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An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Modeling the power system resilience in China under different natural disasters
Hao Chen1, Kai Gong2, Yunhao Chang2
1School of Applied Economics, Renmin University of China, Beijing, 100872, China; Department of Chemistry, Renmin University of China, Beijing, 100872, China.
Abstract:
A good understanding of the power system resilience is necessary for optimizing the investment strategies and supporting the emergency rescue, but the existing quantitative estimation results based on real outage events are still lacked due to the data limitations. Therefore, this study first establishes a unified framework to measure the power system resilience under different natural disasters, by integrating the electricity performance curve with the dynamic inoperability input-output model. Then, a database of 285 Chinese historical big power outage events caused by natural disasters is established, and the city-level power system resilience values are estimated. Finally, a benefit analysis is conducted for improving the power system resilience. Our major findings are that: (1) Electricity system recoveries quickest from hail (23.05 h), while restores slowest from snowstorm (117.31 h). (2) China's city electricity system is the most resilient to the thunderstorm, while is the least resilient to the earthquake. (3) Enhancing the power system resilience will significantly reduce the requirements for rescue resources, and the saved emergency rescue cost ranges from 0.57 million yuan to 12.08 million yuan with 1% reduction of initial inoperability.
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