IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i13p3394-d1689123.html
   My bibliography  Save this article

Resilience Enhancement for Distribution Networks Under Typhoon-Induced Multi-Source Uncertainties

Author

Listed:
  • Naixuan Zhu

    (Economic and Technology Institute, State Grid Fujian Electric Power Co., Ltd., Fuzhou 350013, China
    Distribution Network Planning and Operation Control Technology in Multiple Disaster Superimposed Areas State Grid Corporation Laboratory, Fuzhou 350013, China)

  • Guilian Wu

    (Economic and Technology Institute, State Grid Fujian Electric Power Co., Ltd., Fuzhou 350013, China
    Distribution Network Planning and Operation Control Technology in Multiple Disaster Superimposed Areas State Grid Corporation Laboratory, Fuzhou 350013, China
    Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)

  • Hao Chen

    (Economic and Technology Institute, State Grid Fujian Electric Power Co., Ltd., Fuzhou 350013, China
    Distribution Network Planning and Operation Control Technology in Multiple Disaster Superimposed Areas State Grid Corporation Laboratory, Fuzhou 350013, China)

  • Nuoling Sun

    (Economic and Technology Institute, State Grid Fujian Electric Power Co., Ltd., Fuzhou 350013, China
    Distribution Network Planning and Operation Control Technology in Multiple Disaster Superimposed Areas State Grid Corporation Laboratory, Fuzhou 350013, China)

Abstract

The increasing prevalence of extreme weather events poses significant challenges to the stability of distribution networks (DNs). To enhance the resilience of DNs against such events, a typhoon-oriented resilience framework for DNs is proposed that incorporates multiple sources of typhoon uncertainty. First, component failure probability is modeled by tracking time-sequential variations in typhoon landfall parameters, trajectory, and intensity, thereby improving the quantitative estimation of typhoon impacts. Then, the integrated component failure probability and the importance factor of bus load under disaster are combined and hierarchical analysis is performed to achieve the vulnerability identification for DNs. Next, based on the vulnerability identification results, a resilience enhancement model for DNs is constructed through the strategy of coordinating line reinforcement and energy storage configuration, and the resilience optimization scheme that takes into account the system resilience enhancement effect and economy is obtained under the optimal investment cost. Finally, analysis and verification are conducted in the IEEE 33-bus system. The results indicate that the proposed method can reduce the load loss cost of the system by 5.112 million and 0.2459 million, respectively.

