Forecasting hurricane-induced power outage durations

被引:83
|
作者
Nateghi, Roshanak [1 ,2 ]
Guikema, Seth D. [1 ]
Quiring, Steven M. [3 ]
机构
[1] Johns Hopkins Univ, Baltimore, MD 21218 USA
[2] Resources Future Inc, Washington, DC 20036 USA
[3] Texas A&M Univ, College Stn, TX 77843 USA
基金
美国国家科学基金会;
关键词
Data mining; Hurricanes; Power outages; Random forests; Power restoration; SYSTEMS;
D O I
10.1007/s11069-014-1270-9
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Accurate estimates of the duration of power outages caused by hurricanes prior to landfall are valuable for utility companies and government agencies that wish to plan and optimize their restoration efforts. Accurate pre-storm estimates are also important information for customers and operators of other infrastructures systems, who rely heavily on electricity. Traditionally, utilities make restoration plans based on managerial judgment and experience. However, skillful outage forecast models are conducive to improved decision-making practices by utilities and can greatly enhance storm preparation and restoration management procedures of power companies and emergency managers. This paper presents a novel statistical approach for estimating power outage durations that is 87 % more accurate than existing models in the literature. The power outage duration models are developed and carefully validated for outages caused by Hurricanes Dennis, Katrina, and Ivan in a central Gulf Coast state. This paper identifies the key variables in predicting hurricane-induced outage durations and their degree of influence on predicting outage restoration for the utility company service area used as our case study.
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页码:1795 / 1811
页数:17
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