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PCA-based preprocessing method of electronic data in Power Grid

机译:基于PCA的电网电子数据预处理方法

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摘要

The electronic data which are acquired respectively by SCADA (Supervisory Control and Data Acquisition) and WAMS (wide-area measurement system) have different structures and characters, therefore these two kinds of data could not be merged easily as well as used conveniently. This problem makes online analysis in SASOPG (Stabilization and Security of Power Grid) difficult. Aiming the problem, this paper proposes a PCA-based preprocessing method of electronic data in power grid. The method is based on a two-stage state estimation algorithm optimized by PCA. By using linearon-linear mixed state estimation algorithm, the origin data from SCADA/WAMS are transformed into state values. To accelerate the state estimation restrained rapidly, a data value optimized algorithm of principal component analysis is provided, and finally the basic message of online analysis is obtained. The result shows that the processing method merges the electronic data well, and it also has higher execution efficiency.
机译:分别由SCADA(监控和数据采集)和WAMS(广域测量系统)采集的电子数据具有不同的结构和特征,因此,这两种数据不易合并,使用起来也不方便。此问题使在SASOPG(电网的稳定和安全)中进行在线分析变得困难。针对这一问题,本文提出了一种基于PCA的电网电子数据预处理方法。该方法基于PCA优化的两阶段状态估计算法。通过使用线性/非线性混合状态估计算法,将来自SCADA / WAMS的原始数据转换为状态值。为加快状态估计的速度,提供了一种主成分分析的数据值优化算法,最终获得了在线分析的基本信息。结果表明,该处理方法很好地融合了电子数据,并且具有较高的执行效率。

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