Post-earthquake rapid assessment of interconnected electrical equipment based on hybrid modelling
Beatriz Moya, Huangbin Liang, Francisco Chinesta, Eleni Chatzi
Abstract. Electrical substations play an indispensable role in the power grid for adjusting power voltage and controlling power flow, ensuring normal power transmission and distribution. However, substation equipment is particularly vulnerable to seismic events due to the use of brittle porcelain materials and highly slender structures, increasing the risk of structural failure and cascading effects. While significant research has focused on seismic performance and innovative damping techniques for different standalone equipment, critical gaps remain, particularly in accounting for the interconnected nature of substation equipment and post-earthquake emergency response. This study addresses these gaps by proposing a hybrid post-earthquake rapid assessment model that utilizes monitored ground motion signals. Hybrid modeling combines physics-based models with data-driven approaches, leveraging the strengths of both to overcome their individual limitations. Specifically, the study integrates Graph Neural Networks (GNN) with mechanistic models of standalone equipment to capture the dynamic behavior and interaction forces of interconnected equipment under seismic loads. The spatial relationships of the interconnected equipment are represented through a graph structure, and temporal dependencies are learned through recurrent computations. Thus, this approach circumvents the need for costly and impractical sensor installations on every piece of equipment, offering a cost-effective and accurate assessment method. The efficacy of the proposed hybrid modelling technique is demonstrated with a case study on combinations of 800 kV post insulators interconnected by busbars. By providing a rapid assessment of each equipment’s post-earthquake condition, the proposed model can be applied to inform emergency repair actions and enhance the resilience of power infrastructure.
Keywords
Hybrid Modelling, Rapid Assessment, Interconnected Equipment, Reduced Order Model, Graph Neural Network
Published online 3/25/2025, 9 pages
Copyright © 2025 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA
Citation: Beatriz Moya, Huangbin Liang, Francisco Chinesta, Eleni Chatzi, Post-earthquake rapid assessment of interconnected electrical equipment based on hybrid modelling, Materials Research Proceedings, Vol. 50, pp 52-60, 2025
DOI: https://doi.org/10.21741/9781644903513-6
The article was published as article 6 of the book Structural Health Monitoring
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
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