电测与仪表2025，Vol.62Issue(5)：111-119,9.DOI:10.19753/j.issn1001-1390.2025.05.014
基于VMD和PSO-SVM的非侵入式负荷识别方法
Non-intrusive load identification method based on VMD and PSO-SVM
摘要
Abstract
Non-intrusive load monitoring is one of the important technologies of intelligent power consumption,a-mong which load decomposition and identification is an important link to realize the technology.In view of the ad-vantage of variational mode decomposition(VMD)in signal processing,a load identification algorithm based on variational mode decomposition and fast independent component analysis(VMD-FastICA)and variational mode de-camposition-entropy-particle swanm optimization fo optimizing support vector machines(VMD-Entropy-PSOSVM)is proposed.The total load power signal is decomposed using VMD to obtain multiple intrinsic mode functions(IMF),and then,the IMF is reconstructed based on the cliff criterion and singular value decomposition to virtual-ize single-channel blind source separation into multi-channel blind source separation into fast independent compo-nent analysis(FastICA)for load signal separation.Then,the energy and energy entropy of the modal components of the decomposed load waveform are obtained,and the multi-dimensional feature matrix input is constructed to es-tablish a particle swarm optimization-support vector machine particle swarm optimization for optimizing support vec-tor machines(PSO-SVM)for classification and identification of the load.The experimental algorithm is simulated using the reduced electricity dataset(REDD),and it is verified that the algorithm has better results in both decom-position and recognition compared to other algorithms.关键词
非侵入式负荷监测/单通道盲源分解/变分模态分解/能量熵/粒子群算法优化支持向量机Key words
non-intrusive load monitoring/single-channel blind source decomposition/variational modal decompo-sition/energy entropy/particle swarm optimization-support vector machine分类
动力与电气工程引用本文复制引用
杨锐,邹晓松,熊炜,袁旭峰,郑华俊,刘斌..基于VMD和PSO-SVM的非侵入式负荷识别方法[J].电测与仪表,2025,62(5):111-119,9.基金项目
国家自然科学基金资助项目(52067004) （52067004）
贵州省科学技术基金项目([2019]1058,[2019]1128) （[2019]1058,[2019]1128）
