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Analysis of catastrophic events using statistical outlier methods

机译:利用统计异常方法分析灾难性事件

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Use of IEEE Standard 1366–2003 for determining major events has provided substantial consistency when comparing year-on-year performance, however certain events (such as hurricanes or ice storms) that destroy substantial portions of a company's power system may result in extremely large daily SAIDI results which could skew the calculation of the major event threshold over the subsequent five years (according to the standard). This change in threshold could result in certain days in subsequent years not being considered as Major Events. The Catastrophic Event Task Force, convened under the Distribution Reliability Working Group, undertook substantial investigations to explore the impact of these events and the ability for an outlier method to be developed which transferred well across a variety of companies. This paper will explore an outlier identification method used by statisticians, notably the use of box and whiskers plots, to determine its application in segregating outlier data. It will also summarize the approaches considered and the final conclusions arrived at by the Catastrophic Event Task Force.
机译:使用IEEE标准1366-2003来确定主要事件在比较年度表现时提供了大量的一致性,但是某些事件(如飓风或冰暴),这些事件(如飓风或冰暴)摧毁了公司的电力系统的大量部分可能会导致每天极大大在随后的五年(根据标准的情况下,可能会歪斜主要事件阈值的结果。此阈值的变化可能导致随后几年不被视为重大事件的某些日子产生。在分销可靠性工作组下召开的灾难性事件工作队进行了大量的调查,探讨这些事件的影响以及开发的异常方法的能力,这些方法在各种公司中转移良好。本文将探讨统计学家使用的异常识别方法,特别是使用框和晶须图,以确定其在隔离异常数据中的应用。它还将总结这些方法,并通过灾难性事件特遣部队到达的最终结论。

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