source toolbox for investigating functional resilience in sewer networks based on global resilience analysis," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    18. Liu, Meili & Qi, Xiaogang & Pan, Hao, 2022. "Optimizing communication network geodiversity for disaster resilience through shielding approach," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    19. Linas Martišauskas & Juozas Augutis & Ričardas Krikštolaitis & Rolandas Urbonas & Inga Šarūnienė & Vytis Kopustinskas, 2022. "A Framework to Assess the Resilience of Energy Systems Based on Quantitative Indicators," Energies, MDPI, vol. 15(11), pages 1-25, May.
    20. Wang, Han & Hou, Kai & Zhao, Junbo & Yu, Xiaodan & Jia, Hongjie & Mu, Yunfei, 2022. "Planning-Oriented resilience assessment and enhancement of integrated electricity-gas system considering multi-type natural disasters," Applied Energy, Elsevier, vol. 315(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:gam:jsusta:v:12:y:2020:i:6:p:2167-:d:331290. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.