Resilience of Energy Infrastructure and Services: Modeling, Data Analytics, and Metrics
Resilience of Energy Infrastructure and Services: Modeling, Data Analytics, and Metrics
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DOI：
10.1109/jproc.2017.2698262
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发表时间：
2016-11
影响因子：
20.6
通讯作者：
C. Ji;Yun Wei;H. Poor
中科院分区：
文献类型：
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作者：
C. Ji;Yun Wei;H. Poor
近年来，由恶劣天气引起的大规模停电变得频繁和具有破坏性，导致数百万人数日无电可用。尽管电力行业多年来一直在与天气引起的故障作斗争，但能源基础设施和服务对严重天气中断的适应能力在很大程度上尚不清楚。哪些基本问题制约着复原力？建模和数据分析等先进方法能否帮助行业超越经验方法？本文讨论了迄今为止的研究和开放的问题，这些问题。重点是确定基本挑战和量化复原力的先进方法。特别是，这个问题的第一个方面是如何建模大规模的故障，恢复和影响，涉及基础设施，服务提供商，客户和天气。第二个方面是如何通过大规模数据分析来识别基础设施和服务中的通用漏洞。第三个方面是了解需要哪些弹性指标以及如何制定这些指标。
Large-scale power failures induced by severe weather have become frequent and damaging in recent years, causing millions of people to be without electricity service for days. Although the power industry has been battling weather-induced failures for years, it is largely unknown how resilient the energy infrastructure and services really are to severe weather disruptions. What fundamental issues govern the resilience? Can advanced approaches such as modeling and data analytics help industry to go beyond empirical methods? This paper discusses the research to date and open issues related to these questions. The focus is on identifying fundamental challenges and advanced approaches for quantifying resilience. In particular, the first aspect of this problem is how to model large-scale failures, recoveries, and impacts, involving the infrastructure, service providers, customers, and weather. The second aspect is how to identify generic vulnerability in the infrastructure and services through large-scale data analytics. The third aspect is to understand what resilience metrics are needed and how to develop them.