IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v152y2021ics1364032121009114.html
   My bibliography  Save this article

Stochastic pre-event preparation for enhancing resilience of distribution systems

Author

Listed:
  • Zhang, Qianzhi
  • Wang, Zhaoyu
  • Ma, Shanshan
  • Arif, Anmar

Abstract

Extreme weather events are the common causes for power supply interruptions and power outages in electrical distribution systems. Improving the distribution system and enhancing its resilience is becoming crucial due to the increased frequency of extreme weather events. Preparation and allocation of multiple flexible resources, such as mobile resources, fuel resources, and labor resources before extreme weather events can mitigate the effects of extreme weather events and enhance the resilience of power distribution systems. In this paper, a two-stage stochastic mixed-integer linear programming (SMILP) is proposed to optimize the preparation and resource allocation process for upcoming extreme weather events, which leads to faster and more efficient post-event restoration. The objective of the proposed two-stage SMILP is to maximize the served load and minimize the operating cost of flexible resources. The first stage in the optimization problem selects the amounts and locations of different resources. The second stage considers the operational constraints of the distribution system and repair crew scheduling constraints. The proposed stochastic pre-event preparation model is solved by a scenario decomposition method, Progressive Hedging (PH), to ease the computational complexity introduced by a large number of scenarios. Furthermore, to show the impact of solar photovoltaic (PV) generation on system resilience, three types of PV systems are considered during a power outage and the resilience improvements with different PV penetration levels are compared. Numerical results from simulations on a large-scale (more than 10,000 nodes) distribution feeder have been used to validate the effectiveness and scalability of the proposed method.

