计算机应用与软件2024，Vol.41Issue(5)：101-106,6.DOI:10.3969/j.issn.1000-386x.2024.05.016
基于数据驱动的无监测用户用电模式识别方法
DATA-DRIVEN UNMONITORED USER ELECTRICITY CONSUMPTION PATTERN RECOGNITION METHOD
李凯 1杨大伟 1张建业 2马崇瑞 3李德高 2王慧3
作者信息
- 1. 国网新疆电力有限公司信息通信公司 新疆乌鲁木齐 830000
- 2. 国网新疆电力有限公司 新疆乌鲁木齐 830000
- 3. 北京中电普华信息技术有限公司 北京 100000
- 折叠
摘要
Abstract
Smart meters installed on the end user side can effectively analyze their abnormal power consumption behavior and power consumption patterns.To fill the user data missing that may exist in the transition period,a data-driven unmonitored user power pattern recognition method is proposed.We used the typical daily load curve historical data of users with smart meters to extract the typical power consumption patterns,and trained multi-time sale machine learning models to estimate the monthly consumption of users.The recursive Bayesian learning and branch current state estimation residual method were used to obtain the daily load curve from the monthly electricity bill of the unmonitored user.The simulation results on measurement data from actual systems show that the proposed method can identify the power consumption mode of unmonitored users quickly and accurately.关键词
用电模式识别/频谱聚类/递归贝叶斯学习Key words
Electricity consumption pattern recognition/Spectrum clustering/Recursive Bayes learning分类
信息技术与安全科学引用本文复制引用
李凯,杨大伟,张建业,马崇瑞,李德高,王慧..基于数据驱动的无监测用户用电模式识别方法[J].计算机应用与软件,2024,41(5):101-106,6.
