A framework to estimate a long-term power shortage risk following large-scale earthquake and tsunami disasters
While power shortages during and after a natural disaster cause severe impacts on response and recovery activities, related modeling and data collection efforts have been limited. In particular, no methodology exists to analyze long-term power shortages such as those that occurred during the Great E...
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Veröffentlicht in: | PloS one 2023-03, Vol.18 (3), p.e0283686-e0283686 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | While power shortages during and after a natural disaster cause severe impacts on response and recovery activities, related modeling and data collection efforts have been limited. In particular, no methodology exists to analyze long-term power shortages such as those that occurred during the Great East Japan Earthquake. To visualize a risk of supply shortage during a disaster and assist the coherent recovery of supply and demand systems, this study proposes an integrated damage and recovery estimation framework including the power generator, trunk distribution systems (over 154 kV), and power demand system. This framework is unique because it thoroughly investigates the vulnerability and resilience characteristics of power systems as well as businesses as primary power consumers observed in past disasters in Japan. These characteristics are essentially modeled by statistical functions, and a simple power supply-demand matching algorism is implemented using these functions. As a result, the proposed framework reproduces the original power supply and demand status from the 2011 Great East Japan Earthquake in a relatively consistent manner. Using stochastic components of the statistical functions, the average supply margin is estimated to be 4.1%, but the worst-case scenario is a 5.6% shortfall relative to peak demand. Thus, by applying the framework, the study improves knowledge on potential risk by examining a particular past disaster; the findings are expected to enhance risk perception and supply and demand preparedness after a future large-scale earthquake and tsunami disaster. |
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ISSN: | 1932-6203 1932-6203 |
DOI: | 10.1371/journal.pone.0283686 |