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Clustering algorithm of power load curves in distribution network based on analysis of matrix characteristic roots

机译:基于矩阵特征根分析的配电网电力负荷曲线聚类算法

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In order to solve the problem of determining the clustering number of power load curves, this paper presented a clustering method based on the analysis of matrix characteristic roots. The clustering number is determined by the analysis result and the method is applied to the power load curves clustering. Firstly, the unified mathematical expression of the same type of load curves is established based on the changing pattern of load curves. Then, the equivalent relation between the clustering number of load curves and the number of larger characteristic roots is demonstrated. Besides, two criterions are presented to calculate the number of larger characteristic roots; and the number is the clustering number. After that, the load matrix is standardized and clustered by K-means algorithm. At last, the clustering result is evaluated by two indexes, the distance within classes and the distance between classes; and case simulation is given to prove the effectiveness and reasonability of the method proposed.
机译:为了解决确定电力负荷曲线聚类数的问题,提出了一种基于矩阵特征根分析的聚类方法。通过分析结果确定聚类数,并将该方法应用于电力负荷曲线聚类。首先,根据负荷曲线的变化规律,建立了相同类型负荷曲线的统一数学表达式。然后,证明了负荷曲线的聚类数量与较大特征根数量之间的等效关系。此外,提出了两个准则来计算较大特征根的数量。该数字是聚类数。之后,通过K-means算法对负载矩阵进行标准化和聚类。最后,通过类内距离和类间距离两个指标对聚类结果进行评估。并通过实例仿真证明了该方法的有效性和合理性。

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