重庆大学学报2025，Vol.48Issue(9)：1-11,11.DOI:10.11835/j.issn.1000-582X.2024.214
计及非负和低秩特性的用电数据缺失值插补
Complete electricity data reconstruction based on weighted nonnegative matrix factorization
摘要
Abstract
With the widespread deployment of smart meters,power grids have accumulated vast amounts of raw electricity consumption data.However,data loss remains a challenge due to the complex operational environments of data acquisition equipment.This study addresses the problem of incomplete electricity consumption data by accounting for the influence of Gaussian noise and proposing a robust completion method.First,a electricity consumption data matrix is constructed by reorganizing the sequences of individual users,and the ideal electricity data matrix is approximated using nonnegative matrix factorization(NMF).Second,both the Frobenius norm and the nuclear norm are employed to regularize the Gaussian noise and promote low-rank characteristics of the ideal matrix,thereby formulating an optimization model.Finally,within a block coordinate descent framework,the EM algorithm and a direct updating method are applied alternately to update the matrix factors derived from NMF,enabling accurate and complete data reconstruction.Simulation and experimental results validate the proposed algorithm's effectiveness and accuracy.关键词
用电数据/非负矩阵分解/范数/块坐标下降法/矩阵完备Key words
electricity consumption data/nonnegative matrix factorization/norm/block coordinate descent/matrix completion分类
交通工程引用本文复制引用
钟尧,刘清蝉,李昕泓,林聪,李腾斌,杨超,付志红..计及非负和低秩特性的用电数据缺失值插补[J].重庆大学学报,2025,48(9):1-11,11.基金项目
云南电网科技资助项目(YNKJXM20210147).Supproted by Yunnan Power Grid Technology Project(YNKJXM20210147). （YNKJXM20210147）
