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- W4316660147 abstract "Regional power network reliability analysis is crucial for decision-making when nature hazard attacks. However, the data are scattered due to the sparse geospatially distributed power network components. Therefore, a data generation engine is needed to collect and process the data efficiently. Additionally, the scientific workflow specified to perform power network damage, and loss estimation under hurricane events is limited. This paper proposed a novel data generation engine and a scientific workflow for power network reliability analysis. The data generation engine contains three modules: the power infrastructure module, the hurricane module, and the structural analysis module. The logic and the usability of the proposed framework are validated through a benchmark problem." @default.
- W4316660147 created "2023-01-17" @default.
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- W4316660147 date "2022-10-09" @default.
- W4316660147 modified "2023-09-28" @default.
- W4316660147 title "A Data Generation Engine and Workflow for Power Network Damage and Loss Estimation under Hurricane" @default.
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- W4316660147 doi "https://doi.org/10.1109/naps56150.2022.10012230" @default.
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