摘要
Performing analytics on the load curve(LC)of customers is the foundation for demand response which requires a better understanding of customers'consumption pattern(CP)by analyzing the load curve.However,the performances of previous widely-used LC clustering methods are poor in two folds:larger number of clusters,huge variances within a cluster(a CP is extracted from a cluster),bringing huge difficulty to understand the electricity consumption pattern of customers.In this paper,to improve the performance of LC clustering,a clustering framework incorporated with community detection is proposed.The framework includes three parts:network construction,community detection,and CP extraction.According to the cluster validity index(CVI),the integrated approach outperforms the previous state-of-the-art method with the same amount of clusters.And the approach needs fewer clusters to achieve the same performance measured by CVI.
作者
黄运有
Wang Nana
Hao Tianshu
Guo Xiaoxu
Luo Chunjie
Wang Lei
Ren Rui
Zhan Jianfeng
Huang Yunyou;Wang Nana;Hao Tianshu;Guo Xiaoxu;Luo Chunjie;Wang Lei;Ren Rui;Zhan Jianfeng(School of Computer Science and Information Technology,Guangxi Normal University,Guilin 541004,P.R.China;Institute of Computing Technology,Chinese Academy of Sciences,Beijing 100190,P.R.China;University of Chinese Academy of Sciences,Beijing 100049,P.R.China)
基金
Supported by the Major Program of National Natural Science Foundation of China(No.61432006)。