Research on Line Loss of Low-Voltage Substation Based on Smart Electric Meter Clustering Algorithm

Yan Fuli, Hou Xingzhe
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Abstract

At present, electric power company judgment on abnormal line loss is that the line loss is abnormal when the line loss rate exceeds a certain threshold. Yet the judgement is one-sidedness and limited.Aiming at the large proportion of low-voltage distribution network loss in the total loss of power grid, this paper introduces the line loss analysis process, constructs the line loss analysis model based on smart electric meter the four dimensional eigenvalues of daily average line loss rate, line loss rate variation coefficient, three-phase imbalance, power factor abnormality, and puts forward a method of identifying line loss abnormality in low-voltage distribution network based on clustering algorithm. The experimental results show that the method has certain practical application effects, which can accurately analyze the line loss rate and improve the accuracy of line loss anomaly judgment. Keywords-Component; Line Loss Rate; Loss Abnormal; Low-Voltage Distribution Network; Clustering Algorithm
基于智能电表聚类算法的低压变电站线损研究
目前,电力公司对线损异常的判断是线损率超过一定阈值即为线损异常。然而,这种判断是片面和有限的。针对低压配电网损耗在电网总损耗中所占比例较大的问题,介绍了线损分析过程,构建了基于智能电表的线损分析模型,包括日平均线损率、线损率变异系数、三相不平衡、功率因数异常、提出了一种基于聚类算法的低压配电网线损异常识别方法。实验结果表明,该方法具有一定的实际应用效果,能够准确地分析线损率,提高线损异常判断的准确性。Keywords-Component;线损率;损失异常;低压配电网;聚类算法
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