停电数据通知弹性评估框架

Michael Abdelmalak, Sean Ericson, Jordan Cox, Mohammed Ben-Idris, E. Hotchkiss
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引用次数: 0

摘要

在过去十年中,由于破坏性事件对电力系统造成的灾难性影响显着增加。这些事件突出表明,需要制定方法来评估电力系统对极端事件的抵御能力。然而,在中断事件期间和之后,捕捉电力系统性能的数据的可用性是稀缺的。本文提出了一个评估框架,利用地理定位能源信息分析环境(EAGLE-I)数据来评估极端停电事件期间电网系统的性能方面。EAGLE-I包括与美国受影响客户数量、持续时间和停电地点相关的信息。通过统计分析提取基于弹性的停电数据,并推导其影响和恢复特征的概率分布函数。根据几个预先确定的阈值来确定一系列极端事件。来自其他停电评估的指标用于测量每个事件的特征,包括影响率和持续时间、恢复速度和持续时间以及影响水平。得到每个度量的概率分布函数。所得结果提供了极端事件下国家电网性能的表征,可作为评估各种弹性增强技术的框架。
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A Power Outage Data Informed Resilience Assessment Framework
Catastrophic impacts to power systems due to disruptive events have increased significantly during the last decade. These events highlight the need to develop approaches to assess the resilience of power systems against extreme events. However, the availability of data that capture power system performance during and after disruptive events is scarce. This paper proposes an assessment framework to evaluate the performance aspects of the grid system during extreme outage events using the Environment for Analysis of Geo-Located Energy Information (EAGLE-I) data. EAGLE-I includes information related to the number of impacted customers, duration, and location of power outages in the United States. Statistical analyses were conducted to extract resilient-based outage data and derive probability distribution functions of their impact and recovery characteristics. A list of extreme events is identified based on few predetermined threshold values. Metrics from other power outage assessments were used to measure the characteristics of each event, including impact rate and duration, recovery rate and duration, and impact level. A probability distribution function is obtained for each metric. The obtained results provide a representation of national grid performance during extreme events, which can be applied as a framework to evaluate various resilience enhancement techniques.
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