摘要
首先分析、整合了用户电量数据,然后对用户用电框架进行分析整理,并基于云计算的聚类算法对用户用电数据进行智能研究,得出了用户用电分类的特征选择以及权重计算。然后基于分类特征进行了非介入式用电负荷分解与识别研究,从分解与识别原理着手设计了模型,从模型出发分析了模拟结果,证明基于云计算的聚类算法的用户用电行为分析模型是行之有效的。
This article first analysis,the integration of the user data,then analyze the power framework,and the clustering algorithm based on cloud computing intelligence research data of the power,it is concluded that the user electricity classification feature selection and weight calculation. Then based on the classification of features on the involvement of electricity load decomposition and identify research,from the decomposition and identification principle to design the model,starting from the model simulation results are analyzed,prove the clustering algorithm based on cloud computing power behavior analysis model is effective.
出处
《自动化与仪器仪表》
2016年第2期187-189,共3页
Automation & Instrumentation
关键词
用户用电行为
云计算
聚类算法
用电负荷分解
Power use behavior
Cloud computing
Clustering algorithm
Power load decomposition