A meticulous approach towards contingency clustering in power system

Jatin Verma, I. Sharieff, Ranjana Sodhi
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Abstract

Contingency analysis plays a key role in evaluating the performance of a system under stressed conditions. This paper proposes Trajectory Violation Integral (TVI) index as a measure to quantify the effect of contingency. Contingency clustering enables partitioning of the system into coherent and independent Voltage Control Areas. The data that is worked on during contingency clustering is of high dimensional nature and studies have shown that the algorithms that work on lower dimensional data may get impaired while handling higher dimensional data due to various reasons, one of them being the curse of dimensionality. This work emphasizes the problems associated while dealing with higher dimensional data and proposes a meticulous strategy to undermine the effects of higher dimensionality in the premises of contingency clustering for the formation of Dynamic Voltage Control Areas.
电力系统应急聚类的精细方法
应急分析在评估系统在应力条件下的性能方面起着关键作用。本文提出了轨迹违和积分(TVI)指标来量化偶然性的影响。偶然性聚类能够将系统划分为连贯和独立的电压控制区。偶然性聚类处理的数据是高维数据,研究表明,处理低维数据的算法在处理高维数据时可能由于各种原因而受到损害,其中一个原因就是维数的诅咒。这项工作强调了在处理高维数据时相关的问题,并提出了一种细致的策略来破坏高维数据对动态电压控制区形成的偶然性聚类的影响。
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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