Simonoff Jeffrey S, Restrepo Carlos E, Zimmerman Rae
Leonard N. Stern School of Business, New York University, New York, NY, USA.
Risk Anal. 2007 Jun;27(3):547-70. doi: 10.1111/j.1539-6924.2007.00905.x.
Incident data about disruptions to the electric power grid provide useful information that can be used as inputs into risk management policies in the energy sector for disruptions from a variety of origins, including terrorist attacks. This article uses data from the Disturbance Analysis Working Group (DAWG) database, which is maintained by the North American Electric Reliability Council (NERC), to look at incidents over time in the United States and Canada for the period 1990-2004. Negative binomial regression, logistic regression, and weighted least squares regression are used to gain a better understanding of how these disturbances varied over time and by season during this period, and to analyze how characteristics such as number of customers lost and outage duration are related to different characteristics of the outages. The results of the models can be used as inputs to construct various scenarios to estimate potential outcomes of electric power outages, encompassing the risks, consequences, and costs of such outages.
关于电网中断的事件数据提供了有用信息，这些信息可用作能源部门风险管理政策的输入，以应对包括恐怖袭击在内的各种来源的中断。本文使用由北美电力可靠性委员会（NERC）维护的干扰分析工作组（DAWG）数据库中的数据，来研究1990年至2004年期间美国和加拿大随时间推移发生的事件。使用负二项回归、逻辑回归和加权最小二乘回归，以便更好地了解在此期间这些干扰如何随时间和季节变化，并分析诸如失去的客户数量和停电持续时间等特征与停电的不同特征之间的关系。模型结果可用作构建各种情景的输入，以估计停电的潜在结果，包括此类停电的风险、后果和成本。
