电力系统及其自动化学报2023，Vol.35Issue(12)：50-58,9.DOI:10.19635/j.cnki.csu-epsa.001187
配电网边缘计算轻量化负荷分解
Lightweight Load Decomposition in Distribution Network Using Edge Computing
摘要
Abstract
The key problem in non-intrusive load decomposition is how to realize an accurate detection of load events of unidentified equipment in real time.Aimed at this problem,a cooperative computing system on the cloud-edge side is designed,which mines the behavior feature of load data collected on the edge side and hence realizes an effective de-composition of load signal.A lightweight K-means clustering algorithm is proposed considering the constraints of index-es such as the computing and storage resources of embedded controllers on the edge side together with power consump-tion.The instantaneous peak value,instantaneous power variation and harmonic components are selected as clustering features to realize the identification of load category locally.A lightweight particle swarm optimization algorithm is de-signed to realize the combination of the dynamic clustering algorithm and features including the transient power and har-monic components.The identification accuracy of the electric energy monitoring algorithm designed in this paper is high-er than 97.79%for the REDD shared data set.In addition,the non-invasive load monitoring of daily power consumption data for 313 households in one community is realized.关键词
边缘计算/负荷辨识/群智能/负荷分解/特征聚类Key words
edge computing/load identification/swarm intelligence/load decomposition/feature clustering分类
信息技术与安全科学引用本文复制引用
蔡田田,杨英杰,陈波,邓清唐..配电网边缘计算轻量化负荷分解[J].电力系统及其自动化学报,2023,35(12):50-58,9.基金项目
国家重点研发计划资助项目(2020YFB0906000,2020YFB0906002) （2020YFB0906000,2020YFB0906002）
