摘要
新一代能源互联网的数据采集须具有实时性、同步性和准确性。文章从同域采样与压缩采样结合的全新角度,提出一种可应用于新一代能源互联网的基于压缩感知的数据采集新方法。该方法在数据采集流程中,充分利用了压缩感知的同域空间投影和压缩信息测量的优势,并结合新一代能源互联网的数据特征,在KSVD(K-Singular Value Decomposition)字典学习算法的基础上,实现采集方法的数据稀疏化处理和数据传输处理。实验结果表明,所提方法具有优秀的数据传输量和重构精度,满足新一代能源互联网数据采集的应用要求。
The data collection of new generation energy internet must be real-time,synchronous and accurate.Therefore,from a new view which combines same-domain-sampling and compressing-sampling,a new data collection method based on compressed sensing is proposed,which is suitable for the new generation energy internet.In data collection procedure,the proposed method makes full use of the advantages in compressed sensing,that are same domain projection and compressing information measurement.Then,the sparsification and transmission of monitoring data are realized based on the K-SVD(K-Singular Value Decomposition)dictionary learning algorithm.Results from experiments show that the proposed data collection method has small communication amount and high data reconstruction accuracy,and satisfies the application requirements of data collection for new generation energy internet.
作者
杨杉
谭博
郭静波
Yang Shan;Tan Bo;Guo Jingbo(Department of Electrical Engineering,Tsinghua University,Beijing 100084 China)
出处
《可再生能源》
CAS
CSCD
北大核心
2022年第7期952-958,共7页
Renewable Energy Resources
基金
国家电网有限公司总部管理科技项目资助(面向5G的信息能源融合技术与装备研制5206002000DB)。
关键词
新一代能源互联网
数据采集
压缩感知
字典学习
K-SVD
new generation energy internet
data collection
compressed sensing
dictionary learning
K-SVD