Suggested Citation

  • Zhang, Qianzhi & Wang, Zhaoyu & Ma, Shanshan & Arif, Anmar, 2021. "Stochastic pre-event preparation for enhancing resilience of distribution systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    • Handle: RePEc:eee:rensus:v:152:y:2021:i:c:s1364032121009114
    DOI: 10.1016/j.rser.2021.111636
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032121009114
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2021.111636?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. Molyneaux, Lynette & Brown, Colin & Wagner, Liam & Foster, John, 2016. "Measuring resilience in energy systems: Insights from a range of disciplines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1068-1079.
    2. Wang, Shaojun & Sarker, Bhaba R. & Mann, Lawrence & Triantaphyllou, Evangelos, 2004. "Resource planning and a depot location model for electric power restoration," European Journal of Operational Research, Elsevier, vol. 155(1), pages 22-43, May.
    3. R. T. Rockafellar & Roger J.-B. Wets, 1991. "Scenarios and Policy Aggregation in Optimization Under Uncertainty," Mathematics of Operations Research, INFORMS, vol. 16(1), pages 119-147, February.
    4. Martin, Nigel & Rice, John, 2021. "Power outages, climate events and renewable energy: Reviewing energy storage policy and regulatory options for Australia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    5. Mishra, Dillip Kumar & Ghadi, Mojtaba Jabbari & Azizivahed, Ali & Li, Li & Zhang, Jiangfeng, 2021. "A review on resilience studies in active distribution systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    6. Das, Laya & Munikoti, Sai & Natarajan, Balasubramaniam & Srinivasan, Babji, 2020. "Measuring smart grid resilience: Methods, challenges and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
    7. Mousavizadeh, Saeed & Haghifam, Mahmoud-Reza & Shariatkhah, Mohammad-Hossein, 2018. "A linear two-stage method for resiliency analysis in distribution systems considering renewable energy and demand response resources," Applied Energy, Elsevier, vol. 211(C), pages 443-460.
    8. Schmitz, William Ismael & Schmitz, Magdiel & Canha, Luciane Neves & Garcia, Vinícius Jacques, 2020. "Proactive home energy storage management system to severe weather scenarios," Applied Energy, Elsevier, vol. 279(C).
    9. Feldpausch-Parker, Andrea M. & Peterson, Tarla Rai & Stephens, Jennie C. & Wilson, Elizabeth J., 2018. "Smart grid electricity system planning and climate disruptions: A review of climate and energy discourse post-Superstorm Sandy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P2), pages 1961-1968.
    10. Dehghani, Nariman L. & Jeddi, Ashkan B. & Shafieezadeh, Abdollah, 2021. "Intelligent hurricane resilience enhancement of power distribution systems via deep reinforcement learning," Applied Energy, Elsevier, vol. 285(C).
    11. Sharifi, Ayyoob & Yamagata, Yoshiki, 2016. "Principles and criteria for assessing urban energy resilience: A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1654-1677.
    12. Emmanuel, Michael & Rayudu, Ramesh, 2017. "Evolution of dispatchable photovoltaic system integration with the electric power network for smart grid applications: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 207-224.
    13. Jean-Paul Watson & David Woodruff, 2011. "Progressive hedging innovations for a class of stochastic mixed-integer resource allocation problems," Computational Management Science, Springer, vol. 8(4), pages 355-370, November.
    14. Emenike, Scholastica N. & Falcone, Gioia, 2020. "A review on energy supply chain resilience through optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    15. Salman, Abdullahi M. & Li, Yue & Stewart, Mark G., 2015. "Evaluating system reliability and targeted hardening strategies of power distribution systems subjected to hurricanes," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 319-333.
    16. Craig, Michael T. & Cohen, Stuart & Macknick, Jordan & Draxl, Caroline & Guerra, Omar J. & Sengupta, Manajit & Haupt, Sue Ellen & Hodge, Bri-Mathias & Brancucci, Carlo, 2018. "A review of the potential impacts of climate change on bulk power system planning and operations in the United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 98(C), pages 255-267.
    17. Ranaweera, Iromi & Midtgård, Ole-Morten, 2016. "Optimization of operational cost for a grid-supporting PV system with battery storage," Renewable Energy, Elsevier, vol. 88(C), pages 262-272.
    18. Abdin, I.F. & Fang, Y.-P. & Zio, E., 2019. "A modeling and optimization framework for power systems design with operational flexibility and resilience against extreme heat waves and drought events," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 706-719.
    19. Okoye, Chiemeka Onyeka & Taylan, Onur & Baker, Derek K., 2016. "Solar energy potentials in strategically located cities in Nigeria: Review, resource assessment and PV system design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 550-566.
    20. 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. 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).
    2. Wang, Chong & Ju, Ping & Wu, Feng & Pan, Xueping & Wang, Zhaoyu, 2022. "A systematic review on power system resilience from the perspective of generation, network, and load," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    3. Liu, Hanchen & Wang, Chong & Ju, Ping & Li, Hongyu, 2022. "A sequentially preventive model enhancing power system resilience against extreme-weather-triggered failures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(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. Liu, Hanchen & Wang, Chong & Ju, Ping & Li, Hongyu, 2022. "A sequentially preventive model enhancing power system resilience against extreme-weather-triggered failures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    2. Lei, Shunbo & Pozo, David & Wang, Ming-Hao & Li, Qifeng & Li, Yupeng & Peng, Chaoyi, 2022. "Power economic dispatch against extreme weather conditions: The price of resilience," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    3. Wang, Chong & Ju, Ping & Wu, Feng & Lei, Shunbo & Pan, Xueping, 2021. "Sequential steady-state security region-based transmission power system resilience enhancement," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    4. 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).
    5. Wang, Chong & Ju, Ping & Wu, Feng & Pan, Xueping & Wang, Zhaoyu, 2022. "A systematic review on power system resilience from the perspective of generation, network, and load," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    6. Wang, Zekai & Ding, Tao & Jia, Wenhao & Huang, Can & Mu, Chenggang & Qu, Ming & Shahidehpour, Mohammad & Yang, Yongheng & Blaabjerg, Frede & Li, Li & Wang, Kang & Chi, Fangde, 2022. "Multi-stage stochastic programming for resilient integrated electricity and natural gas distribution systems against typhoon natural disaster attacks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    7. Perera, A.T.D. & Hong, Tianzhen, 2023. "Vulnerability and resilience of urban energy ecosystems to extreme climate events: A systematic review and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 173(C).
    8. Umunnakwe, A. & Huang, H. & Oikonomou, K. & Davis, K.R., 2021. "Quantitative analysis of power systems resilience: Standardization, categorizations, and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    9. 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).
    10. Jasiūnas, Justinas & Lund, Peter D. & Mikkola, Jani, 2021. "Energy system resilience – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    11. Hussain, Akhtar & Bui, Van-Hai & Kim, Hak-Man, 2019. "Microgrids as a resilience resource and strategies used by microgrids for enhancing resilience," Applied Energy, Elsevier, vol. 240(C), pages 56-72.
    12. Mishra, Dillip Kumar & Ghadi, Mojtaba Jabbari & Azizivahed, Ali & Li, Li & Zhang, Jiangfeng, 2021. "A review on resilience studies in active distribution systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    13. Lee, Jinkyu & Bae, Sanghyeon & Kim, Woo Chang & Lee, Yongjae, 2023. "Value function gradient learning for large-scale multistage stochastic programming problems," European Journal of Operational Research, Elsevier, vol. 308(1), pages 321-335.
    14. Dong, Kangyin & Dong, Xiucheng & Jiang, Qingzhe & Zhao, Jun, 2021. "Assessing energy resilience and its greenhouse effect: A global perspective," Energy Economics, Elsevier, vol. 104(C).
    15. Wu, Dexiang & Wu, Desheng Dash, 2020. "A decision support approach for two-stage multi-objective index tracking using improved lagrangian decomposition," Omega, Elsevier, vol. 91(C).
    16. Kevin Ryan & Shabbir Ahmed & Santanu S. Dey & Deepak Rajan & Amelia Musselman & Jean-Paul Watson, 2020. "Optimization-Driven Scenario Grouping," INFORMS Journal on Computing, INFORMS, vol. 32(3), pages 805-821, July.
    17. Fan, Yingjie & Schwartz, Frank & Voß, Stefan, 2017. "Flexible supply chain planning based on variable transportation modes," International Journal of Production Economics, Elsevier, vol. 183(PC), pages 654-666.
    18. Gilles Bareilles & Yassine Laguel & Dmitry Grishchenko & Franck Iutzeler & Jérôme Malick, 2020. "Randomized Progressive Hedging methods for multi-stage stochastic programming," Annals of Operations Research, Springer, vol. 295(2), pages 535-560, December.
    19. Mujjuni, F. & Betts, T. & To, L.S. & Blanchard, R.E., 2021. "Resilience a means to development: A resilience assessment framework and a catalogue of indicators," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    20. Hu, Shaolong & Han, Chuanfeng & Dong, Zhijie Sasha & Meng, Lingpeng, 2019. "A multi-stage stochastic programming model for relief distribution considering the state of road network," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 64-87.

    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:rensus:v:152:y:2021:i:c:s1364032121009114. 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/600126/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.