Suppr超能文献

对热浪和复合天气事件对停电影响的多年分析。

A multi-year analysis of the impact of heatwaves and compound weather events on power outages.

作者信息

Saki Shah, Sofia Giulia, Kar Bandana, Anagnostou Emmanouil

机构信息

School of Civil and Environmental Engineering, University of Connecticut, 261 Glenbrook Road Unit, 3037, Storrs, CT, 06269- 3037, USA.

National Renewable Energy Laboratory, 15013 Denver W Pkwy, Golden, CO, 80401, USA.

出版信息

Sci Rep. 2025 Aug 22;15(1):30846. doi: 10.1038/s41598-025-15065-x.

Abstract

Across the United States, power grids are increasingly under strain from extreme weather events, such as heatwaves, high winds, and heavy precipitation, that result in frequent, long-duration and widespread power outages. The strain is intensified when these events are compounded, which amplifies their impact and exacerbates the risk of disruptions. To identify weather variables driving outages and cluster regions based on these variables, we employed a self-organizing map (SOM) approach using county-level outage data from 2015 to 2022, obtained using the U.S. Department of Energy's EAGLE-I platform, and weather data from the ASOS weather station observations. The findings revealed substantial regional differences in outages resulting from variability in heat, wind, and precipitation. In California, for example, high heat coupled with strong wind gusts led to the most severe outages, while in Texas, the primary contributors were high heat followed by heavy precipitation. This research provides a nuanced understanding of weather-induced power outages, offering a data-driven approach for infrastructure planning and resilience efforts. This study underscores the crucial role of continental weather variability in shaping outage patterns and highlights the necessity for region-specific adaptation strategies to enhance grid resilience, considering the rise in heatwaves and compounding weather events.

摘要

在美国,电网正日益受到极端天气事件的影响,如热浪、大风和强降水,这些导致了频繁、长时间和大面积的停电。当这些事件叠加时,压力会加剧,从而放大其影响并增加中断风险。为了识别导致停电的天气变量并根据这些变量对区域进行聚类,我们采用了自组织映射(SOM)方法,使用了2015年至2022年的县级停电数据(通过美国能源部的EAGLE - I平台获取)以及来自自动气象站(ASOS)观测的天气数据。研究结果表明,由于热量、风和降水的变化,停电情况存在显著的区域差异。例如,在加利福尼亚州,高温加上强风阵风导致了最严重的停电,而在得克萨斯州,主要因素是高温,其次是强降水。这项研究提供了对天气引发的停电情况的细致理解,为基础设施规划和恢复力建设努力提供了一种数据驱动的方法。这项研究强调了大陆天气变化在塑造停电模式中的关键作用,并突出了考虑到热浪增加和天气事件叠加的情况,制定针对特定区域的适应策略以增强电网恢复力的必要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da3a/12373919/e88302e8ae47/41598_2025_15065_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验