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Analysis of catastrophic events using statistical outlier methods

机译:使用统计离群值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性能时提供了基本的一致性,但是某些破坏公司电力系统大部分的事件(例如飓风或冰暴)可能会导致每天的工作量过大SAIDI的结果可能会使随后五年(根据标准)的重大事件阈值的计算产生偏差。阈值的这种更改可能会导致以后年份中的某些日子不被视为重大事件。由分布可靠性工作组召集的灾难性事件工作组进行了实质性调查,以探讨这些事件的影响以及开发出一种异常方法的能力,该方法可以很好地在各种公司之间转移。本文将探讨统计学家使用的离群值识别方法,特别是使用箱形图和须状图,以确定其在分离离群值数据中的应用。还将总结灾难性事件工作组考虑的方法并得出最终结论。

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