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A reliability-based approach to identify critical components in a UHVDC converter station system against earthquakes

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  • Liang, Huangbin

Abstract

Earthquakes pose a huge threat to the power system in seismically active regions. Ultra-High Voltage Direct Current (UHVDC) converter stations become integral to modern power grids, especially for long-distance power transmission, and thus understanding and improving their seismic reliability is essential for ensuring the robustness of the power system. This paper presents a comprehensive reliability-based approach to identify critical components within UHVDC converter stations, focusing on seismic reliability. A seismic reliability index is defined as the expected post-earthquake transmission capacity loss, considering both the earthquake probability and the derated capacity under different operation modes. The converter system's seismic reliability model is established based on divide-and-group principles, dividing it into subsystems and deriving an equivalent logical model based on their interdependency. Failure probabilities of subsystems, consisting of wire-interconnected electrical equipment, are determined through finite element models and seismic vulnerability analysis, accounting for wire interaction forces. Advanced sensitivity analysis techniques such as the Morris method and Sobol's analysis identify critical components influencing seismic reliability. A case study on a real-world ±800 kV UHVDC converter station system demonstrates the effectiveness of the proposed approach in enhancing seismic reliability efficiently.

Suggested Citation

  • Liang, Huangbin, 2025. "A reliability-based approach to identify critical components in a UHVDC converter station system against earthquakes," Reliability Engineering and System Safety, Elsevier, vol. 260(C).
    • Handle: RePEc:eee:reensy:v:260:y:2025:i:c:s0951832025001802
    DOI: 10.1016/j.ress.2025.110977
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    References listed on IDEAS

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    1. Blagojević, Nikola & Didier, Max & Stojadinović, Božidar, 2022. "Quantifying component importance for disaster resilience of communities with interdependent civil infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    2. Xing Jiang & Chengjin Ye & Yi Ding & Ruipeng Guo, 2018. "Reliability Equivalence to Symmetrical UHVDC Transmission Systems Considering Redundant Structure Configuration," Energies, MDPI, vol. 11(4), pages 1-17, March.
    3. Volkanovski, Andrija & ÄŒepin, Marko & Mavko, Borut, 2009. "Application of the fault tree analysis for assessment of power system reliability," Reliability Engineering and System Safety, Elsevier, vol. 94(6), pages 1116-1127.
    4. Ge, Qiao & Menendez, Monica, 2017. "Extending Morris method for qualitative global sensitivity analysis of models with dependent inputs," Reliability Engineering and System Safety, Elsevier, vol. 162(C), pages 28-39.
    5. Ehre, Max & Papaioannou, Iason & Straub, Daniel, 2020. "Global sensitivity analysis in high dimensions with PLS-PCE," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    6. Alassi, Abdulrahman & Bañales, Santiago & Ellabban, Omar & Adam, Grain & MacIver, Callum, 2019. "HVDC Transmission: Technology Review, Market Trends and Future Outlook," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 530-554.
    7. Vuillod, Bruno & Montemurro, Marco & Panettieri, Enrico & Hallo, Ludovic, 2023. "A comparison between Sobol’s indices and Shapley’s effect for global sensitivity analysis of systems with independent input variables," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    8. Borgonovo, E., 2007. "A new uncertainty importance measure," Reliability Engineering and System Safety, Elsevier, vol. 92(6), pages 771-784.
    9. Shang, Xiaobing & Su, Li & Fang, Hai & Zeng, Bowen & Zhang, Zhi, 2023. "An efficient multi-fidelity Kriging surrogate model-based method for global sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    10. Liang, Huangbin & Xie, Qiang, 2025. "Probabilistic seismic risk analysis of electrical substations considering equipment-to-equipment seismic failure correlations," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
    11. Oboudi, Mohammad Hossein & Mohammadi, Mohammad, 2024. "Two-Stage Seismic Resilience Enhancement of Electrical Distribution Systems," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
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