Large-scale data analysis of power grid resilience across multiple US service regions
Large-scale data analysis of power grid resilience across multiple US service regions
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DOI：
10.1038/nenergy.2016.52
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发表时间：
2016-04-29
期刊：
影响因子：
56.7
通讯作者：
Wilcox, Robert
中科院分区：
文献类型：
--
作者：
Ji, Chuanyi;Wei, Yun;Wilcox, Robert
恶劣天气事件经常导致大规模停电，影响数百万人的时间更长。然而，缺乏全面、详细的故障和恢复数据阻碍了大规模的复原力研究。在这里，我们分析了超级风暴桑迪期间代表纽约州北部的四个主要服务地区的数据和日常运营。使用将基础设施故障与恢复和成本相关联的非平稳时空随机过程，我们的数据分析表明，本地电力故障对人们的非本地影响非常大(即，前20%的故障中断了84%的客户服务)。大量(89%)的小故障(以最底层的34%的客户和常见设备为代表)导致了2800万个客户中断小时总成本的56%。我们的研究表明，极端天气不会导致，反而会加剧现有的漏洞，这些漏洞在日常操作中被掩盖了。
Severe weather events frequently result in large-scale power failures, affecting millions of people for extended durations. However, the lack of comprehensive, detailed failure and recovery data has impeded large-scale resilience studies. Here, we analyse data from four major service regions representing Upstate New York during Super Storm Sandy and daily operations. Using non-stationary spatiotemporal random processes that relate infrastructural failures to recoveries and cost, our data analysis shows that local power failures have a disproportionally large non-local impact on people (that is, the top 20% of failures interrupted 84% of services to customers). A large number (89%) of small failures, represented by the bottom 34% of customers and commonplace devices, resulted in 56% of the total cost of 28 million customer interruption hours. Our study shows that extreme weather does not cause, but rather exacerbates, existing vulnerabilities, which are obscured in daily operations.