Open AccessA Lossy Compression Algorithm for Phasor Measurement Units Data Based on Auto-encoder and Long Short Term Memory
Author(s) -
Shouxiang Wang,
Sheng Zhang,
Shiling Hu,
Rong Cui,
Haiwen Chen
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1972/1/012052
Subject(s) - lossy compression , lossless compression , computer science , data compression , encoder , algorithm , data compression ratio , phasor , real time computing , compression (physics) , image compression , power (physics) , electric power system , artificial intelligence , physics , materials science , quantum mechanics , composite material , operating system , image (mathematics) , image processing
With the wide deployment of phasor measurement units (PMU) in power system, the amount of data generated by various measurement devices is increasing, which brings new challenges to data transmission and storage. In this paper, a lossy data compression algorithm based on auto-encoder and Long Short-Term Memory (LSTM) is proposed for PMU data. Specifically, the auto-encoder is used to extract the features of the measurement data first, and then saved the feature vectors to achieve the effect of data compression. When need to decompress the measurement data, the compressed data is input into the decoder to achieve decompression. Compared with the traditional algorithms, the algorithm proposed in this paper can effectively reduce the reconstruction error. At the same time, it can be combined with the existing lossless compression algorithm to further improve the compression rate.