Suggested Citation

  • Naixuan Zhu & Guilian Wu & Hao Chen & Nuoling Sun, 2025. "Resilience Enhancement for Distribution Networks Under Typhoon-Induced Multi-Source Uncertainties," Energies, MDPI, vol. 18(13), pages 1-21, June.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:13:p:3394-:d:1689123
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/13/3394/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/18/13/3394/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Minhui Qian & Ning Chen & Yuge Chen & Changming Chen & Weiqiang Qiu & Dawei Zhao & Zhenzhi Lin, 2021. "Optimal Coordinated Dispatching Strategy of Multi-Sources Power System with Wind, Hydro and Thermal Power Based on CVaR in Typhoon Environment," Energies, MDPI, vol. 14(13), pages 1-35, June.
    2. Wang, Shuaijie & Hou, Ye & Guan, Xin & Liu, Shu & Huo, Zhaoyi, 2024. "Resiliency-informed optimal scheduling of smart distribution network with urban distributed photovoltaic: A stochastic P-robust optimization," Energy, Elsevier, vol. 313(C).
    3. Wu, Wenjie & Hou, Hui & Zhu, Shaohua & Liu, Qin & Wei, Ruizeng & He, Huan & Wang, Lei & Luo, Yingting, 2024. "An intelligent power grid emergency allocation technology considering secondary disaster and public opinion under typhoon disaster," Applied Energy, Elsevier, vol. 353(PA).
    4. Hao Dai & Dafu Liu & Guowei Liu & Hao Deng & Lisheng Xin & Longlong Shang & Ziyu Liu & Ziwen Xu & Jiaju Shi & Chen Chen, 2025. "A Method for Restoring Power Supply to Distribution Networks Considering the Coordination of Multiple Resources Under Typhoon-Induced Waterlogging Disasters," Energies, MDPI, vol. 18(5), pages 1-17, March.
    5. Tang, Liangyu & Han, Yang & Zhou, Siyu & Zalhaf, Amr S. & Yang, Ping & Wang, Congling & Huang, Tao & Lu, Chang, 2025. "Identification and vulnerability assessment of critical components in distribution networks under high penetration rate conditions," Energy, Elsevier, vol. 318(C).
    6. Spyros Giannelos & Danny Pudjianto & Tai Zhang & Goran Strbac, 2025. "Energy Hub Operation Under Uncertainty: Monte Carlo Risk Assessment Using Gaussian and KDE-Based Data," Energies, MDPI, vol. 18(7), pages 1-20, March.
    7. Anduo Hu & Xiaoyue Fan & Dongmei Huang & Feng Zhang & Shuai Shi, 2023. "Risk Assessment of Distribution Lines in Typhoon Weather Considering Socio-economic Factors," Energies, MDPI, vol. 16(18), pages 1-15, September.
    8. Kejian Shi & Ting Wang & Zikuo Dai & Ye Tian & Pu Yang & Haifeng Li, 2024. "Identification and Evaluation of Vulnerable Links in a Distribution Network with Renewable Energy Source Based on Minimum Discriminant Information," Energies, MDPI, vol. 17(17), pages 1-19, September.
    9. Wenqing Ma & Xiaofu Xiong & Jian Wang, 2025. "Rapid Resilience Assessment and Weak Link Analysis of Power Systems Considering Uncertainties of Typhoon," Energies, MDPI, vol. 18(7), pages 1-20, March.
    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. Xuntao Shi & Jian Sun & Xiaobing Xiao & Yongjun Zhang & Yiyong Lei & Hao Yang & Zhuangzhuang Li, 2025. "A Load Restoration Approach Based on Symmetrical Demand Response Incentive Mechanism," Energies, MDPI, vol. 18(11), pages 1-19, May.
    2. 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).
    3. Nitesh Kumar Singh & Chaitali Koley & Sadhan Gope & Subhojit Dawn & Taha Selim Ustun, 2021. "An Economic Risk Analysis in Wind and Pumped Hydro Energy Storage Integrated Power System Using Meta-Heuristic Algorithm," Sustainability, MDPI, vol. 13(24), pages 1-19, December.
    4. Mao, Ding & Wang, Peng & Fang, Yi-Ping & Ni, Long, 2024. "Securing heat-supply against seismic risks: A two-staged framework for assessing vulnerability and economic impacts in district heating networks," Applied Energy, Elsevier, vol. 369(C).
    5. Lei, Xue & Xu, Xueguo, 2025. "Innovation in the storm: How typhoons are reshaping the corporate R&D landscape," Technology in Society, Elsevier, vol. 81(C).
    6. Fausto Pedro García Márquez, 2022. "Advanced Analytics in Renewable Energy," Energies, MDPI, vol. 15(10), pages 1-5, May.
    7. Lin, Yumian & Xiong, Houbo & Zhou, Yue & Wang, Tianjing & Lin, Yujie & Guo, Chuangxin, 2025. "Distributionally robust service restoration for integrated electricity-heating systems considering secondary strikes of subsequent random events," Applied Energy, Elsevier, vol. 380(C).
    8. Tai Zhang & Goran Strbac, 2025. "Novel Artificial Intelligence Applications in Energy: A Systematic Review," Energies, MDPI, vol. 18(14), pages 1-51, July.
    9. Zhaotong Song & Jianli Zhou & Cheng Yang & Shuxian Wu & Zhuohao Chen & Jiawen Sun & Yunna Wu, 2025. "“Photovoltaic +” Multi-Industry Integration for Sustainable Development in “Desert-Gobi-Wilderness” Region: Geospatial Suitability Simulation and Dynamic Site Selection Decision Optimization," Land, MDPI, vol. 14(7), pages 1-29, July.
    10. Yao, Qi & Tang, Jie & Ke, Yiming & Li, Li & Lu, Xiaoqin & Hu, Yang & Fang, Fang & Liu, Jizhen, 2024. "Anti-tropical cyclone load reduction control of wind turbines based on deep neural network yaw algorithm," Applied Energy, Elsevier, vol. 376(PB).
    11. Tian, Yuyu & Chang, Jianxia & Wang, Yimin & Wang, Xuebin & Zhao, Mingzhe & Meng, Xuejiao & Guo, Aijun, 2022. "A method of short-term risk and economic dispatch of the hydro-thermal-wind-PV hybrid system considering spinning reserve requirements," Applied Energy, Elsevier, vol. 328(C).
    12. Wenlu Ji & Lan Lan & Lu Shen & Dahang Shi & Chong Wang, 2025. "Dynamic Identification Method of Distribution Network Weak Links Considering Disaster Emergency Scheduling," Energies, MDPI, vol. 18(13), pages 1-23, July.
    13. Spyros Giannelos, 2025. "Reinforcement Learning in Energy Finance: A Comprehensive Review," Energies, MDPI, vol. 18(11), pages 1-41, May.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:jeners:v:18:y:2025:i:13:p:3394-:d:1689123. 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.