Understanding the Computing and Analysis Needs for Resiliency of Power Systems from Severe Weather Impacts

J. Sanyal, M. Dumas, Sangkeun Lee, S. Chinthavali, J. King, Srijib Mukherjee
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Abstract

As the frequency and intensity of severe weather has increased, its effect on the electric grid has manifested in the form of significantly more and larger outages in the United States. This has become especially true for regions that were previously isolated from weather extremes. In this paper, we analyze the weather impacts on the electric power grid across a variety of weather conditions, draw correlations, and provide practical insights into the operational state of these systems. High resolution computational modeling of specific meteorological variables, computational approaches to solving power system models under these conditions, and the types of resiliency needs are highlighted as goal-oriented computing approaches are being built to address grid resiliency needs. An example analysis correlating outages to 1km day-ahead weather from two historical winter storms, calculated on a large cluster using a combination of interpolated and extrapolated inputs from multiple instrumented sites to workflows that produce primary meteorological outputs, is shown as initial proof of concept.
了解电力系统在恶劣天气影响下的弹性计算和分析需求
随着恶劣天气的频率和强度的增加,其对电网的影响表现为在美国出现更多更大规模的停电。对于那些以前不受极端天气影响的地区来说,情况尤其如此。在本文中,我们分析了各种天气条件下天气对电网的影响,绘制了相关性,并为这些系统的运行状态提供了实用的见解。特定气象变量的高分辨率计算建模,在这些条件下解决电力系统模型的计算方法,以及弹性需求的类型被强调为目标导向的计算方法正在建立,以解决电网的弹性需求。将两次历史冬季风暴导致的1公里前天气的中断联系起来的示例分析,在一个大型集群上计算,使用来自多个仪器站点的内插和外推输入的组合,以产生主要气象输出的工作流,显示为概念的初步证明。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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