IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v250y2024ics0951832024003739.html
   My bibliography  Save this article

Post-disaster repair optimization method for traction power supply system of electrified railways based on train operation loss

Author

Listed:
  • Sun, Xiaojun
  • Lin, Sheng
  • Feng, Ding
  • Zhang, Qiang

Abstract

The traction power supply system (TPSS) is the critical facility that provides power to electrified railways. However, TPSS is highly susceptible to extreme events. Therefore, it is essential to develop reasonable post-disaster repair strategies to mitigate losses. In this context, this paper proposes a post-disaster repair optimization method for TPSS based on train operation loss. The hazard characterization and equipment fragility analysis are introduced to simulate post-disaster fault scenarios of TPSSs. By analyzing the changes in component states during the repair process, the component state transition model based on the multi-stage decision process is established and the state transition relationship is derived. According to the component state and TPSS topology, the model for evaluating the power supply state of the traction network is constructed. On this basis, the indicator of train operation loss is defined, which is used as the objective to formulate the post-disaster repair optimization model of TPSSs. The case study using real-world high-speed railway data demonstrates that, compared to traditional repair strategies, the proposed method effectively reduces the restoration time of TPSS and significantly decreases train operation loss. This method can provide maintenance personnel with theoretical bases for formulating post-disaster repair strategies.

