电力建设2025，Vol.46Issue(9)：120-129,10.DOI:10.12204/j.issn.1000-7229.2025.09.010
基于功率序列相空间拓扑特征的负荷识别
Non-Intrusive Load Monitoring based on Topology Feature of Phase Space Corresponding to Power Series
摘要
Abstract
[Objective]Non-intrusive load monitoring(NILM)has been adopted extensively in practical applications owing to its significant advantages such as low cost and ease of implementation.Although many NILM methods based on deep learning are currently available,they are limited in terms of interpretability and stability.This study proposes a novel NILM method based on power topology features using topological-data analysis.[Methods]First,the phase space of power time-series data is reconstructed,thus transforming the original load power data into a point-cloud dataset with geometric characteristics.Second,based on topological-data-analysis theory,a series of topological geometric features reflecting load characteristics is extracted from the obtained point cloud data,including key feature quantities such as the persistence amplitude,the persistence entropy,and Betti numbers.[Results]Finally,a load-identification model is constructed by combining the topological feature set with an XGBoost machine-learning classifier.Experimental results show that,on the PLAID public dataset,the load-identification accuracy of this method reaches 93%,with a processing time of 98 s.Compared with existing methods,the proposed method not only excels in identification speed but also achieves significant improvements in the identification accuracy of complex appliances.Notably,the identification accuracy of this method for refrigerators and washing machines,which are two types of complex loads,improves by 3%to 10%,respectively.Therefore,this method can be regarded as a new NILM approach that combines computational efficiency,identification accuracy,and model interpretability,thus rendering it worthy of further investigation.[Conclusions]The features extracted using this method present clear mathematical significance,which renders it conducive to mechanistic studies pertaining to load properties.Furthermore,it is a new NILM method that offers computational efficiency,recognition accuracy,and model interpretability;thus,it demonstrates wide application prospects and serves as a useful reference for subsequent related studies.关键词
有功功率/拓扑特征分析/相空间重构/非侵入式负荷监测(NILM)Key words
active power/topological data analysis/phase space reconstruction/non-intrusive load monitoring(NILM)分类
信息技术与安全科学引用本文复制引用
杨国朝,焦龙,韩阳,张军,杨光,代岩,刘博..基于功率序列相空间拓扑特征的负荷识别[J].电力建设,2025,46(9):120-129,10.基金项目
国网天津电力公司科技项目(城东-研发2023-03) （城东-研发2023-03）
