Mukherjee Sayanti, Nateghi Roshanak, Hastak Makarand
Lyles School of Civil Engineering, Division of Construction Engineering and Management, and School of Industrial Engineering, Purdue University, West Lafayette, IN 47907, USA.
School of Industrial Engineering and Division of Environmental and Ecological Engineering, Purdue University, West Lafayette, IN 47907, USA.
Data Brief. 2018 Jun 26;19:2079-2083. doi: 10.1016/j.dib.2018.06.067. eCollection 2018 Aug.
This paper presents the data that is used in the article entitled "A Multi-Hazard Approach to Assess Severe Weather-Induced Major Power Outage Risks in the U.S." (Mukherjee et al., 2018) [1]. The data described in this article pertains to the major outages witnessed by different states in the continental U.S. during January 2000-July 2016. As defined by the Department of Energy, the major outages refer to those that impacted atleast 50,000 customers or caused an unplanned firm load loss of atleast 300 MW. Besides major outage data, this article also presents data on geographical location of the outages, date and time of the outages, regional climatic information, land-use characteristics, electricity consumption patterns and economic characteristics of the states affected by the outages. This dataset can be used to identify and analyze the historical trends and patterns of the major outages and identify and assess the risk predictors associated with sustained power outages in the continental U.S. as described in Mukherjee et al. [1].
本文展示了用于题为《一种多灾害方法评估美国严重天气引发的重大停电风险》（Mukherjee等人，2018年）[1]的文章中的数据。本文所述数据涉及2000年1月至2016年7月期间美国大陆不同州发生的重大停电情况。根据美国能源部的定义，重大停电是指那些影响至少50000名客户或导致至少300兆瓦计划外固定负荷损失的停电事件。除了重大停电数据外，本文还展示了停电地点的地理位置、停电日期和时间、区域气候信息、土地利用特征、电力消费模式以及受停电影响各州的经济特征等数据。如Mukherjee等人[1]所述，该数据集可用于识别和分析重大停电的历史趋势和模式，并识别和评估与美国大陆持续停电相关的风险预测因素。