Suggested Citation

  • Sun, Xiaojun & Lin, Sheng & Feng, Ding & Zhang, Qiang, 2024. "Post-disaster repair optimization method for traction power supply system of electrified railways based on train operation loss," Reliability Engineering and System Safety, Elsevier, vol. 250(C).
    • Handle: RePEc:eee:reensy:v:250:y:2024:i:c:s0951832024003739
    DOI: 10.1016/j.ress.2024.110301
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832024003739
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2024.110301?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. Wang, Hongping & Fang, Yi-Ping & Zio, Enrico, 2022. "Resilience-oriented optimal post-disruption reconfiguration for coupled traffic-power systems," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    2. Liu, Wei & Song, Zhaoyang & Ouyang, Min & Li, Jie, 2020. "Recovery-based seismic resilience enhancement strategies of water distribution networks," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    3. Xu, Min & Li, Guoyuan & Chen, Anthony, 2024. "Resilience-driven post-disaster restoration of interdependent infrastructure systems under different decision-making environments," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    4. Wang, Jian & Gao, Shibin & Yu, Long & Liu, Xingyang & Neri, Ferrante & Zhang, Dongkai & Kou, Lei, 2024. "Uncertainty-aware trustworthy weather-driven failure risk predictor for overhead contact lines," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    5. Shi, Qingxin & Li, Fangxing & Dong, Jin & Olama, Mohammed & Wang, Xiaofei & Winstead, Chris & Kuruganti, Teja, 2022. "Co-optimization of repairs and dynamic network reconfiguration for improved distribution system resilience," Applied Energy, Elsevier, vol. 318(C).
    6. Wang, Jian & Gao, Shibin & Yu, Long & Ma, Chaoqun & Zhang, Dongkai & Kou, Lei, 2023. "A data-driven integrated framework for predictive probabilistic risk analytics of overhead contact lines based on dynamic Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    7. Zhang, Jintao & Bagtzoglou, Yiannis & Zhu, Jin & Li, Baikun & Zhang, Wei, 2023. "Fragility-based system performance assessment of critical power infrastructure," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    8. De Iuliis, Melissa & Kammouh, Omar & Cimellaro, Gian Paolo & Tesfamariam, Solomon, 2021. "Quantifying restoration time of power and telecommunication lifelines after earthquakes using Bayesian belief network model," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    9. Opabola, Eyitayo A. & Galasso, Carmine, 2024. "A probabilistic framework for post-disaster recovery modeling of buildings and electric power networks in developing countries," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    10. Xu, Sheng & Tu, Haicheng & Xia, Yongxiang, 2023. "Resilience enhancement of renewable cyber–physical power system against malware attacks," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    11. Sun, Xiaojun & Feng, Ding & Zhang, Qiang & Lin, Sheng, 2024. "Optimal siting of substations of traction power supply systems considering seismic risk," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    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. Tang, Daogui & Fang, Yi-Ping & Zio, Enrico, 2023. "Vulnerability analysis of demand-response with renewable energy integration in smart grids to cyber attacks and online detection methods," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    2. HIMOTO, Keisuke & SAWADA, Yuto & OHMIYA, Yoshifumi, 2024. "Quantifying fire resilience of buildings considering the impact of water damage accompanied by fire extinguishment," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    3. Amanda Melendez & David Caballero-Russi & Mariantonieta Gutierrez Soto & Luis Felipe Giraldo, 2022. "Computational models of community resilience," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(2), pages 1121-1152, March.
    4. Huang, Xiubing & Wang, Naiyu, 2024. "An adaptive nested dynamic downscaling strategy of wind-field for real-time risk forecast of power transmission systems during tropical cyclones," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    5. Hao, Yucheng & Jia, Limin & Zio, Enrico & Wang, Yanhui & Small, Michael & Li, Man, 2023. "Improving resilience of high-speed train by optimizing repair strategies," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    6. Liu, Juncai & Tian, Li & Yang, Meng & Meng, Xiangrui, 2024. "Probabilistic framework for seismic resilience assessment of transmission tower-line systems subjected to mainshock-aftershock sequences," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    7. Wang, Jian & Liu, Huiyuan & Gao, Shibin & Yu, Long & Liu, Xingyang & Zhang, Dongkai & Kou, Lei, 2024. "Robust deep Gaussian process-based trustworthy fog-haze-caused pollution flashover prediction approach for overhead contact lines," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    8. 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).
    9. Wang, Jian & Gao, Shibin & Yu, Long & Liu, Xingyang & Neri, Ferrante & Zhang, Dongkai & Kou, Lei, 2024. "Uncertainty-aware trustworthy weather-driven failure risk predictor for overhead contact lines," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    10. Li Long & Huaping Yang & Shansuo Zheng & Yonglong Cai, 2024. "Seismic Resilience Evaluation of Urban Multi-Age Water Distribution Systems Considering Soil Corrosive Environments," Sustainability, MDPI, vol. 16(12), pages 1-23, June.
    11. Li, Siran & Xiao, Fuyuan, 2023. "Normal distribution based on maximum Deng entropy," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    12. Xu, Min & Ouyang, Min & Hong, Liu & Mao, Zijun & Xu, Xiaolin, 2022. "Resilience-driven repair sequencing decision under uncertainty for critical infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    13. 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).
    14. Sonal, & Ghosh, Debomita, 2022. "Impact of situational awareness attributes for resilience assessment of active distribution networks using hybrid dynamic Bayesian multi criteria decision-making approach," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    15. Morshedi, Mohamad Ali & Kashani, Hamed, 2022. "Assessment of vulnerability reduction policies: Integration of economic and cognitive models of decision-making," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    16. Wang, Wei & He, Yufei & Wang, Hongbin & Chen, Hongzhou & Xiong, Xiaofu, 2024. "Improving interdependent urban power and gas distribution systems resilience through optimal scheduling of mobile emergency supply and repair resources," Reliability Engineering and System Safety, Elsevier, vol. 250(C).
    17. Yu, Yaocheng & Shuai, Bin & Huang, Wencheng, 2024. "Resilience evaluation of train control on-board system considering common cause failure: Based on a beta-factor and continuous-time bayesian network model," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
    18. Fadel Miguel, Leandro F. & Beck, André T., 2024. "Optimal path shape of friction-based Track-Nonlinear Energy Sinks to minimize lifecycle costs of buildings subjected to ground accelerations," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
    19. 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).
    20. Dui, Hongyan & Liu, Meng & Song, Jiaying & Wu, Shaomin, 2023. "Importance measure-based resilience management: Review, methodology and perspectives on maintenance," Reliability Engineering and System Safety, Elsevier, vol. 237(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:reensy:v:250:y:2024:i:c:s0951832024003739. 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: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    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.