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A fast method for identifying bad data of massive power network data

机译:一种快速识别海量电网数据不良数据的方法

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In this paper, we propose a new fast and bad data detection and identification technology and model as the research goal, to achieve fast and accurate and efficient data detection and identification. This paper analyzes the influence of single, multiple and multi-correlation bad data on the state estimation results in the actual power grid. Based on the characteristics of its influence and the research status of the bad data detection and identification methods at home and abroad, according to the characteristics of the bad data distribution, The object of the power grid rapid partition method, and further proposed two-layer fine bad data detection and identification model and rapid solution method.
机译:本文提出了一种新的快速和不良数据检测与识别技术和模型作为研究目标,以实现快速,准确,高效的数据检测与识别。本文分析了单,多和多相关不良数据对实际电网状态估计结果的影响。根据其不良影响的特点以及国内外不良数据检测与识别方法的研究现状,针对不良数据分布的特点,提出了电网快速划分对象的方法,并进一步提出了两层优良的不良数据检测识别模型和快速解决方法。

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