基于调节潜力指标的用户用电行为聚类分析算法研究

Research on Clustering Analysis Algorithm Based on Adjustable Potential Index for User Power Consumption Behavior

针对柔性负荷不断接入背景下,用户参与电网调节潜力能力的持续提升,基于负荷用户的调节潜力大小对用户的用电行为进行聚类分析。在峰谷分时电价背景下,基于用户心理学原理构建基于峰谷分时电价的负荷转移率模型,以该模型为基础构建基于峰谷分时电价的用户调节潜力指标,并利用该指标对负荷用户的用电行为进行聚类分析,通过与传统基于日负荷曲线以及典型负荷特性指标的聚类算法进行结果对比,证明了该算法聚类结果的有效性与正确性,同时通过对大规模用户的用电行为进行聚类分析,证明基于调节潜力指标的聚类分析算法的聚类效果更佳。

Against the background of continuous access of flexible loads,the ability and potential of users to participate in power grid regulation continues to increase,and the user＇s power consumption behavior is clustered on the basis of the user＇s regulatory potential. On the basis of the peak-to-peak electricity price background,a load transfer rate model based on peak-to-peak time-of-use price is constructed on the basis of the principle of user psychology. On the basis of this model,a user-adjusted potential index based on peak-to-hour electricity price is constructed and used. The user＇s electricity consumption behavior is used for cluster analysis,and the results are compared with traditional clustering algorithms based on daily load curves and typical load characteristics,which proves the validity and correctness of the clustering results of the algorithm. At the same time,the clustering analysis of electricity users＇ electricity consumption behavior proves that the clustering algorithm based on the adjustment potential index has a better clustering effect.