Estimating the spatial distribution of power outages during hurricanes in the Gulf coast region

被引:131
作者
Han, Seung-Ryong [2 ]
Guikema, Seth D. [1 ]
Quiring, Steven M. [3 ]
Lee, Kyung-Ho [4 ]
Rosowsky, David
Davidson, Rachel A. [5 ]
机构
[1] Johns Hopkins Univ, Dept Geog & Environm Engn, Baltimore, MD 21218 USA
[2] Texas A&M Univ, Zachry Dept Civil Engn, College Stn, TX USA
[3] Texas A&M Univ, Dept Geog, College Stn, TX USA
[4] Energo Engn, Houston, TX USA
[5] Univ Delaware, Dept Civil & Environm Engn, Newark, DE USA
关键词
Power distribution system reliability; Hurricane; Generalized linear model (GLM); Regression modeling; Overdispersion; Principal components analysis; Power outage; STANDARDIZED PRECIPITATION INDEX; 20TH-CENTURY DROUGHT; MODEL; REGRESSION; SIMULATION;
D O I
10.1016/j.ress.2008.02.018
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Hurricanes have caused severe damage to the electric power system throughout the Gulf coast region of the US, and electric power is critical to post-hurricane disaster response as well as to long-term recovery for impacted areas. Managing power outage risk and preparing for post-storm recovery efforts requires accurate methods for estimating the number and location of power outages. This paper builds on past work on statistical power outage estimation models to develop, test, and demonstrate a statistical power outage risk estimation model for the Gulf Coast region of the US. Previous work used binary hurricane-indicator variables representing particular hurricanes in order to achieve a good fit to the past data. To use these models for predicting power outages during future hurricanes, one must implicitly assume that an approaching hurricane is similar to the average of the past hurricanes. The model developed in this paper replaces these indicator variables with physically measurable variables, enabling future predictions to be based on only well-understood characteristics of hurricanes. The models were developed using data about power outages during nine hurricanes in three states served by a large, investor-owned utility company in the Gulf Coast region. (C) 2008 Elsevier Ltd. All rights reserved
引用
收藏
页码:199 / 210
页数:12
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