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A load classification framework based on VMD and singular value energy difference spectrum
Chen, Shuo1; Guo, Kunya1; Zeng, Peng2; Lv, Xunming1; Jia, Zhida1; Yang JY(杨俊友)1
Department工业控制网络与系统研究室
Conference Name3rd IEEE International Conference on Energy Internet, ICEI 2019
Conference DateMay 27-31, 2019
Conference PlaceNanjing, China
Author of SourceGlobal Energy Interconnection Research Institute ; North China Electric Power University
Source PublicationProceedings - IEEE International Conference on Energy Internet, ICEI 2019
PublisherIEEE
Publication PlaceNew York
2019
Pages398-402
Indexed ByEI
EI Accession number20193607392979
Contribution Rank2
ISSN978-1-7281-1493-4
KeywordVMD energy difference spectrum load classification compactness
AbstractHigh load data dimension and insufficient sample characteristics challenge the load clustering accuracy. For this challenge, this paper proposes a load analysis method based on variational mode decomposition (VMD) and the energy difference spectrum of singular value (EDSSV). Firstly, the load data is decomposed by VMD algorithm. Simultaneously, the lowest frequency intrinsic function in the decomposition results is selected for EDSSV. The decomposition manifests load sample characteristics and reduces the load data dimension. Furthermore, the singular value is used to obtain an energy difference spectrum curve by EDSSV, which converts curve features to energy features and reduces the amount of data. The k-means clustering result of the original sample and the result of the energy difference spectrum curve are compared through compactness index. Compared with the k-means method, the result of clustering index CP with the proposed method is reduced by 0.0627, which shows that the clustering accuracy is improved. Also, the load data dimension is reduced by about 80%.
Language英语
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/25617
Collection工业控制网络与系统研究室
Corresponding AuthorChen, Shuo
Affiliation1.State Grid Liaoning Electric Power Co. Ltd., Shenyang, China
2.Key Laboratory of Networked Control Systems, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
Recommended Citation
GB/T 7714
Chen, Shuo,Guo, Kunya,Zeng, Peng,et al. A load classification framework based on VMD and singular value energy difference spectrum[C]//Global Energy Interconnection Research Institute, North China Electric Power University. New York:IEEE,2019:398-402.
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