中国电机工程学报2024，Vol.44Issue(9)：3489-3499,中插12,12.DOI:10.13334/j.0258-8013.pcsee.222436
基于在线特征库的非侵入式负荷特征提取方法
Non-intrusive Load Feature Extraction Method Based on Online Feature Library
摘要
Abstract
Load characteristics refer to the special identification of certain statistical laws during the operation of load equipment.The database containing load characteristics is the basic basis for non-intrusive load monitoring and decomposition.For pure resistive load equipment,researchers can accurately extract the load characteristics in the corresponding state by using the characteristics of the power variation during the switching process of its operating states.However,for non-pure resistive devices,the load feature extraction has the following two problems.Problem 1:The power variation is not significant during the switching of the operating states,which results in difficulty in accurately locating the switching point of the state.Problem 2:The load equipment has an operating state in which the power varies slowly,resulting in the consequence that the load characteristics in the corresponding state is not unique,which cannot be manually extracted.Regarding the above problems,this paper proposed a non-intrusive load feature extraction method based on an online feature library.The operation process of the method was divided into two stages.Stage 1:Establish an online feature library based on the steady-state periodic current array during the operation of the load equipment.The sliding window function was constructed by improving Pearson similarity coefficient to calculate the similarity between the periodic current array and the online feature library when the load equipment is running,and synchronously judge the redundancy of the online feature library to achieve the load equipment status data segmentation.Stage 2:Calculate the feature matrix of the online feature library,perform K-means cluster analysis on the feature matrix,and fuse the similar online feature library to form the state feature library of the load equipment,so as to realize the extraction of the characteristics of the current array of the load equipment.The test results on private data sets and PLAID data sets show that the load feature extraction method proposed in this paper has good robustness in different power consumption scenarios.关键词
状态检测/负荷特征/周期电流数组/在线特征库/K-means算法Key words
state detection/load feature/periodic current array/state feature library/K-means clustering分类
信息技术与安全科学引用本文复制引用
王谱宇,耿路路,刘兴江,程含渺,方凯杰,张小平..基于在线特征库的非侵入式负荷特征提取方法[J].中国电机工程学报,2024,44(9):3489-3499,中插12,12.基金项目
国家自然科学基金项目(51807091) （51807091）
国防科技重点实验室基金项目(JCJQLB05406) （JCJQLB05406）
英国工程物理科学基金项目(EP/N032888/1). Project Supported by National Nature Science Foundation of China(51807091) （EP/N032888/1）
Foundation of Key Laboratory of Science and Technology for National Defense(JCJQLB05406) （JCJQLB05406）
Engineering and Physical Sciences Research Council(EPSRC EP/N032888/1). （EPSRC EP/N032888/1）
