A multi-hazard approach to assess severe weather-induced major power outage risks in the US
A multi-hazard approach to assess severe weather-induced major power outage risks in the US
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DOI：
10.1016/j.ress.2018.03.015
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发表时间：
2018-07-01
影响因子：
8.1
通讯作者：
Hastak, Makarand
中科院分区：
文献类型：
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作者：
Mukherjee, Sayanti;Nateghi, Roshanak;Hastak, Makarand
恶劣天气引起的停电影响到数百万人，每年造成数十亿美元的经济损失。全国公用事业监管专员协会最近强调了建立电力部门弹性的重要性，从而提高服务安全性和长期经济效益。在本文中，我们提出了一个多灾害的方法来描述恶劣天气引起的持续停电的关键预测。我们开发了一个两阶段的混合风险估计模型，利用算法数据挖掘技术。我们使用公开的历史重大停电信息、社会经济数据、州级气候观测、电力消费模式和土地使用数据来训练我们的风险模型。我们的研究结果表明，停电风险是各种因素的函数，如自然灾害的类型，架空T&D系统的扩展，国家级农村与城市地区的范围，以及运营/维护活动的潜在投资水平（例如，修剪树木、更换旧设备等）。拟议的框架可以帮助州监管委员会做出风险知情的弹性投资决策。(C)2018爱思唯尔有限公司版权所有
Severe weather-induced power outages affect millions of people and cost billions of dollars of economic losses each year. The National Association of Regulatory Utility Commissioners have recently highlighted the importance of building electricity sector's resilience, and thereby enhancing service-security and long-term economic benefits. In this paper, we propose a multi-hazard approach to characterize the key predictors of severe weather induced sustained power outages. We developed a two-stage hybrid risk estimation model, leveraging algorithmic data-mining techniques. We trained our risk models using publicly available information on historical major power outages, socio-economic data, state-level climatological observations, electricity consumption patterns and land-use data. Our results suggest that power outage risk is a function of various factors such as the type of natural hazard, expanse of overhead T&D systems, the extent of state-level rural versus urban areas, and potentially the levels of investments in operations/maintenance activities (e.g., tree-trimming, replacing old equipment, etc.). The proposed framework can help state regulatory commissions make risk-informed resilience investment decisions. (C) 2018 Elsevier Ltd. All rights reserved.