电力系统自动化2016，Vol.40Issue(12)：21-27,7.DOI:10.7500/AEPS20160316007
面向海量用户用电特性感知的分布式聚类算法
Distributed Clustering Algorithm for Awareness of Electricity Consumption Characteristics of Massive Consumers
摘要
Abstract
The popularity of smart meters promotes the development of big data in smart power distribution and consumption systems.Data mining for smart meter data and awareness of electricity consumption characteristics are of great significance for consumption patterns recognition,demand response potential evaluation,and electricity price design.However,on one hand, the volume of smart meter data will grow dramatically with higher data collection frequency;on the other hand,the collected smart meter data has strong dispersion.To tackle the challenges brought by the massive and distributed smart meter big data, a novel distributed clustering algorithm is proposed.Firstly,the adaptive k-means algorithm is applied to each local data center so the typical load profiles can be extracted and the local model can be built.Then slightly revised traditional clustering algorithms are applied to the local models for secondary clustering analysis,thus the global model is built.Finally,the effectiveness of the proposed algorithm is verified by an actual example from Ireland.关键词
分布式聚类/自适应k-means/聚类算法/大数据/负荷曲线/态势感知Key words
distributed clustering/adaptive k-means/clustering algorithm/big data/load profiling/situation awareness引用本文复制引用
朱文俊,王毅,罗敏,林国营,程将南,康重庆..面向海量用户用电特性感知的分布式聚类算法[J].电力系统自动化,2016,40(12):21-27,7.基金项目
国家杰出青年基金资助项目(51325702) （51325702）
中国南方电网有限责任公司科技项目(GD-KJXM-20150902)。@@@@This work is supported by National Science Fund for Distinguished Young Scholars(No.51325702)and China Southern Power Grid Company Limited(No.GD-KJXM-20150902) （GD-KJXM-20150902）
