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Classification of Massive User Load Characteristics in Distribution Network Based on Agglomerative Hierarchical Algorithm

机译:基于聚集层次算法的配电网海量用户负荷特征分类

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In order to improve primary energy utilization, achieve economical operation of distribution network, comprehensively consider the concentration / compensation needs of various groups under typical load levels, and to gain understanding of characteristics of different types of user loads, the present paper proposes a hierarchical cluster algorithm to enhance the cohesion of a distribution feeder load characteristic clustering algorithm circumstances. This will serve to ultimately provide effective guidance for electricity energy conservation as well as to better realize peak load shifting. By cutting distribution network load time sequence data in longitudinal manner, relevant feature were extracted to achieve user load characteristics classification based on hierarchical clustering algorithm. Such classification will therefore assist to optimize distribution network scheduling. It is therefore an effective way to enhance accuracy and effectiveness of relevant power distribution decision-making.
机译:为了提高一次能源的利用率,实现配电网的经济运行,综合考虑典型负荷水平下各组的集中/补偿需求,并了解不同类型用户负荷的特征,提出了一种层次聚类该算法增强了配电网内聚力负荷特性聚类算法的环境。这将最终为电力节约提供有效的指导,并更好地实现峰值负载转移。通过纵向切割配电网负荷时间序列数据,提取相关特征,实现基于层次聚类算法的用户负荷特征分类。因此,这种分类将有助于优化配电网络调度。因此,这是提高相关配电决策的准确性和有效性的有效方法。

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